Publications

@article{pmid34855359,

title = {Discovery and Optimization of a Novel Series of Competitive and Central Nervous System-Penetrant Protease-Activated Receptor 4 (PAR4) Inhibitors},

author = {Jeanette L Bertron and Matthew T Duvernay and Sidnee G Mitchell and Shannon T Smith and Jae G Maeng and Anna L Blobaum and Dexter C Davis and Jens Meiler and Heidi E Hamm and Craig W Lindsley},

doi = {10.1021/acschemneuro.1c00557},

issn = {1948-7193},

year  = {2021},

date = {2021-12-01},

journal = {ACS Chem Neurosci},

volume = {12},

number = {24},

pages = {4524--4534},

abstract = {The detailed pharmacology and therapeutic potential of the central PAR4 receptors are poorly understood due to a lack of potent, selective, and brain-penetrant tool compounds. Despite this, robust data with biochemical and genetic tools show the therapeutic potential of PAR4 antagonists in traumatic brain injury, Alzheimer's disease, Parkinson's disease, and other neurodegenerative disorders with a neuroinflammatory component. Thus, we performed a functional HTS campaign, identified a fundamentally new PAR4 competitive inhibitor chemotype, optimized this new series (increased potency >45-fold), discovered enantiospecific activity (though opposing preference for human versus mouse PAR4), and engendered high central nervous system penetration (rat 's of 0.52 to 4.2 and 's of 0.52 to 1.2).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34748541,

title = {Computational redesign of a fluorogen activating protein with Rosetta},

author = {Nina G Bozhanova and Joel M Harp and Brian J Bender and Alexey S Gavrikov and Dmitry A Gorbachev and Mikhail S Baranov and Christina B Mercado and Xuan Zhang and Konstantin A Lukyanov and Alexander S Mishin and Jens Meiler},

doi = {10.1371/journal.pcbi.1009555},

issn = {1553-7358},

year  = {2021},

date = {2021-11-01},

journal = {PLoS Comput Biol},

volume = {17},

number = {11},

pages = {e1009555},

abstract = {The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encoded fluorescent imaging tools through the design of fluorogen activating proteins (FAPs). While there is already a handful of such probes available, each of them went through laborious cycles of in vitro screening and selection. Computational modeling approaches are evolving incredibly fast right now and are demonstrating great results in many applications, including de novo protein design. It suggests that the easier task of fine-tuning the fluorogen-binding properties of an already functional protein in silico should be readily achievable. To test this hypothesis, we used Rosetta for computational ligand docking followed by protein binding pocket redesign to further improve the previously described FAP DiB1 that is capable of binding to a BODIPY-like dye M739. Despite an inaccurate initial docking of the chromophore, the incorporated mutations nevertheless improved multiple photophysical parameters as well as the overall performance of the tag. The designed protein, DiB-RM, shows higher brightness, localization precision, and apparent photostability in protein-PAINT super-resolution imaging compared to its parental variant DiB1. Moreover, DiB-RM can be cleaved to obtain an efficient split system with enhanced performance compared to a parental DiB-split system. The possible reasons for the inaccurate ligand binding pose prediction and its consequence on the outcome of the design experiment are further discussed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34845212,

title = {Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks},

author = {Julia Koehler Leman and Sergey Lyskov and Steven M Lewis and Jared Adolf-Bryfogle and Rebecca F Alford and Kyle Barlow and Ziv Ben-Aharon and Daniel Farrell and Jason Fell and William A Hansen and Ameya Harmalkar and Jeliazko Jeliazkov and Georg Kuenze and Justyna D Krys and Ajasja Ljubetič and Amanda L Loshbaugh and Jack Maguire and Rocco Moretti and Vikram Khipple Mulligan and Morgan L Nance and Phuong T Nguyen and Shane Ó Conchúir and Shourya S Roy Burman and Rituparna Samanta and Shannon T Smith and Frank Teets and Johanna K S Tiemann and Andrew Watkins and Hope Woods and Brahm J Yachnin and Christopher D Bahl and Chris Bailey-Kellogg and David Baker and Rhiju Das and Frank DiMaio and Sagar D Khare and Tanja Kortemme and Jason W Labonte and Kresten Lindorff-Larsen and Jens Meiler and William Schief and Ora Schueler-Furman and Justin B Siegel and Amelie Stein and Vladimir Yarov-Yarovoy and Brian Kuhlman and Andrew Leaver-Fay and Dominik Gront and Jeffrey J Gray and Richard Bonneau},

doi = {10.1038/s41467-021-27222-7},

issn = {2041-1723},

year  = {2021},

date = {2021-11-01},

journal = {Nat Commun},

volume = {12},

number = {1},

pages = {6947},

abstract = {Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34176159,

title = {RosettaCM for antibodies with very long HCDR3s and low template availability},

author = {Pranav Kodali and Clara T Schoeder and Samuel Schmitz and James E Crowe and Jens Meiler},

doi = {10.1002/prot.26166},

issn = {1097-0134},

year  = {2021},

date = {2021-11-01},

journal = {Proteins},

volume = {89},

number = {11},

pages = {1458--1472},

abstract = {Antibody-antigen co-crystal structures are a valuable resource for the fundamental understanding of antibody-mediated immunity. Determination of structures with antibodies in complex with their antigens, however, is a laborious task without guarantee of success. Therefore, homology modeling of antibodies and docking to their respective antigens has become a very important technique to drive antibody and vaccine design. The quality of the antibody modeling process is critical for the success of these endeavors. Here, we compare different computational protocols for predicting antibody structure from sequence in the biomolecular modeling software Rosetta-all of which use multiple existing antibody structures to guide modeling. Specifically, we compare protocols developed solely to predict antibody structure (RosettaAntibody, AbPredict) with a universal homology modeling protocol (RosettaCM). Following recent advances in homology modeling with multiple templates simultaneously, we propose that the use of multiple templates over the same antibody regions may improve modeling performance. To evaluate whether multi-template comparative modeling with RosettaCM can improve the modeling accuracy of antibodies over existing methods, this study compares the performance of the three modeling algorithms when modeling human antibodies taken from antibody-antigen co-crystal structures. In these benchmarking experiments, RosettaCM outperformed other methods when modeling antibodies with long HCDR3s and few available templates.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34818554,

title = {Molecular basis for the evolved instability of a human G-protein coupled receptor},

author = {Laura M Chamness and Nathan B Zelt and Haley R Harrington and Charles P Kuntz and Brian J Bender and Wesley D Penn and Joshua J Ziarek and Jens Meiler and Jonathan P Schlebach},

doi = {10.1016/j.celrep.2021.110046},

issn = {2211-1247},

year  = {2021},

date = {2021-11-01},

journal = {Cell Rep},

volume = {37},

number = {8},

pages = {110046},

abstract = {Membrane proteins are prone to misfolding and degradation. This is particularly true for mammalian forms of the gonadotropin-releasing hormone receptor (GnRHR). Although they function at the plasma membrane, mammalian GnRHRs accumulate within the secretory pathway. Their apparent instability is believed to have evolved through selection for attenuated GnRHR activity. Nevertheless, the molecular basis of this adaptation remains unclear. We show that adaptation coincides with a C-terminal truncation that compromises the translocon-mediated membrane integration of its seventh transmembrane domain (TM7). We also identify a series of polar residues in mammalian GnRHRs that compromise the membrane integration of TM2 and TM6. Reverting a lipid-exposed polar residue in TM6 to an ancestral hydrophobic residue restores expression with no impact on function. Evolutionary trends suggest variations in the polarity of this residue track with reproductive phenotypes. Our findings suggest that the marginal energetics of cotranslational folding can be exploited to tune membrane protein fitness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34529933,

title = {Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network},

author = {Souhrid Mukherjee and Joy D Cogan and John H Newman and John A Phillips and Rizwan Hamid and  and Jens Meiler and John A Capra},

doi = {10.1016/j.ajhg.2021.08.010},

issn = {1537-6605},

year  = {2021},

date = {2021-10-01},

journal = {Am J Hum Genet},

volume = {108},

number = {10},

pages = {1946--1963},

abstract = {Rare diseases affect millions of people worldwide, and discovering their genetic causes is challenging. More than half of the individuals analyzed by the Undiagnosed Diseases Network (UDN) remain undiagnosed. The central hypothesis of this work is that many of these rare genetic disorders are caused by multiple variants in more than one gene. However, given the large number of variants in each individual genome, experimentally evaluating combinations of variants for potential to cause disease is currently infeasible. To address this challenge, we developed the digenic predictor (DiGePred), a random forest classifier for identifying candidate digenic disease gene pairs by features derived from biological networks, genomics, evolutionary history, and functional annotations. We trained the DiGePred classifier by using DIDA, the largest available database of known digenic-disease-causing gene pairs, and several sets of non-digenic gene pairs, including variant pairs derived from unaffected relatives of UDN individuals. DiGePred achieved high precision and recall in cross-validation and on a held-out test set (PR area under the curve > 77%), and we further demonstrate its utility by using digenic pairs from the recent literature. In contrast to other approaches, DiGePred also appropriately controls the number of false positives when applied in realistic clinical settings. Finally, to enable the rapid screening of variant gene pairs for digenic disease potential, we freely provide the predictions of DiGePred on all human gene pairs. Our work enables the discovery of genetic causes for rare non-monogenic diseases by providing a means to rapidly evaluate variant gene pairs for the potential to cause digenic disease.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34241650,

title = {Ligand-binding and -scavenging of the chemerin receptor GPR1},

author = {Tobias F Fischer and Anne S Czerniak and Tina Weiß and Clara T Schoeder and Philipp Wolf and Oliver Seitz and Jens Meiler and Annette G Beck-Sickinger},

doi = {10.1007/s00018-021-03894-8},

issn = {1420-9071},

year  = {2021},

date = {2021-09-01},

journal = {Cell Mol Life Sci},

volume = {78},

number = {17-18},

pages = {6265--6281},

abstract = {Tight regulation of cytokines is essential for the initiation and resolution of inflammation. Chemerin, a mediator of innate immunity, mainly acts on chemokine-like receptor 1 (CMKLR1) to induce the migration of macrophages and dendritic cells. The role of the second chemerin receptor, G protein-coupled receptor 1 (GPR1), is still unclear. Here we demonstrate that GPR1 shows ligand-induced arrestin3 recruitment and internalization. The chemerin C-terminus triggers this activation by folding into a loop structure, binding to aromatic residues in the extracellular loops of GPR1. While this overall binding mode is shared between GPR1 and CMKLR1, differences in their respective extracellular loop 2 allowed for the design of the first GPR1-selective peptide. However, our results suggest that ligand-induced arrestin recruitment is not the only mode of action of GPR1. This receptor also displays constitutive internalization, which allows GPR1 to internalize inactive peptides efficiently by an activation-independent pathway. Our results demonstrate that GPR1 takes a dual role in regulating chemerin activity: as a signaling receptor for arrestin-based signaling on one hand, and as a scavenging receptor with broader ligand specificity on the other.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34171264,

title = {Co-occurring gain-of-function mutations in HER2 and HER3 modulate HER2/HER3 activation, oncogenesis, and HER2 inhibitor sensitivity},

author = {Ariella B Hanker and Benjamin P Brown and Jens Meiler and Arnaldo Marín and Harikrishna S Jayanthan and Dan Ye and Chang-Ching Lin and Hiroaki Akamatsu and Kyung-Min Lee and Sumanta Chatterjee and Dhivya R Sudhan and Alberto Servetto and Monica Red Brewer and James P Koch and Jonathan H Sheehan and Jie He and Alshad S Lalani and Carlos L Arteaga},

doi = {10.1016/j.ccell.2021.06.001},

issn = {1878-3686},

year  = {2021},

date = {2021-08-01},

journal = {Cancer Cell},

volume = {39},

number = {8},

pages = {1099--1114.e8},

abstract = {Activating mutations in HER2 (ERBB2) drive the growth of a subset of breast and other cancers and tend to co-occur with HER3 (ERBB3) missense mutations. The HER2 tyrosine kinase inhibitor neratinib has shown clinical activity against HER2-mutant tumors. To characterize the role of HER3 mutations in HER2-mutant tumors, we integrate computational structural modeling with biochemical and cell biological analyses. Computational modeling predicts that the frequent HER3 kinase domain mutation enhances the affinity of HER2/HER3 and reduces binding of HER2 to its inhibitor neratinib. Co-expression of mutant HER2/HER3 enhances HER2/HER3 co-immunoprecipitation and ligand-independent activation of HER2/HER3 and PI3K/AKT, resulting in enhanced growth, invasiveness, and resistance to HER2-targeted therapies, which can be reversed by combined treatment with PI3Kα inhibitors. Our results provide a mechanistic rationale for the evolutionary selection of co-occurring HER2/HER3 mutations and the recent clinical observations that HER3 mutations are associated with a poor response to neratinib in HER2-mutant cancers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34416147,

title = {Therapeutic alphavirus cross-reactive E1 human antibodies inhibit viral egress},

author = {Lauren E Williamson and Kristen M Reeder and Kevin Bailey and Minh H Tran and Vicky Roy and Mallorie E Fouch and Nurgun Kose and Andrew Trivette and Rachel S Nargi and Emma S Winkler and Arthur S Kim and Christopher Gainza and Jessica Rodriguez and Erica Armstrong and Rachel E Sutton and Joseph Reidy and Robert H Carnahan and W Hayes McDonald and Clara T Schoeder and William B Klimstra and Edgar Davidson and Benjamin J Doranz and Galit Alter and Jens Meiler and Kevin L Schey and Justin G Julander and Michael S Diamond and James E Crowe},

doi = {10.1016/j.cell.2021.07.033},

issn = {1097-4172},

year  = {2021},

date = {2021-08-01},

journal = {Cell},

volume = {184},

number = {17},

pages = {4430--4446.e22},

abstract = {Alphaviruses cause severe arthritogenic or encephalitic disease. The E1 structural glycoprotein is highly conserved in these viruses and mediates viral fusion with host cells. However, the role of antibody responses to the E1 protein in immunity is poorly understood. We isolated E1-specific human monoclonal antibodies (mAbs) with diverse patterns of recognition for alphaviruses (ranging from Eastern equine encephalitis virus [EEEV]-specific to alphavirus cross-reactive) from survivors of natural EEEV infection. Antibody binding patterns and epitope mapping experiments identified differences in E1 reactivity based on exposure of epitopes on the glycoprotein through pH-dependent mechanisms or presentation on the cell surface prior to virus egress. Therapeutic efficacy in vivo of these mAbs corresponded with potency of virus egress inhibition in vitro and did not require Fc-mediated effector functions for treatment against subcutaneous EEEV challenge. These studies reveal the molecular basis for broad and protective antibody responses to alphavirus E1 proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34236204,

title = {A Multitask Deep-Learning Method for Predicting Membrane Associations and Secondary Structures of Proteins},

author = {Bian Li and Jeffrey Mendenhall and John A Capra and Jens Meiler},

doi = {10.1021/acs.jproteome.1c00410},

issn = {1535-3907},

year  = {2021},

date = {2021-08-01},

journal = {J Proteome Res},

volume = {20},

number = {8},

pages = {4089--4100},

abstract = {Prediction of residue-level structural attributes and protein-level structural classes helps model protein tertiary structures and understand protein functions. Existing methods are either specialized on only one class of proteins or developed to predict only a specific type of residue-level attribute. In this work, we develop a new deep-learning method, named Membrane Association and Secondary Structure Predictor (MASSP), for accurately predicting both residue-level structural attributes (secondary structure, location, orientation, and topology) and protein-level structural classes (bitopic, α-helical, β-barrel, and soluble). MASSP integrates a multilayer two-dimensional convolutional neural network (2D-CNN) with a long short-term memory (LSTM) neural network into a multitasking framework. Our comparison shows that MASSP performs equally well or better than the state-of-the-art methods in predicting residue-level secondary structures, boundaries of transmembrane segments, and topology. Furthermore, it achieves outstanding accuracy in predicting protein-level structural classes. MASSP automatically distinguishes the structural classes of input sequences and identifies transmembrane segments and topologies if present, making it broadly applicable to different classes of proteins. In summary, MASSP's good performance and broad applicability make it well suited for annotating residue-level attributes and protein-level structural classes at the proteome scale.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34437426,

title = {The Allosteric Activation of α7 nAChR by α-Conotoxin MrIC Is Modified by Mutations at the Vestibular Site},

author = {Alican Gulsevin and Roger L Papke and Clare Stokes and Hue N T Tran and Aihua H Jin and Irina Vetter and Jens Meiler},

doi = {10.3390/toxins13080555},

issn = {2072-6651},

year  = {2021},

date = {2021-08-01},

journal = {Toxins (Basel)},

volume = {13},

number = {8},

abstract = {α-conotoxins are 13-19 amino acid toxin peptides that bind various nicotinic acetylcholine receptor (nAChR) subtypes. α-conotoxin Mr1.7c (MrIC) is a 17 amino acid peptide that targets α7 nAChR. Although MrIC has no activating effect on α7 nAChR when applied by itself, it evokes a large response when co-applied with the type II positive allosteric modulator PNU-120596, which potentiates the α7 nAChR response by recovering it from a desensitized state. A lack of standalone activity, despite activation upon co-application with a positive allosteric modulator, was previously observed for molecules that bind to an extracellular domain allosteric activation (AA) site at the vestibule of the receptor. We hypothesized that MrIC may activate α7 nAChR allosterically through this site. We ran voltage-clamp electrophysiology experiments and in silico peptide docking calculations in order to gather evidence in support of α7 nAChR activation by MrIC through the AA site. The experiments with the wild-type α7 nAChR supported an allosteric mode of action, which was confirmed by the significantly increased MrIC + PNU-120596 responses of three α7 nAChR AA site mutants that were designed in silico to improve MrIC binding. Overall, our results shed light on the allosteric activation of α7 nAChR by MrIC and suggest the involvement of the AA site.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33947782,

title = {Familial Autonomic Ganglionopathy Caused by Rare  Genetic Variants},

author = {Cyndya A Shibao and Karen Joos and John A Phillips and Joy Cogan and John H Newman and Rizwan Hamid and Jens Meiler and John Capra and Jonathan Sheehan and Francesco Vetrini and Yaping Yang and Bonnie Black and André Diedrich and David Roberston and Italo Biaggioni},

doi = {10.1212/WNL.0000000000012143},

issn = {1526-632X},

year  = {2021},

date = {2021-07-01},

journal = {Neurology},

volume = {97},

number = {2},

pages = {e145--e155},

abstract = {OBJECTIVE: To determine the molecular basis of a new monogenetic recessive disorder that results in familial autonomic ganglionopathy with diffuse autonomic failure.nnMETHODS: Two adult siblings from one family (I-4 and I-5) and another participant from a second family (II-3) presented with severe neurogenic orthostatic hypotension (nOH), small nonreactive pupils, and constipation. All 3 affected members had low norepinephrine levels and diffuse panautonomic failure.nnRESULTS: Whole exome sequencing of DNA from I-4 and I-5 showed compound heterozygosity for c.907_908delCT (p.L303Dfs*115)/c.688 G>A (p.D230N) pathologic variants in the acetylcholine receptor, neuronal nicotinic, α3 subunit gene (). II-3 from the second family was homozygous for the same frameshift (fs) variant (p.L303Dfs*115//p.L303Dfs*115).  encodes a critical subunit of the nicotinic acetylcholine receptors (nAChRs) responsible for fast synaptic transmission in the autonomic ganglia. The fs variant is clearly pathogenic and the p.D230N variant is predicted to be damaging (SIFT)/probably damaging (PolyPhen2). The p.D230N variant lies on the interface between CHRNA3 and other nAChR subunits based on structural modeling and is predicted to destabilize the nAChR pentameric complex.nnCONCLUSIONS: We report a novel genetic disease that affected 3 individuals from 2 unrelated families who presented with severe nOH, miosis, and constipation. These patients had rare pathologic variants in the  gene that cosegregate with and are predicted to be the likely cause of their diffuse panautonomic failure.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34133419,

title = {Methodology for rigorous modeling of protein conformational changes by Rosetta using DEER distance restraints},

author = {Diego Del Alamo and Kevin L Jagessar and Jens Meiler and Hassane S Mchaourab},

doi = {10.1371/journal.pcbi.1009107},

issn = {1553-7358},

year  = {2021},

date = {2021-06-01},

journal = {PLoS Comput Biol},

volume = {17},

number = {6},

pages = {e1009107},

abstract = {We describe an approach for integrating distance restraints from Double Electron-Electron Resonance (DEER) spectroscopy into Rosetta with the purpose of modeling alternative protein conformations from an initial experimental structure. Fundamental to this approach is a multilateration algorithm that harnesses sets of interconnected spin label pairs to identify optimal rotamer ensembles at each residue that fit the DEER decay in the time domain. Benchmarked relative to data analysis packages, the algorithm yields comparable distance distributions with the advantage that fitting the DEER decay and rotamer ensemble optimization are coupled. We demonstrate this approach by modeling the protonation-dependent transition of the multidrug transporter PfMATE to an inward facing conformation with a deviation to the experimental structure of less than 2Å Cα RMSD. By decreasing spin label rotamer entropy, this approach engenders more accurate Rosetta models that are also more closely clustered, thus setting the stage for more robust modeling of protein conformational changes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33847017,

title = {Clinical, neuroimaging, and molecular spectrum of TECPR2-associated hereditary sensory and autonomic neuropathy with intellectual disability},

author = {Sonja Neuser and Barbara Brechmann and Gali Heimer and Ines Brösse and Susanna Schubert and Lauren O'Grady and Michael Zech and Siddharth Srivastava and David A Sweetser and Yasemin Dincer and Volker Mall and Juliane Winkelmann and Christian Behrends and Basil T Darras and Robert J Graham and Parul Jayakar and Barry Byrne and Bat El Bar-Aluma and Yael Haberman and Amir Szeinberg and Hesham M Aldhalaan and Mais Hashem and Amal Al Tenaiji and Omar Ismayl and Asma E Al Nuaimi and Karima Maher and Shahnaz Ibrahim and Fatima Khan and Henry Houlden and Vijayalakshmi S Ramakumaran and Alistair T Pagnamenta and Jennifer E Posey and James R Lupski and Wen-Hann Tan and Gehad ElGhazali and Isabella Herman and Tatiana Muñoz and Gabriela M Repetto and Angelika Seitz and Mandy Krumbiegel and Maria Cecilia Poli and Usha Kini and Stephanie Efthymiou and Jens Meiler and Reza Maroofian and Fowzan S Alkuraya and Rami Abou Jamra and Bernt Popp and Bruria Ben-Zeev and Darius Ebrahimi-Fakhari},

doi = {10.1002/humu.24206},

issn = {1098-1004},

year  = {2021},

date = {2021-06-01},

journal = {Hum Mutat},

volume = {42},

number = {6},

pages = {762--776},

abstract = {Bi-allelic TECPR2 variants have been associated with a complex syndrome with features of both a neurodevelopmental and neurodegenerative disorder. Here, we provide a comprehensive clinical description and variant interpretation framework for this genetic locus. Through international collaboration, we identified 17 individuals from 15 families with bi-allelic TECPR2-variants. We systemically reviewed clinical and molecular data from this cohort and 11 cases previously reported. Phenotypes were standardized using Human Phenotype Ontology terms. A cross-sectional analysis revealed global developmental delay/intellectual disability, muscular hypotonia, ataxia, hyporeflexia, respiratory infections, and central/nocturnal hypopnea as core manifestations. A review of brain magnetic resonance imaging scans demonstrated a thin corpus callosum in 52%. We evaluated 17 distinct variants. Missense variants in TECPR2 are predominantly located in the N- and C-terminal regions containing β-propeller repeats. Despite constituting nearly half of disease-associated TECPR2 variants, classifying missense variants as (likely) pathogenic according to ACMG criteria remains challenging. We estimate a pathogenic variant carrier frequency of 1/1221 in the general and 1/155 in the Jewish Ashkenazi populations. Based on clinical, neuroimaging, and genetic data, we provide recommendations for variant reporting, clinical assessment, and surveillance/treatment of individuals with TECPR2-associated disorder. This sets the stage for future prospective natural history studies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33865871,

title = {Structural Perspective on Ancient Neuropeptide Y-like System reveals Hallmark Features for Peptide Recognition and Receptor Activation},

author = {Miron Mikhailowitsch Gershkovich and Victoria Elisabeth Groß and Oanh Vu and Clara Tabea Schoeder and Jens Meiler and Simone Prömel and Anette Kaiser},

doi = {10.1016/j.jmb.2021.166992},

issn = {1089-8638},

year  = {2021},

date = {2021-06-01},

journal = {J Mol Biol},

volume = {433},

number = {13},

pages = {166992},

abstract = {The neuropeptide Y (NPY) family is a peptide-activated G protein-coupled receptor system conserved across all bilaterians, and is involved in food intake, learning, and behavior. We hypothesized that comparing the NPY system in evolutionarily ancient organisms can reveal structural determinants of peptide recognition and receptor activation conserved in evolution. To test this hypothesis, we investigated the homologous FLP/NPR system of the protostome C.elegans. For three prototypic peptide-receptor complexes representing different ligand types, we integrate extensive functional data into structural models of the receptors. Common features include acidic patches in the extracellular loops (ECLs) of the receptors that cooperatively 'draw' the peptide into the binding pocket, which was functionally validated in vivo. A structurally conserved glutamate in the ECL2 anchors the peptides by a conserved salt bridge to the arginine of the RFamide motif. Beyond this conserved interaction, peptide binding show variability enabled by receptor-specific interactions. The family-conserved residue Q is a key player for peptide binding and receptor activation. Altered interaction patterns at Q may drastically increase the efficacy to activate the receptor.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33640379,

title = {Structural determinants of cholesterol recognition in helical integral membrane proteins},

author = {Brennica Marlow and Georg Kuenze and Bian Li and Charles R Sanders and Jens Meiler},

doi = {10.1016/j.bpj.2021.02.028},

issn = {1542-0086},

year  = {2021},

date = {2021-05-01},

journal = {Biophys J},

volume = {120},

number = {9},

pages = {1592--1604},

abstract = {Cholesterol is an integral component of mammalian membranes. It has been shown to modulate membrane fluidity and dynamics and alter integral membrane protein function. However, understanding the molecular mechanisms of how cholesterol impacts protein function is complicated by limited and conflicting structural data. Because of the nature of the crystallization and cryo-EM structure determination, it is difficult to distinguish between specific and biologically relevant interactions and a nonspecific association. The only widely recognized search algorithm for cholesterol-integral-membrane-protein interaction sites is sequence based, i.e., searching for the so-called "Cholesterol Recognition/interaction Amino acid Consensus" motif. Although these motifs are present in numerous integral membrane proteins, there is inconclusive evidence to support their necessity or sufficiency for cholesterol binding. Here, we leverage the increasing number of experimental cholesterol-integral-membrane-protein structures to systematically analyze putative interaction sites based on their spatial arrangement and evolutionary conservation. This analysis creates three-dimensional representations of general cholesterol interaction sites that form clusters across multiple integral membrane protein classes. We also classify cholesterol-integral-membrane-protein interaction sites as either likely-specific or nonspecific. Information gleaned from our characterization will eventually enable a structure-based approach to predict and design cholesterol-integral-membrane-protein interaction sites.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34002696,

title = {Psychomotor impairments and therapeutic implications revealed by a mutation associated with infantile Parkinsonism-Dystonia},

author = {Jenny I Aguilar and Mary Hongying Cheng and Josep Font and Alexandra C Schwartz and Kaitlyn Ledwitch and Amanda Duran and Samuel J Mabry and Andrea N Belovich and Yanqi Zhu and Angela M Carter and Lei Shi and Manju A Kurian and Cristina Fenollar-Ferrer and Jens Meiler and Renae Monique Ryan and Hassane S Mchaourab and Ivet Bahar and Heinrich Jg Matthies and Aurelio Galli},

doi = {10.7554/eLife.68039},

issn = {2050-084X},

year  = {2021},

date = {2021-05-01},

journal = {Elife},

volume = {10},

abstract = {Parkinson disease (PD) is a progressive, neurodegenerative disorder affecting over 6.1 million people worldwide. Although the cause of PD remains unclear, studies of highly penetrant mutations identified in early-onset familial parkinsonism have contributed to our understanding of the molecular mechanisms underlying disease pathology. Dopamine (DA) transporter (DAT) deficiency syndrome (DTDS) is a distinct type of infantile parkinsonism-dystonia that shares key clinical features with PD, including motor deficits (progressive bradykinesia, tremor, hypomimia) and altered DA neurotransmission. Here, we define structural, functional, and behavioral consequences of a Cys substitution at R445 in human DAT (hDAT R445C), identified in a patient with DTDS. We found that this R445 substitution disrupts a phylogenetically conserved intracellular (IC) network of interactions that compromise the hDAT IC gate. This is demonstrated by both Rosetta molecular modeling and fine-grained simulations using hDAT R445C, as well as EPR analysis and X-ray crystallography of the bacterial homolog leucine transporter. Notably, the disruption of this IC network of interactions supported a channel-like intermediate of hDAT and compromised hDAT function. We demonstrate that  expressing hDAT R445C show impaired hDAT activity, which is associated with DA dysfunction in isolated brains and with abnormal behaviors monitored at high-speed time resolution. We show that hDAT R445C  exhibit motor deficits, lack of motor coordination (i.e. flight coordination) and phenotypic heterogeneity in these behaviors that is typically associated with DTDS and PD. These behaviors are linked with altered dopaminergic signaling stemming from loss of DA neurons and decreased DA availability. We rescued flight coordination with chloroquine, a lysosomal inhibitor that enhanced DAT expression in a heterologous expression system. Together, these studies shed some light on how a DTDS-linked DAT mutation underlies DA dysfunction and, possibly, clinical phenotypes shared by DTDS and PD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33851970,

title = {An arginine residue in the outer segment of hASIC1a TM1 affects both proton affinity and channel desensitization},

author = {Zhuyuan Chen and Georg Kuenze and Jens Meiler and Cecilia M Canessa},

doi = {10.1085/jgp.202012802},

issn = {1540-7748},

year  = {2021},

date = {2021-05-01},

journal = {J Gen Physiol},

volume = {153},

number = {5},

abstract = {Acid-sensing ion channels (ASICs) respond to changes in pH in the central and peripheral nervous systems and participate in synaptic plasticity and pain perception. Understanding the proton-mediated gating mechanism remains elusive despite the of their structures in various conformational states. We report here that R64, an arginine located in the outer segment of the first transmembrane domain of all three isoforms of mammalian ASICs, markedly impacts the apparent proton affinity of activation and the degree of desensitization from the open and preopen states. Rosetta calculations of free energy changes predict that substitutions of R64 in hASIC1a by aromatic residues destabilize the closed conformation while stabilizing the open conformation. Accordingly, F64 enhances the efficacy of proton-mediated gating of hASIC1a, which increases the apparent pH50 and facilitates channel opening when only one or two subunits are activated. F64 also lengthens the duration of opening events, thus keeping channels open for extended periods of time and diminishing low pH-induced desensitization. Our results indicate that activation of a proton sensor(s) with pH50 equal to or greater than pH 7.2-7.1 opens F64hASIC1a, whereas it induces steady-state desensitization in wildtype channels due to the high energy of activation imposed by R64, which prevents opening of the pore. Together, these findings suggest that activation of a high-affinity proton-sensor(s) and a common gating mechanism may mediate the processes of activation and steady-state desensitization of hASIC1a.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33730029,

title = {Prediction of amphipathic helix-membrane interactions with Rosetta},

author = {Alican Gulsevin and Jens Meiler},

doi = {10.1371/journal.pcbi.1008818},

issn = {1553-7358},

year  = {2021},

date = {2021-03-01},

journal = {PLoS Comput Biol},

volume = {17},

number = {3},

pages = {e1008818},

abstract = {Amphipathic helices have hydrophobic and hydrophilic/charged residues situated on opposite faces of the helix. They can anchor peripheral membrane proteins to the membrane, be attached to integral membrane proteins, or exist as independent peptides. Despite the widespread presence of membrane-interacting amphipathic helices, there is no computational tool within Rosetta to model their interactions with membranes. In order to address this need, we developed the AmphiScan protocol with PyRosetta, which runs a grid search to find the most favorable position of an amphipathic helix with respect to the membrane. The performance of the algorithm was tested in benchmarks with the RosettaMembrane, ref2015_memb, and franklin2019 score functions on six engineered and 44 naturally-occurring amphipathic helices using membrane coordinates from the OPM and PDBTM databases, OREMPRO server, and MD simulations for comparison. The AmphiScan protocol predicted the coordinates of amphipathic helices within less than 3Å of the reference structures and identified membrane-embedded residues with a Matthews Correlation Constant (MCC) of up to 0.57. Overall, AmphiScan stands as fast, accurate, and highly-customizable protocol that can be pipelined with other Rosetta and Python applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33221380,

title = {Identification of a novel leptin receptor (LEPR) variant and proof of functional relevance directing treatment decisions in patients with morbid obesity},

author = {Franziska Voigtmann and Philipp Wolf and Kathrin Landgraf and Robert Stein and Jürgen Kratzsch and Samuel Schmitz and Rami Abou Jamra and Matthias Blüher and Jens Meiler and Annette G Beck-Sickinger and Wieland Kiess and Antje Körner},

doi = {10.1016/j.metabol.2020.154438},

issn = {1532-8600},

year  = {2021},

date = {2021-03-01},

journal = {Metabolism},

volume = {116},

pages = {154438},

abstract = {BACKGROUND: Deficiency in the leptin-leptin receptor (LEPR) axis leads to severe, and potentially treatable, obesity in humans. To guide clinical decision-making, the functional relevance of variants in the LEPR gene needs to be carefully investigated.nnCASES AND METHODS: We characterized the functional impact of LEPR variants identified in two patients with severe early-onset obesity (1: compound heterozygous for the novel variant p.Tyr411del and p.Trp664Arg; 2: heterozygous for p.Arg612His) by investigating leptin-mediated signaling, leptin binding, receptor expression on cell surfaces, and receptor dimerization and activation for either wild-type and/or mutant LEPR.nnRESULTS: Leptin-induced STAT3-phosphorylation was blunted the novel p.Tyr411del or the p.Trp664Arg variant and mildly reduced with the p.Arg612His variant. Computational structure prediction suggested impaired leptin binding for all three LEPR variants. Experimentally, reduced leptin binding of all mutant proteins was due to diminished LEPR expression on the cell surface, with the p.Trp664Arg mutations being the most affected. Considering the heterozygosity in our patients, we assessed the heterodimerization capacity with the wild-type LEPR, which was retained for the p.Tyr411del and p.Arg612His variants. Finally, mimicking (compound) heterozygosity, we confirmed abolished STAT3-phosphorylation for the variant combination [p.Tyr411del + p.Trp664Arg] as found in patient 1, whereas it was retained for [p.Arg612His + wilde type] as found in patient 2.nnCONCLUSIONS: The novel p.Tyr411del mutation causes complete loss of function alone (and combined with p.Trp664Arg) and is likely the cause for the early onset obesity, qualifying the patient for pharmacologic treatment. Heterozygosity for the p.Arg612His variant, however, appears unlikely to be solely responsible for the phenotype.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33705117,

title = {Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design},

author = {Clara T Schoeder and Samuel Schmitz and Jared Adolf-Bryfogle and Alexander M Sevy and Jessica A Finn and Marion F Sauer and Nina G Bozhanova and Benjamin K Mueller and Amandeep K Sangha and Jaume Bonet and Jonathan H Sheehan and Georg Kuenze and Brennica Marlow and Shannon T Smith and Hope Woods and Brian J Bender and Cristina E Martina and Diego Del Alamo and Pranav Kodali and Alican Gulsevin and William R Schief and Bruno E Correia and James E Crowe and Jens Meiler and Rocco Moretti},

doi = {10.1021/acs.biochem.0c00912},

issn = {1520-4995},

year  = {2021},

date = {2021-03-01},

journal = {Biochemistry},

volume = {60},

number = {11},

pages = {825--846},

abstract = {Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33595306,

title = {Highly Selective Y Receptor Antagonist Binds in an Allosteric Binding Pocket},

author = {Corinna Schüß and Oanh Vu and Mario Schubert and Yu Du and Nigam M Mishra and Iain R Tough and Jan Stichel and C David Weaver and Kyle A Emmitte and Helen M Cox and Jens Meiler and Annette G Beck-Sickinger},

doi = {10.1021/acs.jmedchem.0c02000},

issn = {1520-4804},

year  = {2021},

date = {2021-03-01},

journal = {J Med Chem},

volume = {64},

number = {5},

pages = {2801--2814},

abstract = {Human neuropeptide Y receptors (YR, YR, YR, and YR) belong to the superfamily of G protein-coupled receptors and play an important role in the regulation of food intake and energy metabolism. We identified and characterized the first selective YR allosteric antagonist ()VU0637120, an important step toward validating Y receptors as therapeutic targets for metabolic diseases. To obtain insight into the antagonistic mechanism of ()VU0637120, we conducted a variety of in vitro, ex vivo, and in silico studies. These studies revealed that ()VU0637120 selectively inhibits native YR function and binds in an allosteric site located below the binding pocket of the endogenous ligand pancreatic polypeptide in the core of the YR transmembrane domains. Taken together, our studies provide a first-of-its-kind tool for probing YR function and improve the general understanding of allosteric modulation, ultimately contributing to the rational development of allosteric modulators for peptide-activated G protein-coupled receptors (GPCRs).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33705662,

title = {Cyclic Analogues of the Chemerin C-Terminus Mimic a Loop Conformation Essential for Activating the Chemokine-like Receptor 1},

author = {Tobias F Fischer and Clara T Schoeder and Tristan Zellmann and Jan Stichel and Jens Meiler and Annette G Beck-Sickinger},

doi = {10.1021/acs.jmedchem.0c01804},

issn = {1520-4804},

year  = {2021},

date = {2021-03-01},

journal = {J Med Chem},

volume = {64},

number = {6},

pages = {3048--3058},

abstract = {The chemokine-like receptor 1 (CMKLR1) is a promising target for treating autoinflammatory diseases, cancer, and reproductive disorders. However, the interaction between CMKLR1 and its protein-ligand chemerin remains uncharacterized, and no drugs targeting this interaction have passed clinical trials. Here, we identify the binding mode of chemerin-9, the C-terminus of chemerin, at the receptor by combining complementary mutagenesis with structure-based modeling. Incorporating our experimental data, we present a detailed model of this binding site, including experimentally confirmed pairwise interactions for the most critical ligand residues: Chemerin-9 residue F binds to a hydrophobic pocket in CMKLR1 formed by the extracellular loop (ECL) 2, while F interacts with Y, suggesting a turn-like structure. On the basis of this model, we created the first cyclic peptide with nanomolar activity, confirming the overall binding conformation. This constrained agonist mimics the loop conformation adopted by the natural ligand and can serve as a lead compound for future drug design.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33654076,

title = {Structure-function analysis of oncogenic EGFR Kinase Domain Duplication reveals insights into activation and a potential approach for therapeutic targeting},

author = {Zhenfang Du and Benjamin P Brown and Soyeon Kim and Donna Ferguson and Dean C Pavlick and Gowtham Jayakumaran and Ryma Benayed and Jean-Nicolas Gallant and Yun-Kai Zhang and Yingjun Yan and Monica Red-Brewer and Siraj M Ali and Alexa B Schrock and Ahmet Zehir and Marc Ladanyi and Adam W Smith and Jens Meiler and Christine M Lovly},

doi = {10.1038/s41467-021-21613-6},

issn = {2041-1723},

year  = {2021},

date = {2021-03-01},

journal = {Nat Commun},

volume = {12},

number = {1},

pages = {1382},

abstract = {Mechanistic understanding of oncogenic variants facilitates the development and optimization of treatment strategies. We recently identified in-frame, tandem duplication of EGFR exons 18 - 25, which causes EGFR Kinase Domain Duplication (EGFR-KDD). Here, we characterize the prevalence of ERBB family KDDs across multiple human cancers and evaluate the functional biochemistry of EGFR-KDD as it relates to pathogenesis and potential therapeutic intervention. We provide computational and experimental evidence that EGFR-KDD functions by forming asymmetric EGF-independent intra-molecular and EGF-dependent inter-molecular dimers. Time-resolved fluorescence microscopy and co-immunoprecipitation reveals EGFR-KDD can form ligand-dependent inter-molecular homo- and hetero-dimers/multimers. Furthermore, we show that inhibition of EGFR-KDD activity is maximally achieved by blocking both intra- and inter-molecular dimerization. Collectively, our findings define a previously unrecognized model of EGFR dimerization, providing important insights for the understanding of EGFR activation mechanisms and informing personalized treatment of patients with tumors harboring EGFR-KDD. Finally, we establish ERBB KDDs as recurrent oncogenic events in multiple cancers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33496578,

title = {General Purpose Structure-Based Drug Discovery Neural Network Score Functions with Human-Interpretable Pharmacophore Maps},

author = {Benjamin P Brown and Jeffrey Mendenhall and Alexander R Geanes and Jens Meiler},

doi = {10.1021/acs.jcim.0c01001},

issn = {1549-960X},

year  = {2021},

date = {2021-02-01},

journal = {J Chem Inf Model},

volume = {61},

number = {2},

pages = {603--620},

abstract = {The BioChemical Library (BCL) is an academic open-source cheminformatics toolkit comprising ligand-based virtual high-throughput screening (vHTS) tools such as quantitative structure-activity/property relationship (QSAR/QSPR) modeling, small molecule flexible alignment, small molecule conformer generation, and more. Here, we expand the capabilities of the BCL to include structure-based virtual screening. We introduce two new score functions, BCL-AffinityNet and BCL-DockANNScore, based on novel distance-dependent signed protein-ligand atomic property correlations. Both metrics are conventional feed-forward dropout neural networks trained on the new descriptors. We demonstrate that BCL-AffinityNet is one of the top performing score functions on the comparative assessment of score functions 2016 affinity prediction and affinity ranking tasks. We also demonstrate that BCL-AffinityNet performs well on the CSAR-NRC HiQ I and II test sets. Furthermore, we demonstrate that BCL-DockANNScore is competitive with multiple state-of-the-art methods on the docking power and screening power tasks. Finally, we show how our models can be decomposed into human-interpretable pharmacophore maps to aid in hit/lead optimization. Altogether, our results expand the utility of the BCL for structure-based scoring to aid small molecule discovery and design. BCL-AffinityNet, BCL-DockANNScore, and the pharmacophore mapping application, as well as the remainder of the BCL cheminformatics toolkit, are freely available with an academic license at the BCL Commons site hosted on http://meilerlab.org/.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33600800,

title = {Disease-linked supertrafficking of a potassium channel},

author = {Hui Huang and Laura M Chamness and Carlos G Vanoye and Georg Kuenze and Jens Meiler and Alfred L George and Jonathan Patrick Schlebach and Charles R Sanders},

doi = {10.1016/j.jbc.2021.100423},

issn = {1083-351X},

year  = {2021},

date = {2021-01-01},

journal = {J Biol Chem},

volume = {296},

pages = {100423},

abstract = {Gain-of-function (GOF) mutations in the voltage-gated potassium channel subfamily Q member 1 (KCNQ1) can induce cardiac arrhythmia. In this study, it was tested whether any of the known human GOF disease mutations in KCNQ1 act by increasing the amount of KCNQ1 that reaches the cell surface-"supertrafficking." Seven of the 15 GOF mutants tested were seen to surface traffic more efficiently than the WT channel. Among these, we found that the levels of R231C KCNQ1 in the plasma membrane were fivefold higher than the WT channel. This was shown to arise from the combined effects of enhanced efficiency of translocon-mediated membrane integration of the S4 voltage-sensor helix and from enhanced post-translational folding/trafficking related to the energetic linkage of C231 with the V129 and F166 side chains. Whole-cell electrophysiology recordings confirmed that R231C KCNQ1 in complex with the voltage-gated potassium channel-regulatory subfamily E member 1 not only exhibited constitutive conductance but also revealed that the single-channel activity of this mutant is only 20% that of WT. The GOF phenotype associated with R231C therefore reflects the effects of supertrafficking and constitutive channel activation, which together offset reduced channel activity. These investigations show that membrane protein supertrafficking can contribute to human disease.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33210733,

title = {Lipocalin Blc is a potential heme-binding protein},

author = {Nina G Bozhanova and M Wade Calcutt and William N Beavers and Benjamin P Brown and Eric P Skaar and Jens Meiler},

doi = {10.1002/1873-3468.14001},

issn = {1873-3468},

year  = {2021},

date = {2021-01-01},

journal = {FEBS Lett},

volume = {595},

number = {2},

pages = {206--219},

abstract = {Lipocalins are a superfamily of functionally diverse proteins defined by a well-conserved tertiary structure despite variation in sequence. Lipocalins bind and transport small hydrophobic molecules in organisms of all kingdoms. However, there is still uncertainty regarding the function of some members of the family, including bacterial lipocalin Blc from Escherichia coli. Here, we present evidence that lipocalin Blc may be involved in heme binding, trans-periplasmic transport, or heme storage. This conclusion is supported by a cocrystal structure, mass-spectrometric data, absorption titration, and in silico analysis. Binding of heme is observed at low micromolar range with one-to-one ligand-to-protein stoichiometry. However, the absence of classical coordination to the iron atom leaves the possibility that the primary ligand of Blc is another tetrapyrrole.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33465067,

title = {Rosetta design with co-evolutionary information retains protein function},

author = {Samuel Schmitz and Moritz Ertelt and Rainer Merkl and Jens Meiler},

doi = {10.1371/journal.pcbi.1008568},

issn = {1553-7358},

year  = {2021},

date = {2021-01-01},

journal = {PLoS Comput Biol},

volume = {17},

number = {1},

pages = {e1008568},

abstract = {Computational protein design has the ambitious goal of crafting novel proteins that address challenges in biology and medicine. To overcome these challenges, the computational protein modeling suite Rosetta has been tailored to address various protein design tasks. Recently, statistical methods have been developed that identify correlated mutations between residues in a multiple sequence alignment of homologous proteins. These subtle inter-dependencies in the occupancy of residue positions throughout evolution are crucial for protein function, but we found that three current Rosetta design approaches fail to recover these co-evolutionary couplings. Thus, we developed the Rosetta method ResCue (residue-coupling enhanced) that leverages co-evolutionary information to favor sequences which recapitulate correlated mutations, as observed in nature. To assess the protocols via recapitulation designs, we compiled a benchmark of ten proteins each represented by two, structurally diverse states. We could demonstrate that ResCue designed sequences with an average sequence recovery rate of 70%, whereas three other protocols reached not more than 50%, on average. Our approach had higher recovery rates also for functionally important residues, which were studied in detail. This improvement has only a minor negative effect on the fitness of the designed sequences as assessed by Rosetta energy. In conclusion, our findings support the idea that informing protocols with co-evolutionary signals helps to design stable and native-like proteins that are compatible with the different conformational states required for a complex function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33351632,

title = {BCL::Conf: Improved Open-Source Knowledge-Based Conformation Sampling Using the Crystallography Open Database},

author = {Jeffrey Mendenhall and Benjamin P Brown and Sandeepkumar Kothiwale and Jens Meiler},

doi = {10.1021/acs.jcim.0c01140},

issn = {1549-960X},

year  = {2021},

date = {2021-01-01},

journal = {J Chem Inf Model},

volume = {61},

number = {1},

pages = {189--201},

abstract = {We previously described BCL::Conf, a knowledge-based conformation sampling algorithm utilizing a small molecule fragment rotamer library derived from the Cambridge Structural Database (CSD, license required), as a component of the BioChemical Library (BCL) cheminformatics toolkit. This paper describes substantial improvements made to the BCL::Conf algorithm and a transition to a rotamer library derived from molecules in the Crystallography Open Database (COD, no license required). We demonstrate the performance of the new BCL::Conf on native conformer recovery in the Platinum dataset of high-quality protein-ligand complexes. This set of 2859 structures has previously been used to assess the performance of over a dozen conformer generation algorithms, including the Conformator, Balloon, RDKit DG, ETKDG, Confab, Frog2, MultiConf-DOCK, CSD conformer generator, ConfGenX-OPSL3 force field, Omega, excalc, iCon, and MOE. These benchmarks suggest that the CSD conformer generator is at the state of the art of reported conformer generators. Our results indicate that the improved BCL::Conf significantly outperforms the CSD conformer generation algorithm at binding conformer recovery across a range of ensemble sizes and with similarly fast rates of conformer generation. BCL::Conf is now distributed with the COD-derived rotamer library and is free for academic use. The BCL can be downloaded at http://meilerlab.org/bclcommons for Windows, Linux, or Apple operating systems. BCL::Conf can now also be accessed via webserver at http://meilerlab.org/bclconf.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33373213,

title = {Efficient Sampling of Protein Loop Regions Using Conformational Hashing Complemented with Random Coordinate Descent},

author = {Diego Del Alamo and Axel W Fischer and Rocco Moretti and Nathan S Alexander and Jeffrey Mendenhall and Nicholas J Hyman and Jens Meiler},

doi = {10.1021/acs.jctc.0c00836},

issn = {1549-9626},

year  = {2021},

date = {2021-01-01},

journal = {J Chem Theory Comput},

volume = {17},

number = {1},

pages = {560--570},

abstract = { construction of loop regions is an important problem in computational structural biology. Compared to regions with well-defined secondary structure, loops tend to exhibit significant conformational heterogeneity. As a result, their structures are often ambiguous when determined using experimental data obtained by crystallography, cryo-EM, or NMR. Although structurally diverse models could provide a more relevant representation of proteins in their native states, obtaining large numbers of biophysically realistic and physiologically relevant loop conformations is a resource-consuming task. To address this need, we developed a novel loop construction algorithm, Hash/RCD, that combines knowledge-based conformational hashing with random coordinate descent (RCD). This hybrid approach achieved a closure rate of 100% on a benchmark set of 195 loops in 29 proteins that range from 3 to 31 residues. More importantly, the use of templates allows Hash/RCD to maintain the accuracy of state-of-the-art coordinate descent methods while reducing sampling time from over 400 to 141 ms. These results highlight how the integration of coordinate descent with knowledge-based sampling overcomes barriers inherent to either approach in isolation. This method may facilitate the identification of native-like loop conformations using experimental data or full-atom scoring functions by allowing rapid sampling of large numbers of loops. In this manuscript, we investigate and discuss the advantages, bottlenecks, and limitations of combining conformational hashing with RCD. By providing a detailed technical description of the Hash/RCD algorithm, we hope to facilitate its implementation by other researchers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32780485,

title = {Hydroxamic Acids Immobilized on Resins (HAIRs): Synthesis of Dual-Targeting HDAC Inhibitors and HDAC Degraders (PROTACs)},

author = {Laura Sinatra and Jan J Bandolik and Martin Roatsch and Melf Sönnichsen and Clara T Schoeder and Alexandra Hamacher and Andrea Schöler and Arndt Borkhardt and Jens Meiler and Sanil Bhatia and Matthias U Kassack and Finn K Hansen},

doi = {10.1002/anie.202006725},

issn = {1521-3773},

year  = {2020},

date = {2020-12-01},

journal = {Angew Chem Int Ed Engl},

volume = {59},

number = {50},

pages = {22494--22499},

abstract = {Inhibition of more than one cancer-related pathway by multi-target agents is an emerging approach in modern anticancer drug discovery. Here, based on the well-established synergy between histone deacetylase inhibitors (HDACi) and alkylating agents, we present the discovery of a series of alkylating HDACi using a pharmacophore-linking strategy. For the parallel synthesis of the target compounds, we developed an efficient solid-phase-supported protocol using hydroxamic acids immobilized on resins (HAIRs) as stable and versatile building blocks for the preparation of functionalized HDACi. The most promising compound, 3 n, was significantly more active in apoptosis induction, activation of caspase 3/7, and formation of DNA damage (γ-H2AX) than the sum of the activities of either active principle alone. Furthermore, to demonstrate the utility of our preloaded resins, the HAIR approach was successfully extended to the synthesis of a proof-of-concept proteolysis-targeting chimera (PROTAC), which efficiently degrades histone deacetylases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33015868,

title = {Predicting susceptibility to SARS-CoV-2 infection based on structural differences in ACE2 across species},

author = {Matthew R Alexander and Clara T Schoeder and Jacquelyn A Brown and Charles D Smart and Chris Moth and John P Wikswo and John A Capra and Jens Meiler and Wenbiao Chen and Meena S Madhur},

doi = {10.1096/fj.202001808R},

issn = {1530-6860},

year  = {2020},

date = {2020-12-01},

journal = {FASEB J},

volume = {34},

number = {12},

pages = {15946--15960},

abstract = {Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the global pandemic of coronavirus disease-2019 (COVID-19). SARS-CoV-2 is a zoonotic disease, but little is known about variations in species susceptibility that could identify potential reservoir species, animal models, and the risk to pets, wildlife, and livestock. Certain species, such as domestic cats and tigers, are susceptible to SARS-CoV-2 infection, while other species such as mice and chickens are not. Most animal species, including those in close contact with humans, have unknown susceptibility. Hence, methods to predict the infection risk of animal species are urgently needed. SARS-CoV-2 spike protein binding to angiotensin-converting enzyme 2 (ACE2) is critical for viral cell entry and infection. Here we integrate species differences in susceptibility with multiple in-depth structural analyses to identify key ACE2 amino acid positions including 30, 83, 90, 322, and 354 that distinguish susceptible from resistant species. Using differences in these residues across species, we developed a susceptibility score that predicts an elevated risk of SARS-CoV-2 infection for multiple species including horses and camels. We also demonstrate that SARS-CoV-2 is nearly optimal for binding ACE2 of humans compared to other animals, which may underlie the highly contagious transmissibility of this virus among humans. Taken together, our findings define potential ACE2 and SARS-CoV-2 residues for therapeutic targeting and identification of animal species on which to focus research and protection measures for environmental and public health.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33229516,

title = {Discovery of Marburg virus neutralizing antibodies from virus-naïve human antibody repertoires using large-scale structural predictions},

author = {Nina G Bozhanova and Amandeep K Sangha and Alexander M Sevy and Pavlo Gilchuk and Kai Huang and Rachel S Nargi and Joseph X Reidy and Andrew Trivette and Robert H Carnahan and Alexander Bukreyev and James E Crowe and Jens Meiler},

doi = {10.1073/pnas.1922654117},

issn = {1091-6490},

year  = {2020},

date = {2020-12-01},

journal = {Proc Natl Acad Sci U S A},

volume = {117},

number = {49},

pages = {31142--31148},

abstract = {Marburg virus (MARV) disease is lethal, with fatality rates up to 90%. Neutralizing antibodies (Abs) are promising drug candidates to prevent or treat the disease. Current efforts are focused in part on vaccine development to induce such MARV-neutralizing Abs. We analyzed the antibody repertoire from healthy unexposed and previously MARV-infected individuals to assess if naïve repertoires contain suitable precursor antibodies that could become neutralizing with a limited set of somatic mutations. We computationally searched the human Ab variable gene repertoire for predicted structural homologs of the neutralizing Ab MR78 that is specific to the receptor binding site (RBS) of MARV glycoprotein (GP). Eight Ab heavy-chain complementarity determining region 3 (HCDR3) loops from MARV-naïve individuals and one from a previously MARV-infected individual were selected for testing as HCDR3 loop chimeras on the MR78 Ab framework. Three of these chimerized antibodies bound to MARV GP. We then tested a full-length native Ab heavy chain encoding the same 17-residue-long HCDR3 loop that bound to the MARV GP the best among the chimeric Abs tested. Despite only 57% amino acid sequence identity, the Ab from a MARV-naïve donor recognized MARV GP and possessed neutralizing activity against the virus. Crystallization of both chimeric and full-length native heavy chain-containing Abs provided structural insights into the mechanism of binding for these types of Abs. Our work suggests that the MARV GP RBS is a promising candidate for epitope-focused vaccine design to induce neutralizing Abs against MARV.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33184362,

title = {Characterization of the ExoU activation mechanism using EPR and integrative modeling},

author = {Maxx H Tessmer and Samuel A DeCero and Diego Del Alamo and Molly O Riegert and Jens Meiler and Dara W Frank and Jimmy B Feix},

doi = {10.1038/s41598-020-76023-3},

issn = {2045-2322},

year  = {2020},

date = {2020-11-01},

journal = {Sci Rep},

volume = {10},

number = {1},

pages = {19700},

abstract = {ExoU, a type III secreted phospholipase effector of Pseudomonas aeruginosa, serves as a prototype to model large, dynamic, membrane-associated proteins. ExoU is synergistically activated by interactions with membrane lipids and ubiquitin. To dissect the activation mechanism, structural homology was used to identify an unstructured loop of approximately 20 residues in the ExoU amino acid sequence. Mutational analyses indicate the importance of specific loop amino acid residues in mediating catalytic activity. Engineered disulfide cross-links show that loop movement is required for activation. Site directed spin labeling EPR and DEER (double electron-electron resonance) studies of apo and holo states demonstrate local conformational changes at specific sites within the loop and a conformational shift of the loop during activation. These data are consistent with the formation of a substrate-binding pocket providing access to the catalytic site. DEER distance distributions were used as constraints in RosettaDEER to construct ensemble models of the loop in both apo and holo states, significantly extending the range for modeling a conformationally dynamic loop.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33095155,

title = {Allosteric mechanism for KCNE1 modulation of KCNQ1 potassium channel activation},

author = {Georg Kuenze and Carlos G Vanoye and Reshma R Desai and Sneha Adusumilli and Kathryn R Brewer and Hope Woods and Eli F McDonald and Charles R Sanders and Alfred L George and Jens Meiler},

doi = {10.7554/eLife.57680},

issn = {2050-084X},

year  = {2020},

date = {2020-10-01},

journal = {Elife},

volume = {9},

abstract = {The function of the voltage-gated KCNQ1 potassium channel is regulated by co-assembly with KCNE auxiliary subunits. KCNQ1-KCNE1 channels generate the slow delayed rectifier current, I, which contributes to the repolarization phase of the cardiac action potential. A three amino acid motif (F57-T58-L59, FTL) in KCNE1 is essential for slow activation of KCNQ1-KCNE1 channels. However, how this motif interacts with KCNQ1 to control its function is unknown. Combining computational modeling with electrophysiological studies, we developed structural models of the KCNQ1-KCNE1 complex that suggest how KCNE1 controls KCNQ1 activation. The FTL motif binds at a cleft between the voltage-sensing and pore domains and appears to affect the channel gate by an allosteric mechanism. Comparison with the KCNQ1-KCNE3 channel structure suggests a common transmembrane-binding mode for different KCNEs and illuminates how specific differences in the interaction of their triplet motifs determine the profound differences in KCNQ1 functional modulation by KCNE1 versus KCNE3.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32783953,

title = {Identification of Structurally Related Antibodies in Antibody Sequence Databases Using Rosetta-Derived Position-Specific Scoring},

author = {Jessica A Finn and Jinhui Dong and Alexander M Sevy and Erica Parrish and Iuliia Gilchuk and Rachel Nargi and Morgan Scarlett-Jones and Walter Reichard and Robin Bombardi and Thomas G Voss and Jens Meiler and James E Crowe},

doi = {10.1016/j.str.2020.07.012},

issn = {1878-4186},

year  = {2020},

date = {2020-10-01},

journal = {Structure},

volume = {28},

number = {10},

pages = {1124--1130.e5},

abstract = {The amount of antibody (Ab) variable gene sequence information is expanding rapidly, but our ability to predict the function of Abs from sequence alone is limited. Here, we describe a sequence-to-function prediction method that couples structural data for a single Ab/antigen (Ag) complex with repertoire data. We used a position-specific structure-scoring matrix (P3SM) incorporating structure-prediction scores from Rosetta to identify Ab variable loops that have predicted structural similarity to the influenza virus-specific human Ab CH65. The P3SM approach identified new members of this Ab class. Recombinant Ab expression, crystallography, and virus inhibition assays showed that the HCDR3 loops of the newly identified Abs possessed similar structure and antiviral activity as the comparator CH65. This approach enables discovery of new human Abs with desired structure and function using cDNA repertoires that are obtained readily with current amplicon sequencing techniques.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33010233,

title = {A Computational Analysis of the Factors Governing the Dynamics of α7 nAChR and Its Homologs},

author = {Alican Gulsevin and Jens Meiler and Nicole A Horenstein},

doi = {10.1016/j.bpj.2020.09.006},

issn = {1542-0086},

year  = {2020},

date = {2020-10-01},

journal = {Biophys J},

volume = {119},

number = {8},

pages = {1656--1669},

abstract = {The α7 nicotinic acetylcholine receptor is a homopentameric ion channel from the Cys-loop receptor superfamily targeted for psychiatric indications and inflammatory pain. Molecular dynamics studies of the receptor have focused on residue mobility and global conformational changes to address receptor function. However, a comparative analysis of α7 with its homologs that cannot trigger channel opening has not been made so far. To identify the residues involved in α7 activation, we ran triplicate 500-ns molecular dynamics simulations with an α7 extracellular domain homology model and two acetylcholine-binding protein homologs. We tested the effect of ligand binding and amino acid sequence on the structure and dynamics of the three proteins. We found that mobile regions identified based on root mean-square deviation and root mean-square fluctuation values are not always consistent among the individual α7 extracellular domain simulations. Comparison of the replica-average properties of the three proteins based on dynamic cross-correlation maps showed that ligand binding affects the coupling between the C-loop and the Cys-loop, vestibular loop, and β1-β2 loops. In addition, the main-immunogenic-region-like domain of α7 went through correlated motions with multiple domains of the receptor. These correlated motions were absent or diminished in α7 homologs, suggesting a unique role in α7 activation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32610044,

title = {Computationally Designed Cyclic Peptides Derived from an Antibody Loop Increase Breadth of Binding for Influenza Variants},

author = {Alexander M Sevy and Iuliia M Gilchuk and Benjamin P Brown and Nina G Bozhanova and Rachel Nargi and Mattie Jensen and Jens Meiler and James E Crowe},

doi = {10.1016/j.str.2020.04.005},

issn = {1878-4186},

year  = {2020},

date = {2020-10-01},

journal = {Structure},

volume = {28},

number = {10},

pages = {1114--1123.e4},

abstract = {The influenza hemagglutinin (HA) glycoprotein is the target of many broadly neutralizing antibodies. However, influenza viruses can rapidly escape antibody recognition by mutation of hypervariable regions of HA that overlap with the binding epitope. We hypothesized that by designing peptides to mimic antibody loops, we could enhance breadth of binding to HA antigenic variants by reducing contact with hypervariable residues on HA that mediate escape. We designed cyclic peptides that mimic the heavy-chain complementarity-determining region 3 (CDRH3) of anti-influenza broadly neutralizing antibody C05 and show that these peptides bound to HA molecules with <100 nM affinity, comparable with that of the full-length parental C05 IgG. In addition, these peptides exhibited increased breadth of recognition to influenza H4 and H7 subtypes by eliminating clashes between the hypervariable antigenic regions and the antibody CDRH1 loop. This approach can be used to generate antibody-derived peptides against a wide variety of targets.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33112852,

title = {Improving homology modeling from low-sequence identity templates in Rosetta: A case study in GPCRs},

author = {Brian Joseph Bender and Brennica Marlow and Jens Meiler},

doi = {10.1371/journal.pcbi.1007597},

issn = {1553-7358},

year  = {2020},

date = {2020-10-01},

journal = {PLoS Comput Biol},

volume = {16},

number = {10},

pages = {e1007597},

abstract = {As sequencing methodologies continue to advance, the availability of protein sequences far outpaces the ability of structure determination. Homology modeling is used to bridge this gap but relies on high-identity templates for accurate model building. G-protein coupled receptors (GPCRs) represent a significant target class for pharmaceutical therapies in which homology modeling could fill the knowledge gap for structure-based drug design. To date, only about 17% of druggable GPCRs have had their structures characterized at atomic resolution. However, modeling of the remaining 83% is hindered by the low sequence identity between receptors. Here we test key inputs in the model building process using GPCRs as a focus to improve the pipeline in two critical ways: Firstly, we use a blended sequence- and structure-based alignment that accounts for structure conservation in loop regions. Secondly, by merging multiple template structures into one comparative model, the best possible template for every region of a target can be used expanding the conformational space sampled in a meaningful way. This optimization allows for accurate modeling of receptors using templates as low as 20% sequence identity, which accounts for nearly the entire druggable space of GPCRs. A model database of all non-odorant GPCRs is made available at www.rosettagpcr.org. Additionally, all protocols are made available with insights into modifications that may improve accuracy at new targets.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32947868,

title = {An Investigation of Three-Finger Toxin-nAChR Interactions through Rosetta Protein Docking},

author = {Alican Gulsevin and Jens Meiler},

doi = {10.3390/toxins12090598},

issn = {2072-6651},

year  = {2020},

date = {2020-09-01},

journal = {Toxins (Basel)},

volume = {12},

number = {9},

abstract = {Three-finger toxins (3FTX) are a group of peptides that affect multiple receptor types. One group of proteins affected by 3FTX are nicotinic acetylcholine receptors (nAChR). Structural information on how neurotoxins interact with nAChR is limited and is confined to a small group of neurotoxins. Therefore, in silico methods are valuable in understanding the interactions between 3FTX and different nAChR subtypes, but there are no established protocols to model 3FTX-nAChR interactions. We followed a homology modeling and protein docking protocol to address this issue and tested its success on three different systems. First, neurotoxin peptides co-crystallized with acetylcholine binding protein (AChBP) were re-docked to assess whether Rosetta protein-protein docking can reproduce the native poses. Second, experimental data on peptide binding to AChBP was used to test whether the docking protocol can qualitatively distinguish AChBP-binders from non-binders. Finally, we docked eight peptides with known α7 and muscle-type nAChR binding properties to test whether the protocol can explain the differential activities of the peptides at the two receptor subtypes. Overall, the docking protocol predicted the qualitative and some specific aspects of 3FTX binding to nAChR with reasonable success and shed light on unknown aspects of 3FTX binding to different receptor subtypes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32809793,

title = {Structure-Based Rational Design of Two Enhanced Bacterial Lipocalin  Tags for Protein-PAINT Super-resolution Microscopy},

author = {Liya Muslinkina and Alexey S Gavrikov and Nina G Bozhanova and Alexander S Mishin and Mikhail S Baranov and Jens Meiler and Nadya V Pletneva and Vladimir Z Pletnev and Sergei Pletnev},

doi = {10.1021/acschembio.0c00440},

issn = {1554-8937},

year  = {2020},

date = {2020-09-01},

journal = {ACS Chem Biol},

volume = {15},

number = {9},

pages = {2456--2465},

abstract = {Super-resolution fluorescent imaging in living cells remains technically challenging, largely due to the photodecomposition of fluorescent tags. The recently suggested protein-PAINT is the only super-resolution technique available for prolonged imaging of proteins in living cells. It is realized with complexes of fluorogen-activating proteins, expressed as fusions, and solvatochromic synthetic dyes. Once photobleached, the dye in the complex is replaced with a fresh fluorogen available in the sample. With suitable kinetics, this replacement creates fluorescence blinking required for attaining super-resolution and overcomes photobleaching associated with the loss of an irreplaceable fluorophore. Here we report on the rational design of two protein-PAINT tags based on the 1.58 Å crystal structure of the DiB1:M739 complex, an improved green-emitting DiB3/F74V:M739 and a new orange-emitting DiB3/F53L:M739. They outperform previously reported DiB-based tags to become best in class biomarkers for protein-PAINT. The new tags advance protein-PAINT from the proof-of-concept to a reliable tool suitable for prolonged super-resolution imaging of intracellular proteins in fixed and living cells and two-color PAINT-like nanoscopy with a single fluorogen.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32668443,

title = {Potently neutralizing and protective human antibodies against SARS-CoV-2},

author = {Seth J Zost and Pavlo Gilchuk and James Brett Case and Elad Binshtein and Rita E Chen and Joseph P Nkolola and Alexandra Schäfer and Joseph X Reidy and Andrew Trivette and Rachel S Nargi and Rachel E Sutton and Naveenchandra Suryadevara and David R Martinez and Lauren E Williamson and Elaine C Chen and Taylor Jones and Samuel Day and Luke Myers and Ahmed O Hassan and Natasha M Kafai and Emma S Winkler and Julie M Fox and Swathi Shrihari and Benjamin K Mueller and Jens Meiler and Abishek Chandrashekar and Noe B Mercado and James J Steinhardt and Kuishu Ren and Yueh-Ming Loo and Nicole L Kallewaard and Broc T McCune and Shamus P Keeler and Michael J Holtzman and Dan H Barouch and Lisa E Gralinski and Ralph S Baric and Larissa B Thackray and Michael S Diamond and Robert H Carnahan and James E Crowe},

doi = {10.1038/s41586-020-2548-6},

issn = {1476-4687},

year  = {2020},

date = {2020-08-01},

journal = {Nature},

volume = {584},

number = {7821},

pages = {443--449},

abstract = {The ongoing pandemic of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major threat to global health and the medical countermeasures available so far are limited. Moreover, we currently lack a thorough understanding of the mechanisms of humoral immunity to SARS-CoV-2. Here we analyse a large panel of human monoclonal antibodies that target the spike (S) glycoprotein, and identify several that exhibit potent neutralizing activity and fully block the receptor-binding domain of the S protein (S) from interacting with human angiotensin-converting enzyme 2 (ACE2). Using competition-binding, structural and functional studies, we show that the monoclonal antibodies can be clustered into classes that recognize distinct epitopes on the S, as well as distinct conformational states of the S trimer. Two potently neutralizing monoclonal antibodies, COV2-2196 and COV2-2130, which recognize non-overlapping sites, bound simultaneously to the S protein and neutralized wild-type SARS-CoV-2 virus in a synergistic manner. In two mouse models of SARS-CoV-2 infection, passive transfer of COV2-2196, COV2-2130 or a combination of both of these antibodies protected mice from weight loss and reduced the viral burden and levels of inflammation in the lungs. In addition, passive transfer of either of two of the most potent ACE2-blocking monoclonal antibodies (COV2-2196 or COV2-2381) as monotherapy protected rhesus macaques from SARS-CoV-2 infection. These results identify protective epitopes on the S and provide a structure-based framework for rational vaccine design and the selection of robust immunotherapeutic agents.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32803091,

title = {Phenotypic Profiling in Subjects Heterozygous for 1 of 2 Rare Variants in the Hypophosphatasia Gene ()},

author = {Daniel R Tilden and Jonathan H Sheehan and John H Newman and Jens Meiler and John A Capra and Andrea Ramirez and Jill Simmons and Kathryn Dahir},

doi = {10.1210/jendso/bvaa084},

issn = {2472-1972},

year  = {2020},

date = {2020-08-01},

journal = {J Endocr Soc},

volume = {4},

number = {8},

pages = {bvaa084},

abstract = {CONTEXT: Hypophosphatasia (HPP) is a syndrome marked by low serum alkaline phosphatase (AlkP) activity as well as musculoskeletal and/or dental disease. While the majority of subjects with HPP carry a pathogenic variant in the  gene or its regulatory regions, individual pathogenic variants are often not tightly correlated with clinical symptomatology. We sought to better understand the genotype/phenotype correlation in HPP by examining the clinical and biochemical data of 37 subjects with 2 rare variants in .nnMETHODS: Through BioVU, a DNA biobank that pairs individuals' genetic information with their de-identified medical records, we identified subjects with 2 rare variants with distinct reported clinical phenotypes (p.D294A and p.T273M). We then performed a manual review of these subjects' de-identified medical records along with computational modeling of protein structure to construct a genetic, biochemical and clinical phenotype for each subject and variant.nnRESULTS: Twenty subjects with the p.D294A variant and 17 with the p.T273M variant had sufficient data for analysis. Among subjects in our cohort with the p.D294A variant, 6 (30.0%) had both clinical bone disease and serum AlkP activity below 40 IU/L while 4 subjects (23.5%) with the p.T273M variant met the same criteria despite the distinct clinical phenotypes of these variants.nnCONCLUSIONS: Given the loose genotype/phenotype correlation in HPP seen in our cohort, clinical context is crucial for the interpretation of genetic test results to guide clinical care in this population. Otherwise, over- or under-diagnosis may occur, resulting in misidentification of those who may benefit from additional screening and perhaps pharmacologic intervention.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32483333,

title = {Macromolecular modeling and design in Rosetta: recent methods and frameworks},

author = {Julia Koehler Leman and Brian D Weitzner and Steven M Lewis and Jared Adolf-Bryfogle and Nawsad Alam and Rebecca F Alford and Melanie Aprahamian and David Baker and Kyle A Barlow and Patrick Barth and Benjamin Basanta and Brian J Bender and Kristin Blacklock and Jaume Bonet and Scott E Boyken and Phil Bradley and Chris Bystroff and Patrick Conway and Seth Cooper and Bruno E Correia and Brian Coventry and Rhiju Das and René M De Jong and Frank DiMaio and Lorna Dsilva and Roland Dunbrack and Alexander S Ford and Brandon Frenz and Darwin Y Fu and Caleb Geniesse and Lukasz Goldschmidt and Ragul Gowthaman and Jeffrey J Gray and Dominik Gront and Sharon Guffy and Scott Horowitz and Po-Ssu Huang and Thomas Huber and Tim M Jacobs and Jeliazko R Jeliazkov and David K Johnson and Kalli Kappel and John Karanicolas and Hamed Khakzad and Karen R Khar and Sagar D Khare and Firas Khatib and Alisa Khramushin and Indigo C King and Robert Kleffner and Brian Koepnick and Tanja Kortemme and Georg Kuenze and Brian Kuhlman and Daisuke Kuroda and Jason W Labonte and Jason K Lai and Gideon Lapidoth and Andrew Leaver-Fay and Steffen Lindert and Thomas Linsky and Nir London and Joseph H Lubin and Sergey Lyskov and Jack Maguire and Lars Malmström and Enrique Marcos and Orly Marcu and Nicholas A Marze and Jens Meiler and Rocco Moretti and Vikram Khipple Mulligan and Santrupti Nerli and Christoffer Norn and Shane Ó'Conchúir and Noah Ollikainen and Sergey Ovchinnikov and Michael S Pacella and Xingjie Pan and Hahnbeom Park and Ryan E Pavlovicz and Manasi Pethe and Brian G Pierce and Kala Bharath Pilla and Barak Raveh and P Douglas Renfrew and Shourya S Roy Burman and Aliza Rubenstein and Marion F Sauer and Andreas Scheck and William Schief and Ora Schueler-Furman and Yuval Sedan and Alexander M Sevy and Nikolaos G Sgourakis and Lei Shi and Justin B Siegel and Daniel-Adriano Silva and Shannon Smith and Yifan Song and Amelie Stein and Maria Szegedy and Frank D Teets and Summer B Thyme and Ray Yu-Ruei Wang and Andrew Watkins and Lior Zimmerman and Richard Bonneau},

doi = {10.1038/s41592-020-0848-2},

issn = {1548-7105},

year  = {2020},

date = {2020-07-01},

journal = {Nat Methods},

volume = {17},

number = {7},

pages = {665--680},

abstract = {The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at http://www.rosettacommons.org.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32632329,

title = {DiB-splits: nature-guided design of a novel fluorescent labeling split system},

author = {Nina G Bozhanova and Alexey S Gavrikov and Alexander S Mishin and Jens Meiler},

doi = {10.1038/s41598-020-67095-2},

issn = {2045-2322},

year  = {2020},

date = {2020-07-01},

journal = {Sci Rep},

volume = {10},

number = {1},

pages = {11049},

abstract = {Fluorogen-activating proteins (FAPs) are innovative fluorescent probes combining advantages of genetically-encoded proteins such as green fluorescent protein and externally added fluorogens that allow for highly tunable and on demand fluorescent signaling. Previously, a panel of green- and red-emitting FAPs has been created from bacterial lipocalin Blc (named DiBs). Here we present a rational design as well as functional and structural characterization of the first self-assembling FAP split system, DiB-splits. This new system decreases the size of the FAP label to ~8-12 kDa while preserving DiBs' unique properties: strong increase in fluorescence intensity of the chromophore upon binding, binding affinities to the chromophore in nanomolar to low micromolar range, and high photostability of the protein-ligand complex. These properties allow for use of DiB-splits for wide-field, confocal, and super-resolution fluorescence microscopy. DiB-splits also represent an attractive starting point for further design of a protein-protein interaction detection system as well as novel FAP-based sensors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31924303,

title = {Comparative modeling and docking of chemokine-receptor interactions with Rosetta},

author = {Michael J Wedemeyer and Benjamin K Mueller and Brian J Bender and Jens Meiler and Brian F Volkman},

doi = {10.1016/j.bbrc.2019.12.076},

issn = {1090-2104},

year  = {2020},

date = {2020-07-01},

journal = {Biochem Biophys Res Commun},

volume = {528},

number = {2},

pages = {389--397},

abstract = {Chemokine receptors are a subset of G protein-coupled receptors defined by the distinct property of binding small protein ligands in the chemokine family. Chemokine receptors recognize their ligands by a mechanism that is distinct from other class A GPCRs that bind peptides or small molecules. For this reason, structural information on other ligand-GPCR interactions are only indirectly relevant to understanding the chemokine receptor interface. Additionally, the experimentally determined structures of chemokine-GPCR complexes represent less than 3% of the known interactions of this complex, multi-ligand/multi-receptor network. To enable predictive modeling of the remaining 97% of interactions, a general in silico protocol was designed to utilize existing chemokine receptor crystal structures, co-crystal structures, and NMR ensembles of chemokines bound to receptor fragments. This protocol was benchmarked on the ability to predict each of the three published co-crystal structures, while being blinded to the target structure. Averaging ensembles selected from the top-ranking models reproduced up to 84% of the intermolecular contacts found in the crystal structure, with the lowest Cα-RMSD of the complex at 3.3 Å. The chemokine receptor N-terminus, unresolved in crystal structures, was included in the modeling and recapitulates contacts with known sulfotyrosine binding pockets seen in structures derived from experimental NMR data. This benchmarking experiment suggests that realistic homology models of chemokine-GPCR complexes can be generated by leveraging current structural data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32433991,

title = {Integrated Structural Modeling of Full-Length LRH-1 Reveals Inter-domain Interactions Contribute to Receptor Structure and Function},

author = {Corey D Seacrist and Georg Kuenze and Reece M Hoffmann and Brandon E Moeller and John E Burke and Jens Meiler and Raymond D Blind},

doi = {10.1016/j.str.2020.04.020},

issn = {1878-4186},

year  = {2020},

date = {2020-07-01},

journal = {Structure},

volume = {28},

number = {7},

pages = {830--846.e9},

abstract = {Liver receptor homolog-1 (LRH-1; NR5A2) is a nuclear receptor that regulates a diverse array of biological processes. In contrast to dimeric nuclear receptors, LRH-1 is an obligate monomer and contains a subtype-specific helix at the C terminus of the DNA-binding domain (DBD), termed FTZ-F1. Although detailed structural information is available for individual domains of LRH-1, it is unknown how these domains exist in the intact nuclear receptor. Here, we developed an integrated structural model of human full-length LRH-1 using a combination of HDX-MS, XL-MS, Rosetta computational docking, and SAXS. The model predicts the DBD FTZ-F1 helix directly interacts with ligand binding domain helix 2. We confirmed several other predicted inter-domain interactions via structural and functional analyses. Comparison between the LRH-1/Dax-1 co-crystal structure and the integrated model predicted and confirmed Dax-1 co-repressor to modulate LRH-1 inter-domain dynamics. Together, these data support individual LRH-1 domains interacting to influence receptor structure and function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32677886,

title = {PyIR: a scalable wrapper for processing billions of immunoglobulin and T cell receptor sequences using IgBLAST},

author = {Cinque Soto and Jessica A Finn and Jordan R Willis and Samuel B Day and Robert S Sinkovits and Taylor Jones and Samuel Schmitz and Jens Meiler and Andre Branchizio and James E Crowe},

doi = {10.1186/s12859-020-03649-5},

issn = {1471-2105},

year  = {2020},

date = {2020-07-01},

journal = {BMC Bioinformatics},

volume = {21},

number = {1},

pages = {314},

abstract = {BACKGROUND: Recent advances in DNA sequencing technologies have enabled significant leaps in capacity to generate large volumes of DNA sequence data, which has spurred a rapid growth in the use of bioinformatics as a means of interrogating antibody variable gene repertoires. Common tools used for annotation of antibody sequences are often limited in functionality, modularity and usability.nnRESULTS: We have developed PyIR, a Python wrapper and library for IgBLAST, which offers a minimal setup CLI and API, FASTQ support, file chunking for large sequence files, JSON and Python dictionary output, and built-in sequence filtering.nnCONCLUSIONS: PyIR offers improved processing speed over multithreaded IgBLAST (version 1.14) when spawning more than 16 processes on a single computer system. Its customizable filtering and data encapsulation allow it to be adapted to a wide range of computing environments. The API allows for IgBLAST to be used in customized bioinformatics workflows.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32482872,

title = {MHC-II alleles shape the CDR3 repertoires of conventional and regulatory naïve CD4 T cells},

author = {Nadezhda N Logunova and Valeriia V Kriukova and Pavel V Shelyakin and Evgeny S Egorov and Alina Pereverzeva and Nina G Bozhanova and Mikhail Shugay and Dmitrii S Shcherbinin and Mikhail V Pogorelyy and Ekaterina M Merzlyak and Vasiliy N Zubov and Jens Meiler and Dmitriy M Chudakov and Alexander S Apt and Olga V Britanova},

doi = {10.1073/pnas.2003170117},

issn = {1091-6490},

year  = {2020},

date = {2020-06-01},

journal = {Proc Natl Acad Sci U S A},

volume = {117},

number = {24},

pages = {13659--13669},

abstract = {T cell maturation and activation depend upon T cell receptor (TCR) interactions with a wide variety of antigenic peptides displayed in a given major histocompatibility complex (MHC) context. Complementarity-determining region 3 (CDR3) is the most variable part of the TCRα and -β chains, which govern interactions with peptide-MHC complexes. However, it remains unclear how the CDR3 landscape is shaped by individual MHC context during thymic selection of naïve T cells. We established two mouse strains carrying distinct allelic variants of  and analyzed thymic and peripheral production and TCR repertoires of naïve conventional CD4 T (T) and naïve regulatory CD4 T (T) cells. Compared with tuberculosis-resistant C57BL/6 (H2-A) mice, the tuberculosis-susceptible H2-A mice had fewer CD4 T cells of both subsets in the thymus. In the periphery, this deficiency was only apparent for T and was compensated for by peripheral reconstitution for T We show that H2-A favors selection of a narrower and more convergent repertoire with more hydrophobic and strongly interacting amino acid residues in the middle of CDR3α and CDR3β, suggesting more stringent selection against a narrower peptide-MHC-II context. H2-A and H2-A mice have prominent reciprocal differences in CDR3α and CDR3β features, probably reflecting distinct modes of TCR fitting to MHC-II variants. These data reveal the mechanics and extent of how MHC-II shapes the naïve CD4 T cell CDR3 landscape, which essentially defines adaptive response to infections and self-antigens.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32365137,

title = {Better together: Elements of successful scientific software development in a distributed collaborative community},

author = {Julia Koehler Leman and Brian D Weitzner and P Douglas Renfrew and Steven M Lewis and Rocco Moretti and Andrew M Watkins and Vikram Khipple Mulligan and Sergey Lyskov and Jared Adolf-Bryfogle and Jason W Labonte and Justyna Krys and  and Christopher Bystroff and William Schief and Dominik Gront and Ora Schueler-Furman and David Baker and Philip Bradley and Roland Dunbrack and Tanja Kortemme and Andrew Leaver-Fay and Charlie E M Strauss and Jens Meiler and Brian Kuhlman and Jeffrey J Gray and Richard Bonneau},

doi = {10.1371/journal.pcbi.1007507},

issn = {1553-7358},

year  = {2020},

date = {2020-05-01},

journal = {PLoS Comput Biol},

volume = {16},

number = {5},

pages = {e1007507},

abstract = {Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}