Publications

@article{pmid37404061,

title = {Acquired secondary HER2 mutations enhance HER2/MAPK signaling and promote resistance to HER2 kinase inhibition in breast cancer},

author = {Arnaldo Marin and Abdullah Al Mamun and Hima Patel and Hiroaki Akamatsu and Dan Ye and Dhivya R Sudhan and Lisa Eli and Katherine Marcelain and Benjamin P Brown and Jens Meiler and Carlos L Arteaga and Ariella B Hanker},

doi = {10.1158/0008-5472.CAN-22-3617},

issn = {1538-7445},

year  = {2023},

date = {2023-07-01},

journal = {Cancer Res},

abstract = {HER2 mutations drive the growth of a subset of breast cancers and are targeted with HER2 tyrosine kinase inhibitors (TKIs) such as neratinib. However, acquired resistance is common and limits the durability of clinical responses. Most HER2-mutant breast cancers progressing on neratinib-based therapy acquire secondary mutations in HER2. It is unknown whether these secondary HER2 mutations, other than the HER2T798I gatekeeper mutation, are causal to neratinib resistance. Herein, we show that secondary acquired HER2T862A and HER2L755S mutations promote resistance to HER2 TKIs via enhanced HER2 activation and impaired neratinib binding. While cells expressing each acquired HER2 mutation alone were sensitive to neratinib, expression of acquired double mutations enhanced HER2 signaling and reduced neratinib sensitivity. Computational structural modeling suggested that secondary HER2 mutations stabilize the HER2 active state and reduce neratinib binding affinity. Cells expressing double HER2 mutations exhibited resistance to most HER2 TKIs but retained sensitivity to mobocertinib and poziotinib. Double-mutant cells showed enhanced MEK/ERK signaling, which was blocked by combined inhibition of HER2 and MEK. Together, these findings reveal the driver function of secondary HER2 mutations in resistance to HER2 inhibition and provide a potential treatment strategy to overcome acquired resistance to HER2 TKIs in HER2-mutant breast cancer.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37339079,

title = {Structure-Activity Relationship Study of the High-Affinity Neuropeptide Y Receptor Positive Allosteric Modulator VU0506013},

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

doi = {10.1021/acs.jmedchem.3c00383},

issn = {1520-4804},

year  = {2023},

date = {2023-07-01},

journal = {J Med Chem},

volume = {66},

number = {13},

pages = {8745--8766},

abstract = {Positive allosteric modulators targeting the Y receptor (YR), a G protein-coupled receptor (GPCR) involved in the regulation of satiety, offer great potential in anti-obesity research. In this study, we selected 603 compounds by using quantitative structure-activity relationship (QSAR) models and tested them in high-throughput screening (HTS). Here, the novel positive allosteric modulator (PAM) VU0506013 was identified, which exhibits nanomolar affinity and pronounced selectivity toward the YR in engineered cell lines and mouse descending colon mucosa natively expressing the YR. Based on this lead structure, we conducted a systematic SAR study in two regions of the scaffold and presented a series of 27 analogues with modifications in the - and -terminal heterocycles of the molecule to obtain insight into functionally relevant positions. By mutagenesis and computational docking, we present a potential binding mode of VU0506013 in the transmembrane core of the YR. VU0506013 presents a promising scaffold for developing  tools to move toward anti-obesity drug research focused on the YR.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37467526,

title = {Interplay of thermodynamics and evolution within the ternary ligand-GPCR-G protein complex},

author = {Hannes Junker and Jens Meiler and Clara T Schoeder},

doi = {10.1016/j.sbi.2023.102656},

issn = {1879-033X},

year  = {2023},

date = {2023-07-01},

journal = {Curr Opin Struct Biol},

volume = {82},

pages = {102656},

abstract = {Recent studies on G protein-coupled receptors (GPCRs) dynamics report that GPCRs adopt a wide range of conformations that coexist in equilibrium, with the apo state of a GPCR having a high entropy. The formation of a ligand-GPCR-transducer complex comes with a reduction of conformational space and therefore with an entropic cost. We hypothesize that the availability of binding partners, their binding affinity and the rigidity of the respective binding sites are reflected in a distinct degree of sequence conservation to balance the energetic cost of intra- and extracellular binding events. Here, we outline the current findings in delineating the conformational space and include sequential conservation of many-to-many ligand-receptor systems to discuss the entropic cost that comes with GPCR signal transduction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37016190,

title = {Sparse pseudocontact shift NMR data obtained from a non-canonical amino acid-linked lanthanide tag improves integral membrane protein structure prediction},

author = {Kaitlyn V Ledwitch and Georg Künze and Jacob R McKinney and Elleansar Okwei and Katherine Larochelle and Lisa Pankewitz and Soumya Ganguly and Heather L Darling and Irene Coin and Jens Meiler},

doi = {10.1007/s10858-023-00412-9},

issn = {1573-5001},

year  = {2023},

date = {2023-06-01},

journal = {J Biomol NMR},

volume = {77},

number = {3},

pages = {69--82},

abstract = {A single experimental method alone often fails to provide the resolution, accuracy, and coverage needed to model integral membrane proteins (IMPs). Integrating computation with experimental data is a powerful approach to supplement missing structural information with atomic detail. We combine RosettaNMR with experimentally-derived paramagnetic NMR restraints to guide membrane protein structure prediction. We demonstrate this approach using the disulfide bond formation protein B (DsbB), an α-helical IMP. Here, we attached a cyclen-based paramagnetic lanthanide tag to an engineered non-canonical amino acid (ncAA) using a copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry reaction. Using this tagging strategy, we collected 203 backbone H pseudocontact shifts (PCSs) for three different labeling sites and used these as input to guide de novo membrane protein structure prediction protocols in Rosetta. We find that this sparse PCS dataset combined with 44 long-range NOEs as restraints in our calculations improves structure prediction of DsbB by enhancements in model accuracy, sampling, and scoring. The inclusion of this PCS dataset improved the Cα-RMSD transmembrane segment values of the best-scoring and best-RMSD models from 9.57 Å and 3.06 Å (no NMR data) to 5.73 Å and 2.18 Å, respectively.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37253358,

title = {General trends in the effects of VX-661 and VX-445 on the plasma membrane expression of clinical CFTR variants},

author = {Andrew G McKee and Eli F McDonald and Wesley D Penn and Charles P Kuntz and Karen Noguera and Laura M Chamness and Francis J Roushar and Jens Meiler and Kathryn E Oliver and Lars Plate and Jonathan P Schlebach},

doi = {10.1016/j.chembiol.2023.05.001},

issn = {2451-9448},

year  = {2023},

date = {2023-06-01},

journal = {Cell Chem Biol},

volume = {30},

number = {6},

pages = {632--642.e5},

abstract = {Cystic fibrosis (CF) is caused by mutations that compromise the expression and/or function of the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel. Most people with CF harbor a common misfolded variant (ΔF508) that can be partially rescued by therapeutic "correctors" that restore its expression. Nevertheless, many other CF variants are insensitive to correctors. Using deep mutational scanning, we quantitatively compare the effects of two correctors on the plasma membrane expression of 129 CF variants. Though structural calculations suggest corrector binding provides similar stabilization to most variants, it's those with intermediate expression and mutations near corrector binding pockets that exhibit the greatest response. Deviations in sensitivity appear to depend on the degree of variant destabilization and the timing of misassembly. Combining correctors appears to rescue more variants by doubling the binding energy and stabilizing distinct cotranslational folding transitions. These results provide an overview of rare CF variant expression and establish new tools for precision pharmacology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36352786,

title = {Template-free prediction of a new monotopic membrane protein fold and assembly by AlphaFold2},

author = {Alican Gulsevin and Bing Han and Jason C Porta and Hassane S Mchaourab and Jens Meiler and Anne K Kenworthy},

doi = {10.1016/j.bpj.2022.11.011},

issn = {1542-0086},

year  = {2023},

date = {2023-06-01},

journal = {Biophys J},

volume = {122},

number = {11},

pages = {2041--2052},

abstract = {AlphaFold2 (AF2) has revolutionized the field of protein structural prediction. Here, we test its ability to predict the tertiary and quaternary structure of a previously undescribed scaffold with new folds and unusual architecture, the monotopic membrane protein caveolin-1 (CAV1). CAV1 assembles into a disc-shaped oligomer composed of 11 symmetrically arranged protomers, each assuming an identical new fold, and contains the largest parallel β-barrel known to exist in nature. Remarkably, AF2 predicts both the fold of the protomers and the interfaces between them. It also assembles between seven and 15 copies of CAV1 into disc-shaped complexes. However, the predicted multimers are energetically strained, especially the parallel β-barrel. These findings highlight the ability of AF2 to correctly predict new protein folds and oligomeric assemblies at a granular level while missing some elements of higher-order complexes, thus positing a new direction for the continued development of deep-learning protein structure prediction approaches.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37119820,

title = {Computational modeling and prediction of deletion mutants},

author = {Hope Woods and Dominic L Schiano and Jonathan I Aguirre and Kaitlyn V Ledwitch and Eli F McDonald and Markus Voehler and Jens Meiler and Clara T Schoeder},

doi = {10.1016/j.str.2023.04.005},

issn = {1878-4186},

year  = {2023},

date = {2023-06-01},

journal = {Structure},

volume = {31},

number = {6},

pages = {713--723.e3},

abstract = {In-frame deletion mutations can result in disease. The impact of these mutations on protein structure and subsequent functional changes remain understudied, partially due to the lack of comprehensive datasets including a structural readout. In addition, the recent breakthrough in structure prediction through deep learning demands an update of computational deletion mutation prediction. In this study, we deleted individually every residue of a small α-helical sterile alpha motif domain and investigated the structural and thermodynamic changes using 2D NMR spectroscopy and differential scanning fluorimetry. Then, we tested computational protocols to model and classify observed deletion mutants. We show a method using AlphaFold2 followed by RosettaRelax performs the best overall. In addition, a metric containing pLDDT values and Rosetta ΔΔG is most reliable in classifying tolerated deletion mutations. We further test this method on other datasets and show they hold for proteins known to harbor disease-causing deletion mutations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36870682,

title = {Structural analysis of the P132L disease mutation in caveolin-1 reveals its role in the assembly of oligomeric complexes},

author = {Bing Han and Alican Gulsevin and Sarah Connolly and Ting Wang and Brigitte Meyer and Jason Porta and Ajit Tiwari and Angie Deng and Louise Chang and Yelena Peskova and Hassane S Mchaourab and Erkan Karakas and Melanie D Ohi and Jens Meiler and Anne K Kenworthy},

doi = {10.1016/j.jbc.2023.104574},

issn = {1083-351X},

year  = {2023},

date = {2023-04-01},

journal = {J Biol Chem},

volume = {299},

number = {4},

pages = {104574},

abstract = {Caveolin-1 (CAV1) is a membrane-sculpting protein that oligomerizes to generate flask-shaped invaginations of the plasma membrane known as caveolae. Mutations in CAV1 have been linked to multiple diseases in humans. Such mutations often interfere with oligomerization and the intracellular trafficking processes required for successful caveolae assembly, but the molecular mechanisms underlying these defects have not been structurally explained. Here, we investigate how a disease-associated mutation in one of the most highly conserved residues in CAV1, P132L, affects CAV1 structure and oligomerization. We show that P132 is positioned at a major site of protomer-protomer interactions within the CAV1 complex, providing a structural explanation for why the mutant protein fails to homo-oligomerize correctly. Using a combination of computational, structural, biochemical, and cell biological approaches, we find that despite its homo-oligomerization defects P132L is capable of forming mixed hetero-oligomeric complexes with WT CAV1 and that these complexes can be incorporated into caveolae. These findings provide insights into the fundamental mechanisms that control the formation of homo- and hetero-oligomers of caveolins that are essential for caveolae biogenesis, as well as how these processes are disrupted in human disease.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37175495,

title = {Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection},

author = {Fabian Liessmann and Georg Künze and Jens Meiler},

doi = {10.3390/ijms24097788},

issn = {1422-0067},

year  = {2023},

date = {2023-04-01},

journal = {Int J Mol Sci},

volume = {24},

number = {9},

abstract = {G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of C-C-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36971354,

title = {Antigenic mapping and functional characterization of human New World hantavirus neutralizing antibodies},

author = {Taylor B Engdahl and Elad Binshtein and Rebecca L Brocato and Natalia A Kuzmina and Lucia M Principe and Steven A Kwilas and Robert K Kim and Nathaniel S Chapman and Monique S Porter and Pablo Guardado-Calvo and Félix A Rey and Laura S Handal and Summer M Diaz and Irene A Zagol-Ikapitte and Minh H Tran and W Hayes McDonald and Jens Meiler and Joseph X Reidy and Andrew Trivette and Alexander Bukreyev and Jay W Hooper and James E Crowe},

doi = {10.7554/eLife.81743},

issn = {2050-084X},

year  = {2023},

date = {2023-03-01},

journal = {Elife},

volume = {12},

abstract = {Hantaviruses are high-priority emerging pathogens carried by rodents and transmitted to humans by aerosolized excreta or, in rare cases, person-to-person contact. While infections in humans are relatively rare, mortality rates range from 1 to 40% depending on the hantavirus species. There are currently no FDA-approved vaccines or therapeutics for hantaviruses, and the only treatment for infection is supportive care for respiratory or kidney failure. Additionally, the human humoral immune response to hantavirus infection is incompletely understood, especially the location of major antigenic sites on the viral glycoproteins and conserved neutralizing epitopes. Here, we report antigenic mapping and functional characterization for four neutralizing hantavirus antibodies. The broadly neutralizing antibody SNV-53 targets an interface between Gn/Gc, neutralizes through fusion inhibition and cross-protects against the Old World hantavirus species Hantaan virus when administered pre- or post-exposure. Another broad antibody, SNV-24, also neutralizes through fusion inhibition but targets domain I of Gc and demonstrates weak neutralizing activity to authentic hantaviruses. ANDV-specific, neutralizing antibodies (ANDV-5 and ANDV-34) neutralize through attachment blocking and protect against hantavirus cardiopulmonary syndrome (HCPS) in animals but target two different antigenic faces on the head domain of Gn. Determining the antigenic sites for neutralizing antibodies will contribute to further therapeutic development for hantavirus-related diseases and inform the design of new broadly protective hantavirus vaccines.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36972273,

title = {Docking cholesterol to integral membrane proteins with Rosetta},

author = {Brennica Marlow and Georg Kuenze and Jens Meiler and Julia Koehler Leman},

doi = {10.1371/journal.pcbi.1010947},

issn = {1553-7358},

year  = {2023},

date = {2023-03-01},

journal = {PLoS Comput Biol},

volume = {19},

number = {3},

pages = {e1010947},

abstract = {Lipid molecules such as cholesterol interact with the surface of integral membrane proteins (IMP) in a mode different from drug-like molecules in a protein binding pocket. These differences are due to the lipid molecule's shape, the membrane's hydrophobic environment, and the lipid's orientation in the membrane. We can use the recent increase in experimental structures in complex with cholesterol to understand protein-cholesterol interactions. We developed the RosettaCholesterol protocol consisting of (1) a prediction phase using an energy grid to sample and score native-like binding poses and (2) a specificity filter to calculate the likelihood that a cholesterol interaction site may be specific. We used a multi-pronged benchmark (self-dock, flip-dock, cross-dock, and global-dock) of protein-cholesterol complexes to validate our method. RosettaCholesterol improved sampling and scoring of native poses over the standard RosettaLigand baseline method in 91% of cases and performs better regardless of benchmark complexity. On the β2AR, our method found one likely-specific site, which is described in the literature. The RosettaCholesterol protocol quantifies cholesterol binding site specificity. Our approach provides a starting point for high-throughput modeling and prediction of cholesterol binding sites for further experimental validation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36626571,

title = {Rosetta's Predictive Ability for Low-Affinity Ligand Binding in Fragment-Based Drug Discovery},

author = {Elleansar Okwei and Shannon T Smith and Brian J Bender and Brittany Allison and Soumya Ganguly and Alexander Geanes and Xuan Zhang and Kaitlyn Ledwitch and Jens Meiler},

doi = {10.1021/acs.biochem.2c00649},

issn = {1520-4995},

year  = {2023},

date = {2023-02-01},

journal = {Biochemistry},

volume = {62},

number = {3},

pages = {700--709},

abstract = {Fragment-based drug discovery begins with the identification of small molecules with a molecular weight of usually less than 250 Da which weakly bind to the protein of interest. This technique is challenging for computational docking methods as binding is determined by only a few specific interactions. Inaccuracies in the energy function or slight deviations in the docking pose can lead to the prediction of incorrect binding or difficulties in ranking fragments in  screening. Here, we test RosettaLigand by docking a series of fragments to a cysteine-depleted variant of the TIM-barrel protein, HisF (UniProtKB Q9X0C6). We compare the computational results with experimental NMR spectroscopy screens. NMR spectroscopy gives details on binding affinities of individual ligands, which allows assessment of the ligand-ranking ability using RosettaLigand and also provides feedback on the location of the binding pocket, which serves as a reliable test of RosettaLigand's ability to identify plausible binding poses. From a library screen of 3456 fragments, we identified a set of 31 ligands with intrinsic affinities to HisF with dissociation constants as low as 400 μM. The same library of fragments was blindly screened in silico. RosettaLigand was able to rank binders before non-binders with an area under the curve of the receiver operating characteristics of 0.74. The docking poses observed for binders agreed with the binding pocket identified by NMR chemical shift perturbations for all fragments. Taken together, these results provide a baseline performance of RosettaLigand in a fragment-based drug discovery setting.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36876042,

title = {Biasing AlphaFold2 to predict GPCRs and kinases with user-defined functional or structural properties},

author = {Davide Sala and Peter W Hildebrand and Jens Meiler},

doi = {10.3389/fmolb.2023.1121962},

issn = {2296-889X},

year  = {2023},

date = {2023-01-01},

journal = {Front Mol Biosci},

volume = {10},

pages = {1121962},

abstract = {Determining the three-dimensional structure of proteins in their native functional states has been a longstanding challenge in structural biology. While integrative structural biology has been the most effective way to get a high-accuracy structure of different conformations and mechanistic insights for larger proteins, advances in deep machine-learning algorithms have paved the way to fully computational predictions. In this field, AlphaFold2 (AF2) pioneered  high-accuracy single-chain modeling. Since then, different customizations have expanded the number of conformational states accessible through AF2. Here, we further expanded AF2 with the aim of enriching an ensemble of models with user-defined functional or structural features. We tackled two common protein families for drug discovery, G-protein-coupled receptors (GPCRs) and kinases. Our approach automatically identifies the best templates satisfying the specified features and combines those with genetic information. We also introduced the possibility of shuffling the selected templates to expand the space of solutions. In our benchmark, models showed the intended bias and great accuracy. Our protocol can thus be exploited for modeling user-defined conformational states in an automatic fashion.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37033915,

title = {Glycan masking in vaccine design: Targets, immunogens and applications},

author = {Cristina E Martina and James E Crowe and Jens Meiler},

doi = {10.3389/fimmu.2023.1126034},

issn = {1664-3224},

year  = {2023},

date = {2023-01-01},

journal = {Front Immunol},

volume = {14},

pages = {1126034},

abstract = {Glycan masking is a novel technique in reverse vaccinology in which sugar chains (glycans) are added on the surface of immunogen candidates to hide regions of low interest and thus focus the immune system on highly therapeutic epitopes. This shielding strategy is inspired by viruses such as influenza and HIV, which are able to escape the immune system by incorporating additional glycosylation and preventing the binding of therapeutic antibodies. Interestingly, the glycan masking technique is mainly used in vaccine design to fight the same viruses that naturally use glycans to evade the immune system. In this review we report the major successes obtained with the glycan masking technique in epitope-focused vaccine design. We focus on the choice of the target antigen, the strategy for immunogen design and the relevance of the carrier vector to induce a strong immune response. Moreover, we will elucidate the different applications that can be accomplished with glycan masking, such as shifting the immune response from hyper-variable epitopes to more conserved ones, focusing the response on known therapeutic epitopes, broadening the response to different viral strains/sub-types and altering the antigen immunogenicity to elicit higher or lower immune response, as desired.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36525975,

title = {Benchmarking AlphaFold2 on peptide structure prediction},

author = {Eli Fritz McDonald and Taylor Jones and Lars Plate and Jens Meiler and Alican Gulsevin},

doi = {10.1016/j.str.2022.11.012},

issn = {1878-4186},

year  = {2023},

date = {2023-01-01},

journal = {Structure},

volume = {31},

number = {1},

pages = {111--119.e2},

abstract = {Recent advancements in computational tools have allowed protein structure prediction with high accuracy. Computational prediction methods have been used for modeling many soluble and membrane proteins, but the performance of these methods in modeling peptide structures has not yet been systematically investigated. We benchmarked the accuracy of AlphaFold2 in predicting 588 peptide structures between 10 and 40 amino acids using experimentally determined NMR structures as reference. Our results showed AlphaFold2 predicts α-helical, β-hairpin, and disulfide-rich peptides with high accuracy. AlphaFold2 performed at least as well if not better than alternative methods developed specifically for peptide structure prediction. AlphaFold2 showed several shortcomings in predicting Φ/Ψ angles, disulfide bond patterns, and the lowest RMSD structures failed to correlate with lowest pLDDT ranked structures. In summary, computation can be a powerful tool to predict peptide structures, but additional steps may be necessary to analyze and validate the results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36477260,

title = {Computational epitope mapping of class I fusion proteins using low complexity supervised learning methods},

author = {Marion F S Fischer and James E Crowe and Jens Meiler},

doi = {10.1371/journal.pcbi.1010230},

issn = {1553-7358},

year  = {2022},

date = {2022-12-01},

journal = {PLoS Comput Biol},

volume = {18},

number = {12},

pages = {e1010230},

abstract = {Antibody epitope mapping of viral proteins plays a vital role in understanding immune system mechanisms of protection. In the case of class I viral fusion proteins, recent advances in cryo-electron microscopy and protein stabilization techniques have highlighted the importance of cryptic or 'alternative' conformations that expose epitopes targeted by potent neutralizing antibodies. Thorough epitope mapping of such metastable conformations is difficult but is critical for understanding sites of vulnerability in class I fusion proteins that occur as transient conformational states during viral attachment and fusion. We introduce a novel method Accelerated class I fusion protein Epitope Mapping (AxIEM) that accounts for fusion protein flexibility to improve out-of-sample prediction of discontinuous antibody epitopes. Harnessing data from previous experimental epitope mapping efforts of several class I fusion proteins, we demonstrate that accuracy of epitope prediction depends on residue environment and allows for the prediction of conformation-dependent antibody target residues. We also show that AxIEM can identify common epitopes and provide structural insights for the development and rational design of vaccines.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36035247,

title = {Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by  KCNC2 variants},

author = {Souhrid Mukherjee and Thomas A Cassini and Ningning Hu and Tao Yang and Bian Li and Wangzhen Shen and Christopher W Moth and David C Rinker and Jonathan H Sheehan and Joy D Cogan and  and John H Newman and Rizwan Hamid and Robert L Macdonald and Dan M Roden and Jens Meiler and Georg Kuenze and John A Phillips and John A Capra},

doi = {10.1016/j.xhgg.2022.100131},

issn = {2666-2477},

year  = {2022},

date = {2022-10-01},

journal = {HGG Adv},

volume = {3},

number = {4},

pages = {100131},

abstract = {Whole-exome sequencing (WES) in the clinic has identified several rare monogenic developmental and epileptic encephalopathies (DEE) caused by ion channel variants. However, WES often fails to provide actionable insight for rare diseases, such as DEEs, due to the challenges of interpreting variants of unknown significance (VUS). Here, we describe a "personalized structural biology" (PSB) approach that leverages recent innovations in the analysis of protein 3D structures to address this challenge. We illustrate this approach in an Undiagnosed Diseases Network (UDN) individual with DEE symptoms and a  VUS in  (p.V469L), the Kv3.2 voltage-gated potassium channel. A nearby  variant (p.V471L) was recently suggested to cause DEE-like phenotypes. Computational structural modeling suggests that both affect protein function. However, despite their proximity, the p.V469L variant is likely to sterically block the channel pore, while the p.V471L variant is likely to stabilize the open state. Biochemical and electrophysiological analyses demonstrate heterogeneous loss-of-function and gain-of-function effects, as well as differential response to 4-aminopyridine treatment. Molecular dynamics simulations illustrate that the pore of the p.V469L variant is more constricted, increasing the energetic barrier for K permeation, whereas the p.V471L variant stabilizes the open conformation. Our results implicate variants in  as causative for DEE and guide the interpretation of a UDN individual. They further delineate the molecular basis for the heterogeneous clinical phenotypes resulting from two proximal pathogenic variants. This demonstrates how the PSB approach can provide an analytical framework for individualized hypothesis-driven interpretation of protein-coding VUS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35973423,

title = {Integrative model of the FSH receptor reveals the structural role of the flexible hinge region},

author = {Marcus Nagel and Rocco Moretti and Ralf Paschke and Martin von Bergen and Jens Meiler and Stefan Kalkhof},

doi = {10.1016/j.str.2022.07.007},

issn = {1878-4186},

year  = {2022},

date = {2022-10-01},

journal = {Structure},

volume = {30},

number = {10},

pages = {1424--1431.e3},

abstract = {The follicle-stimulating hormone receptor (FSHR) belongs to the glycoprotein hormone receptors, a subfamily of G-protein-coupled receptors (GPCRs). FSHR is involved in reproductive processes such as gonadal development and maturation. Structurally, the extensive extracellular domain, which contains the hormone-binding site and is linked to the transmembrane domain by the hinge region (HR), is characteristic for these receptors. How this HR is involved in hormone binding and signal transduction is still an open question. We combined in vitro and in situ chemical crosslinking, disulfide pattern analysis, and mutation data with molecular modeling to generate experimentally driven full-length models. These models provide insights into the interface, important side-chain interactions, and activation mechanism. The interface indicates a strong involvement of the connecting loop. A major rearrangement of the HR seems implausible due to the tight arrangement and fixation by disulfide bonds. The models are expected to allow for testable hypotheses about signal transduction and drug development for GPHRs.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35843285,

title = {Principles of Alternating Access in LeuT-fold Transporters: Commonalities and Divergences},

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

doi = {10.1016/j.jmb.2022.167746},

issn = {1089-8638},

year  = {2022},

date = {2022-10-01},

journal = {J Mol Biol},

volume = {434},

number = {19},

pages = {167746},

abstract = {Found in all domains of life, transporters belonging to the LeuT-fold class mediate the import and exchange of hydrophilic and charged compounds such as amino acids, metals, and sugar molecules. Nearly two decades of investigations on the eponymous bacterial transporter LeuT have yielded a library of high-resolution snapshots of its conformational cycle linked by solution-state experimental data obtained from multiple techniques. In parallel, its topology has been observed in symporters and antiporters characterized by a spectrum of substrate specificities and coupled to gradients of distinct ions. Here we review and compare mechanistic models of transport for LeuT, its well-studied homologs, as well as functionally distant members of the fold, emphasizing the commonalities and divergences in alternating access and the corresponding energy landscapes. Our integrated summary illustrates how fold conservation, a hallmark of the LeuT fold, coincides with divergent choreographies of alternating access that nevertheless capitalize on recurrent structural motifs. In addition, it highlights the knowledge gap that hinders the leveraging of the current body of research into detailed mechanisms of transport for this important class of membrane proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35315300,

title = {Confirmation of association of  p.Ser591Phe mutation with variant lattice corneal dystrophy},

author = {Charlene H Choo and Doug D Chung and Kaitlyn V Ledwitch and Alexa Kassels and Jens Meiler and Anthony J Aldave},

doi = {10.1080/13816810.2022.2050766},

issn = {1744-5094},

year  = {2022},

date = {2022-08-01},

journal = {Ophthalmic Genet},

volume = {43},

number = {4},

pages = {530--533},

abstract = {PURPOSE: To provide the initial confirmation of the c.1772C>T (p.Ser591Phe) mutation in the transforming growth factor--induced ( gene as being associated with variant lattice corneal dystrophy (LCD).nnMETHODS: Ophthalmologic examination of the proband was performed with slit lamp biomicroscopy. Saliva was collected as a source of DNA for screening all 17 exons of , after which three family members were selectively screened for variants in exon 13. Rosetta-based structure prediction was used to calculate changes in TGFBI protein (TGFBIp) stability secondary to the c.1772C>T (p.Ser591Phe) missense mutation.nnRESULTS: Slit lamp examination of the 38-year-old proband revealed a clear cornea right eye and unilateral, discrete, and branching lattice lines in the anterior and mid-stroma of the central cornea left eye. Screening of  in the proband revealed a heterozygous missense mutation in exon 13 (c.1772C>T (p.Ser591Phe)) that was also identified in her affected mother but not in her brother or maternal grandmother. Calculated energy change in Rosetta (ΔΔG) for the TGFBIp variant p.Ser591Phe was 23.5, indicating a thermodynamic destabilization resulting from energetic frustration.nnCONCLUSIONS: The p.Ser591Phe mutation in  is associated with an unilateral variant of LCD. Rosetta-predicted stability changes indicate that the p.Ser591Phe variant is destabilizing, which is consistent with other observations for LCD-causing mutations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35969794,

title = {Integrated AlphaFold2 and DEER investigation of the conformational dynamics of a pH-dependent APC antiporter},

author = {Diego Del Alamo and Lillian DeSousa and Rahul M Nair and Suhaila Rahman and Jens Meiler and Hassane S Mchaourab},

doi = {10.1073/pnas.2206129119},

issn = {1091-6490},

year  = {2022},

date = {2022-08-01},

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

volume = {119},

number = {34},

pages = {e2206129119},

abstract = {The Amino Acid-Polyamine-Organocation (APC) transporter GadC contributes to the survival of pathogenic bacteria under extreme acid stress by exchanging extracellular glutamate for intracellular γ-aminobutyric acid (GABA). Its structure, determined in an inward-facing conformation at alkaline pH, consists of the canonical LeuT-fold with a conserved five-helix inverted repeat, thereby resembling functionally divergent transporters such as the serotonin transporter SERT and the glucose-sodium symporter SGLT1. However, despite this structural similarity, it is unclear if the conformational dynamics of antiporters such as GadC follow the blueprint of these or other LeuT-fold transporters. Here, we used double electron-electron resonance (DEER) spectroscopy to monitor the conformational dynamics of GadC in lipid bilayers in response to acidification and substrate binding. To guide experimental design and facilitate the interpretation of the DEER data, we generated an ensemble of structural models in multiple conformations using a recently introduced modification of AlphaFold2 . Our experimental results reveal acid-induced conformational changes that dislodge the Cterminus from the permeation pathway coupled with rearrangement of helices that enables isomerization between inward- and outward-facing states. The substrate glutamate, but not GABA, modulates the dynamics of an extracellular thin gate without shifting the equilibrium between inward- and outward-facing conformations. In addition to introducing an integrated methodology for probing transporter conformational dynamics, the congruence of the DEER data with patterns of structural rearrangements deduced from ensembles of AlphaFold2 models illuminates the conformational cycle of GadC underpinning transport and exposes yet another example of the divergence between the dynamics of different families in the LeuT-fold.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35850308,

title = {Molecular basis for variations in the sensitivity of pathogenic rhodopsin variants to 9-cis-retinal},

author = {Francis J Roushar and Andrew G McKee and Charles P Kuntz and Joseph T Ortega and Wesley D Penn and Hope Woods and Laura M Chamness and Victoria Most and Jens Meiler and Beata Jastrzebska and Jonathan P Schlebach},

doi = {10.1016/j.jbc.2022.102266},

issn = {1083-351X},

year  = {2022},

date = {2022-08-01},

journal = {J Biol Chem},

volume = {298},

number = {8},

pages = {102266},

abstract = {Over 100 mutations in the rhodopsin gene have been linked to a spectrum of retinopathies that include retinitis pigmentosa and congenital stationary night blindness. Though most of these variants exhibit a loss of function, the molecular defects caused by these underlying mutations vary considerably. In this work, we utilize deep mutational scanning to quantitatively compare the plasma membrane expression of 123 known pathogenic rhodopsin variants in the presence and absence of the stabilizing cofactor 9-cis-retinal. We identify 69 retinopathy variants, including 20 previously uncharacterized variants, that exhibit diminished plasma membrane expression in HEK293T cells. Of these apparent class II variants, 67 exhibit a measurable increase in expression in the presence of 9-cis-retinal. However, the magnitude of the response to this molecule varies considerably across this spectrum of mutations. Evaluation of the observed shifts relative to thermodynamic estimates for the coupling between binding and folding suggests underlying differences in stability constrains the magnitude of their response to retinal. Nevertheless, estimates from computational modeling suggest that many of the least sensitive variants also directly compromise binding. Finally, we evaluate the functional properties of three previous uncharacterized, retinal-sensitive variants (ΔN73, S131P, and R135G) and show that two of these retain residual function in vitro. Together, our results provide a comprehensive experimental characterization of the proteostatic properties of retinopathy variants and their response to retinal.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35982797,

title = {Dual pancreatic adrenergic and dopaminergic signaling as a therapeutic target of bromocriptine},

author = {Despoina Aslanoglou and Suzanne Bertera and Laura Friggeri and Marta Sánchez-Soto and Jeongkyung Lee and Xiangning Xue and Ryan W Logan and J Robert Lane and Vijay K Yechoor and Peter J McCormick and Jens Meiler and R Benjamin Free and David R Sibley and Rita Bottino and Zachary Freyberg},

doi = {10.1016/j.isci.2022.104771},

issn = {2589-0042},

year  = {2022},

date = {2022-08-01},

journal = {iScience},

volume = {25},

number = {8},

pages = {104771},

abstract = {Bromocriptine is approved as a diabetes therapy, yet its therapeutic mechanisms remain unclear. Though bromocriptine's actions have been mainly attributed to the stimulation of brain dopamine D receptors (D2R), bromocriptine also targets the pancreas. Here, we employ bromocriptine as a tool to elucidate the roles of catecholamine signaling in regulating pancreatic hormone secretion. In β-cells, bromocriptine acts on D2R and α-adrenergic receptor (α-AR) to reduce glucose-stimulated insulin secretion (GSIS). Moreover, in α-cells, bromocriptine acts via D2R to reduce glucagon secretion. α-AR activation by bromocriptine recruits an ensemble of G proteins with no β-arrestin2 recruitment. In contrast, D2R recruits G proteins and β-arrestin2 upon bromocriptine stimulation, demonstrating receptor-specific signaling. Docking studies reveal distinct bromocriptine binding to α-AR versus D2R, providing a structural basis for bromocriptine's dual actions on β-cell α-AR and D2R. Together, joint dopaminergic and adrenergic receptor actions on α-cell and β-cell hormone release provide a new therapeutic mechanism to improve dysglycemia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35597243,

title = {Modeling of protein conformational changes with Rosetta guided by limited experimental data},

author = {Davide Sala and Diego Del Alamo and Hassane S Mchaourab and Jens Meiler},

doi = {10.1016/j.str.2022.04.013},

issn = {1878-4186},

year  = {2022},

date = {2022-08-01},

journal = {Structure},

volume = {30},

number = {8},

pages = {1157--1168.e3},

abstract = {Conformational changes are an essential component of functional cycles of many proteins, but their characterization often requires an integrative structural biology approach. Here, we introduce and benchmark ConfChangeMover (CCM), a new method built into the widely used macromolecular modeling suite Rosetta that is tailored to model conformational changes in proteins using sparse experimental data. CCM can rotate and translate secondary structural elements and modify their backbone dihedral angles in regions of interest. We benchmarked CCM on soluble and membrane proteins with simulated Cα-Cα distance restraints and sparse experimental double electron-electron resonance (DEER) restraints, respectively. In both benchmarks, CCM outperformed state-of-the-art Rosetta methods, showing that it can model a diverse array of conformational changes. In addition, the Rosetta framework allows a wide variety of experimental data to be integrated with CCM, thus extending its capability beyond DEER restraints. This method will contribute to the biophysical characterization of protein dynamics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35687855,

title = {An Active Learning Framework Improves Tumor Variant Interpretation},

author = {Alexandra M Blee and Bian Li and Turner Pecen and Jens Meiler and Zachary D Nagel and John A Capra and Walter J Chazin},

doi = {10.1158/0008-5472.CAN-21-3798},

issn = {1538-7445},

year  = {2022},

date = {2022-08-01},

journal = {Cancer Res},

volume = {82},

number = {15},

pages = {2704--2715},

abstract = {A novel machine learning approach predicts the impact of tumor mutations on cellular phenotypes, overcomes limited training data, minimizes costly functional validation, and advances efforts to implement cancer precision medicine.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35867821,

title = {Allele-specific activation, enzyme kinetics, and inhibitor sensitivities of EGFR exon 19 deletion mutations in lung cancer},

author = {Benjamin P Brown and Yun-Kai Zhang and Soyeon Kim and Patrick Finneran and Yingjun Yan and Zhenfang Du and Jiyoon Kim and Abigail Leigh Hartzler and Michele L LeNoue-Newton and Adam W Smith and Jens Meiler and Christine M Lovly},

doi = {10.1073/pnas.2206588119},

issn = {1091-6490},

year  = {2022},

date = {2022-07-01},

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

volume = {119},

number = {30},

pages = {e2206588119},

abstract = {Oncogenic mutations within the epidermal growth factor receptor (EGFR) are found in 15 to 30% of all non-small-cell lung carcinomas. The term exon 19 deletion (ex19del) is collectively used to refer to more than 20 distinct genomic alterations within exon 19 that comprise the most common EGFR mutation subtype in lung cancer. Despite this heterogeneity, clinical treatment decisions are made irrespective of which EGFR ex19del variant is present within the tumor, and there is a paucity of information regarding how individual ex19del variants influence protein structure and function. Herein, we identified allele-specific functional differences among ex19del variants attributable to recurring sequence and structure motifs. We built all-atom structural models of 60 ex19del variants identified in patients and combined molecular dynamics simulations with biochemical and biophysical experiments to analyze three ex19del mutations (E746_A750, E746_S752 > V, and L747_A750 > P). We demonstrate that sequence variation in ex19del alters oncogenic cell growth, dimerization propensity, enzyme kinetics, and tyrosine kinase inhibitor (TKI) sensitivity. We show that in contrast to E746_A750 and E746_S752 > V, the L747_A750 > P variant forms highly active ligand-independent dimers. Enzyme kinetic analysis and TKI inhibition experiments suggest that E746_S752 > V and L747_A750 > P display reduced TKI sensitivity due to decreased adenosine 5'-triphosphate . Through these analyses, we propose an expanded framework for interpreting ex19del variants and considerations for therapeutic intervention.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35715957,

title = {Towards generalizable predictions for G protein-coupled receptor variant expression},

author = {Charles P Kuntz and Hope Woods and Andrew G McKee and Nathan B Zelt and Jeffrey L Mendenhall and Jens Meiler and Jonathan P Schlebach},

doi = {10.1016/j.bpj.2022.06.018},

issn = {1542-0086},

year  = {2022},

date = {2022-07-01},

journal = {Biophys J},

volume = {121},

number = {14},

pages = {2712--2720},

abstract = {Missense mutations that compromise the plasma membrane expression (PME) of integral membrane proteins are the root cause of numerous genetic diseases. Differentiation of this class of mutations from those that specifically modify the activity of the folded protein has proven useful for the development and targeting of precision therapeutics. Nevertheless, it remains challenging to predict the effects of mutations on the stability and/ or expression of membrane proteins. In this work, we utilize deep mutational scanning data to train a series of artificial neural networks to predict the PME of transmembrane domain variants of G protein-coupled receptors from structural and/ or evolutionary features. We show that our best-performing network, which we term the PME predictor, can recapitulate mutagenic trends within rhodopsin and can differentiate pathogenic transmembrane domain variants that cause it to misfold from those that compromise its signaling. This network also generates statistically significant predictions for the relative PME of transmembrane domain variants for another class A G protein-coupled receptor (β adrenergic receptor) but not for an unrelated voltage-gated potassium channel (KCNQ1). Notably, our analyses of these networks suggest structural features alone are generally sufficient to recapitulate the observed mutagenic trends. Moreover, our findings imply that networks trained in this manner may be generalizable to proteins that share a common fold. Implications of our findings for the design of mechanistically specific genetic predictors are discussed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35676279,

title = {Computational identification of HCV neutralizing antibodies with a common HCDR3 disulfide bond motif in the antibody repertoires of infected individuals},

author = {Nina G Bozhanova and Andrew I Flyak and Benjamin P Brown and Stormy E Ruiz and Jordan Salas and Semi Rho and Robin G Bombardi and Luke Myers and Cinque Soto and Justin R Bailey and James E Crowe and Pamela J Bjorkman and Jens Meiler},

doi = {10.1038/s41467-022-30865-9},

issn = {2041-1723},

year  = {2022},

date = {2022-06-01},

journal = {Nat Commun},

volume = {13},

number = {1},

pages = {3178},

abstract = {Despite recent success in hepatitis C virus (HCV) treatment using antivirals, an HCV vaccine is still needed to prevent reinfections in treated patients, to avert the emergence of drug-resistant strains, and to provide protection for people with no access to the antiviral therapeutics. The early production of broadly neutralizing antibodies (bNAbs) associates with HCV clearance. Several potent bNAbs bind a conserved HCV glycoprotein E2 epitope using an unusual heavy chain complementarity determining region 3 (HCDR3) containing an intra-loop disulfide bond. Isolation of additional structurally-homologous bNAbs would facilitate the recognition of key determinants of such bNAbs and guide rational vaccine design. Here we report the identification of new antibodies containing an HCDR3 disulfide bond motif using computational screening with the Rosetta software. Using the newly-discovered and already-known members of this antibody family, we review the required HCDR3 amino acid composition and propose determinants for the bent versus straight HCDR3 loop conformation observed in these antibodies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35073610,

title = {Balancing Histone Deacetylase (HDAC) Inhibition and Drug-likeness: Biological and Physicochemical Evaluation of Class I Selective HDAC Inhibitors},

author = {Linda Schäker-Hübner and Reza Haschemi and Thomas Büch and Fabian B Kraft and Birke Brumme and Andrea Schöler and Robert Jenke and Jens Meiler and Achim Aigner and Gerd Bendas and Finn K Hansen},

doi = {10.1002/cmdc.202100755},

issn = {1860-7187},

year  = {2022},

date = {2022-05-01},

journal = {ChemMedChem},

volume = {17},

number = {9},

pages = {e202100755},

abstract = {Herein we report the structure-activity and structure-physicochemical property relationships of a series of class I selective ortho-aminoanilides targeting the "foot-pocket" in HDAC1&2. To balance the structural benefits and the physicochemical disadvantages of these substances, we started with a set of HDACi related to tacedinaline (CI-994) and evaluated their solubility, lipophilicity (log D ) and inhibition of selected HDAC isoforms. Subsequently, we selected the most promising "capless" HDACi and transferred its ZBG to our previously published scaffold featuring a peptoid-based cap group. The resulting hit compound 10 c (LSH-A54) showed favorable physicochemical properties and is a potent, selective HDAC1/2 inhibitor. The following evaluation of its slow binding properties revealed that LSH-A54 binds tightly to HDAC1 in an induced-fit mechanism. The potent HDAC1/2 inhibitory properties were reflected by attenuated cell migration in a modified wound healing assay and reduced cell viability in a clonogenic survival assay in selected breast cancer cell lines.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35290761,

title = {Small integral membrane protein 10 like 1 downregulation enhances differentiation of adipose progenitor cells},

author = {Michèle Nebe and Stephanie Kehr and Samuel Schmitz and Jana Breitfeld and Judith Lorenz and Diana Le Duc and Peter F Stadler and Jens Meiler and Wieland Kiess and Antje Garten and Anna S Kirstein},

doi = {10.1016/j.bbrc.2022.03.014},

issn = {1090-2104},

year  = {2022},

date = {2022-05-01},

journal = {Biochem Biophys Res Commun},

volume = {604},

pages = {57--62},

abstract = {Small integral membrane protein 10 like 1 (SMIM10L1) was identified by RNA sequencing as the most significantly downregulated gene in Phosphatase and Tensin Homologue (PTEN) knockdown adipose progenitor cells (APCs). PTEN is a tumor suppressor that antagonizes the growth promoting Phosphoinositide 3-kinase (PI3K)/AKT/mechanistic Target of Rapamycin (mTOR) cascade. Diseases caused by germline pathogenic variants in PTEN are summarized as PTEN Hamartoma Tumor Syndrome (PHTS). This overgrowth syndrome is associated with lipoma formation, especially in pediatric patients. The mechanisms underlying this adipose tissue dysfunction remain elusive. We observed that SMIM10L1 downregulation in APCs led to an enhanced adipocyte differentiation in two- and three-dimensional cell culture and increased expression of adipogenesis markers. Furthermore, SMIM10L1 knockdown cells showed a decreased expression of PTEN, pointing to a mutual crosstalk between PTEN and SMIM10L1. In line with these observations, SMIM10L1 knockdown cells showed increased activation of PI3K/AKT/mTOR signaling and concomitantly increased expression of the adipogenic transcription factor SREBP1. We computationally predicted an α-helical structure and membrane association of SMIM10L1. These results support a specific role for SMIM10L1 in regulating adipogenesis, potentially by increasing PI3K/AKT/mTOR signaling, which might be conducive to lipoma formation in pediatric patients with PHTS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35584193,

title = {Epitope-focused immunogen design based on the ebolavirus glycoprotein HR2-MPER region},

author = {Clara T Schoeder and Pavlo Gilchuk and Amandeep K Sangha and Kaitlyn V Ledwitch and Delphine C Malherbe and Xuan Zhang and Elad Binshtein and Lauren E Williamson and Cristina E Martina and Jinhui Dong and Erica Armstrong and Rachel Sutton and Rachel Nargi and Jessica Rodriguez and Natalia Kuzmina and Brooke Fiala and Neil P King and Alexander Bukreyev and James E Crowe and Jens Meiler},

doi = {10.1371/journal.ppat.1010518},

issn = {1553-7374},

year  = {2022},

date = {2022-05-01},

journal = {PLoS Pathog},

volume = {18},

number = {5},

pages = {e1010518},

abstract = {The three human pathogenic ebolaviruses: Zaire (EBOV), Bundibugyo (BDBV), and Sudan (SUDV) virus, cause severe disease with high fatality rates. Epitopes of ebolavirus glycoprotein (GP) recognized by antibodies with binding breadth for all three ebolaviruses are of major interest for rational vaccine design. In particular, the heptad repeat 2 -membrane-proximal external region (HR2-MPER) epitope is relatively conserved between EBOV, BDBV, and SUDV GP and targeted by human broadly-neutralizing antibodies. To study whether this epitope can serve as an immunogen for the elicitation of broadly-reactive antibody responses, protein design in Rosetta was employed to transplant the HR2-MPER epitope identified from a co-crystal structure with the known broadly-reactive monoclonal antibody (mAb) BDBV223 onto smaller scaffold proteins. From computational analysis, selected immunogen designs were produced as recombinant proteins and functionally validated, leading to the identification of a sterile alpha motif (SAM) domain displaying the BDBV-HR2-MPER epitope near its C terminus as a promising candidate. The immunogen was fused to one component of a self-assembling, two-component nanoparticle and tested for immunogenicity in rabbits. Robust titers of cross-reactive serum antibodies to BDBV and EBOV GPs and moderate titers to SUDV GP were induced following immunization. To confirm the structural composition of the immunogens, solution NMR studies were conducted and revealed structural flexibility in the C-terminal residues of the epitope. Overall, our study represents the first report on an epitope-focused immunogen design based on the structurally challenging BDBV-HR2-MPER epitope.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35510622,

title = {Heterogeneity of the GFP fitness landscape and data-driven protein design},

author = {Louisa Gonzalez Somermeyer and Aubin Fleiss and Alexander S Mishin and Nina G Bozhanova and Anna A Igolkina and Jens Meiler and Maria-Elisenda Alaball Pujol and Ekaterina V Putintseva and Karen S Sarkisyan and Fyodor A Kondrashov},

doi = {10.7554/eLife.75842},

issn = {2050-084X},

year  = {2022},

date = {2022-05-01},

journal = {Elife},

volume = {11},

abstract = {Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design - instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35544577,

title = {Molecular architecture of the human caveolin-1 complex},

author = {Jason C Porta and Bing Han and Alican Gulsevin and Jeong Min Chung and Yelena Peskova and Sarah Connolly and Hassane S Mchaourab and Jens Meiler and Erkan Karakas and Anne K Kenworthy and Melanie D Ohi},

doi = {10.1126/sciadv.abn7232},

issn = {2375-2548},

year  = {2022},

date = {2022-05-01},

journal = {Sci Adv},

volume = {8},

number = {19},

pages = {eabn7232},

abstract = {Membrane-sculpting proteins shape the morphology of cell membranes and facilitate remodeling in response to physiological and environmental cues. Complexes of the monotopic membrane protein caveolin function as essential curvature-generating components of caveolae, flask-shaped invaginations that sense and respond to plasma membrane tension. However, the structural basis for caveolin's membrane remodeling activity is currently unknown. Here, we show that, using cryo-electron microscopy, the human caveolin-1 complex is composed of 11 protomers organized into a tightly packed disc with a flat membrane-embedded surface. The structural insights suggest a previously unrecognized mechanism for how membrane-sculpting proteins interact with membranes and reveal how key regions of caveolin-1, including its scaffolding, oligomerization, and intramembrane domains, contribute to its function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35034430,

title = {Mapping the Binding Sites of UDP and Prostaglandin E2 Glyceryl Ester in the Nucleotide Receptor P2Y},

author = {Anne Zimmermann and Oanh Vu and Antje Brüser and Gregory Sliwoski and Lawrence J Marnett and Jens Meiler and Torsten Schöneberg},

doi = {10.1002/cmdc.202100683},

issn = {1860-7187},

year  = {2022},

date = {2022-04-01},

journal = {ChemMedChem},

volume = {17},

number = {7},

pages = {e202100683},

abstract = {Cyclooxygenase-2 catalyzes the biosynthesis of prostaglandins from arachidonic acid and the biosynthesis of prostaglandin glycerol esters (PG-Gs) from 2-arachidonoylglycerol. PG-Gs are mediators of several biological actions such as macrophage activation, hyperalgesia, synaptic plasticity, and intraocular pressure. Recently, the human UDP receptor P2Y was identified as a target for the prostaglandin E2 glycerol ester (PGE -G). Here, we show that UDP and PGE -G are evolutionary conserved endogenous agonists at vertebrate P2Y orthologs. Using sequence comparison of P2Y orthologs, homology modeling, and ligand docking studies, we proposed several receptor positions participating in agonist binding. Site-directed mutagenesis and functional analysis of these P2Y mutants revealed that both UDP and PGE -G share in parts one ligand-binding site. Thus, the convergent signaling of these two chemically very different agonists has already been manifested in the evolutionary design of the ligand-binding pocket.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35442947,

title = {Predicting the functional impact of KCNQ1 variants with artificial neural networks},

author = {Saksham Phul and Georg Kuenze and Carlos G Vanoye and Charles R Sanders and Alfred L George and Jens Meiler},

doi = {10.1371/journal.pcbi.1010038},

issn = {1553-7358},

year  = {2022},

date = {2022-04-01},

journal = {PLoS Comput Biol},

volume = {18},

number = {4},

pages = {e1010038},

abstract = {Recent advances in experimental and computational protein structure determination have provided access to high-quality structures for most human proteins and mutants thereof. However, linking changes in structure in protein mutants to functional impact remains an active area of method development. If successful, such methods can ultimately assist physicians in taking appropriate treatment decisions. This work presents three artificial neural network (ANN)-based predictive models that classify four key functional parameters of KCNQ1 variants as normal or dysfunctional using PSSM-based evolutionary and/or biophysical descriptors. Recent advances in predicting protein structure and variant properties with artificial intelligence (AI) rely heavily on the availability of evolutionary features and thus fail to directly assess the biophysical underpinnings of a change in structure and/or function. The central goal of this work was to develop an ANN model based on structure and physiochemical properties of KCNQ1 potassium channels that performs comparably or better than algorithms using only on PSSM-based evolutionary features. These biophysical features highlight the structure-function relationships that govern protein stability, function, and regulation. The input sensitivity algorithm incorporates the roles of hydrophobicity, polarizability, and functional densities on key functional parameters of the KCNQ1 channel. Inclusion of the biophysical features outperforms exclusive use of PSSM-based evolutionary features in predicting activation voltage dependence and deactivation time. As AI is increasingly applied to problems in biology, biophysical understanding will be critical with respect to 'explainable AI', i.e., understanding the relation of sequence, structure, and function of proteins. Our model is available at www.kcnq1predict.org.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35238773,

title = {Sampling alternative conformational states of transporters and receptors with AlphaFold2},

author = {Diego Del Alamo and Davide Sala and Hassane S Mchaourab and Jens Meiler},

doi = {10.7554/eLife.75751},

issn = {2050-084X},

year  = {2022},

date = {2022-03-01},

journal = {Elife},

volume = {11},

abstract = {Equilibrium fluctuations and triggered conformational changes often underlie the functional cycles of membrane proteins. For example, transporters mediate the passage of molecules across cell membranes by alternating between inward- and outward-facing states, while receptors undergo intracellular structural rearrangements that initiate signaling cascades. Although the conformational plasticity of these proteins has historically posed a challenge for traditional  protein structure prediction pipelines, the recent success of AlphaFold2 (AF2) in CASP14 culminated in the modeling of a transporter in multiple conformations to high accuracy. Given that AF2 was designed to predict static structures of proteins, it remains unclear if this result represents an underexplored capability to accurately predict multiple conformations and/or structural heterogeneity. Here, we present an approach to drive AF2 to sample alternative conformations of topologically diverse transporters and G-protein-coupled receptors that are absent from the AF2 training set. Whereas models of most proteins generated using the default AF2 pipeline are conformationally homogeneous and nearly identical to one another, reducing the depth of the input multiple sequence alignments by stochastic subsampling led to the generation of accurate models in multiple conformations. In our benchmark, these conformations spanned the range between two experimental structures of interest, with models at the extremes of these conformational distributions observed to be among the most accurate (average template modeling score of 0.94). These results suggest a straightforward approach to identifying native-like alternative states, while also highlighting the need for the next generation of deep learning algorithms to be designed to predict ensembles of biophysically relevant states.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35327663,

title = {Structural Comparative Modeling of Multi-Domain F508del CFTR},

author = {Eli Fritz McDonald and Hope Woods and Shannon T Smith and Minsoo Kim and Clara T Schoeder and Lars Plate and Jens Meiler},

doi = {10.3390/biom12030471},

issn = {2218-273X},

year  = {2022},

date = {2022-03-01},

journal = {Biomolecules},

volume = {12},

number = {3},

abstract = {Cystic fibrosis (CF) is a rare genetic disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR), an epithelial anion channel expressed in several vital organs. Absence of functional CFTR results in imbalanced osmotic equilibrium and subsequent mucus build up in the lungs-which increases the risk of infection and eventually causes death. CFTR is an ATP-binding cassette (ABC) transporter family protein composed of two transmembrane domains (TMDs), two nucleotide binding domains (NBDs), and an unstructured regulatory domain. The most prevalent patient mutation is the deletion of F508 (F508del), making F508del CFTR the primary target for current FDA approved CF therapies. However, no experimental multi-domain F508del CFTR structure has been determined and few studies have modeled F508del using multi-domain WT CFTR structures. Here, we used cryo-EM density data and Rosetta comparative modeling (RosettaCM) to compare a F508del model with published experimental data on CFTR NBD1 thermodynamics. We then apply this modeling method to generate multi-domain WT and F508del CFTR structural models. These models demonstrate the destabilizing effects of F508del on NBD1 and the NBD1/TMD interface in both the inactive and active conformation of CFTR. Furthermore, we modeled F508del/R1070W and F508del bound to the CFTR corrector VX-809. Our models reveal the stabilizing effects of VX-809 on multi-domain models of F508del CFTR and pave the way for rational design of additional drugs that target F508del CFTR for treatment of CF.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35216338,

title = {Veratridine Can Bind to a Site at the Mouth of the Channel Pore at Human Cardiac Sodium Channel Na1.5},

author = {Alican Gulsevin and Andrew M Glazer and Tiffany Shields and Brett M Kroncke and Dan M Roden and Jens Meiler},

doi = {10.3390/ijms23042225},

issn = {1422-0067},

year  = {2022},

date = {2022-02-01},

journal = {Int J Mol Sci},

volume = {23},

number = {4},

abstract = {The cardiac sodium ion channel (Na1.5) is a protein with four domains (DI-DIV), each with six transmembrane segments. Its opening and subsequent inactivation results in the brief rapid influx of Na ions resulting in the depolarization of cardiomyocytes. The neurotoxin veratridine (VTD) inhibits Na1.5 inactivation resulting in longer channel opening times, and potentially fatal action potential prolongation. VTD is predicted to bind at the channel pore, but alternative binding sites have not been ruled out. To determine the binding site of VTD on Na1.5, we perform docking calculations and high-throughput electrophysiology experiments in the present study. The docking calculations identified two distinct binding regions. The first site was in the pore, close to the binding site of Na1.4 and Na1.5 blocking drugs in experimental structures. The second site was at the "mouth" of the pore at the cytosolic side, partly solvent-exposed. Mutations at this site (L409, E417, and I1466) had large effects on VTD binding, while residues deeper in the pore had no effect, consistent with VTD binding at the mouth site. Overall, our results suggest a VTD binding site close to the cytoplasmic mouth of the channel pore. Binding at this alternative site might indicate an allosteric inactivation mechanism for VTD at Na1.5.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35309920,

title = {The Collagen Receptor Discoidin Domain Receptor 1b Enhances Integrin β1-Mediated Cell Migration by Interacting With Talin and Promoting Rac1 Activation},

author = {Corina M Borza and Gema Bolas and Xiuqi Zhang and Mary Beth Browning Monroe and Ming-Zhi Zhang and Jens Meiler and Marcin J Skwark and Raymond C Harris and Lynne A Lapierre and James R Goldenring and Magnus Hook and Jose Rivera and Kyle L Brown and Birgit Leitinger and Matthew J Tyska and Markus Moser and Ralph T Böttcher and Roy Zent and Ambra Pozzi},

doi = {10.3389/fcell.2022.836797},

issn = {2296-634X},

year  = {2022},

date = {2022-01-01},

journal = {Front Cell Dev Biol},

volume = {10},

pages = {836797},

abstract = {Integrins and discoidin domain receptors (DDRs) 1 and 2 promote cell adhesion and migration on both fibrillar and non fibrillar collagens. Collagen I contains DDR and integrin selective binding motifs; however, the relative contribution of these two receptors in regulating cell migration is unclear. DDR1 has five isoforms (DDR1a-e), with most cells expressing the DDR1a and DDR1b isoforms. We show that human embryonic kidney 293 cells expressing DDR1b migrate more than DDR1a expressing cells on DDR selective substrata as well as on collagen I . In addition, DDR1b expressing cells show increased lung colonization after tail vein injection in nude mice. DDR1a and DDR1b differ from each other by an extra 37 amino acids in the DDR1b cytoplasmic domain. Interestingly, these 37 amino acids contain an NPxY motif which is a central control module within the cytoplasmic domain of β integrins and acts by binding scaffold proteins, including talin. Using purified recombinant DDR1 cytoplasmic tail proteins, we show that DDR1b directly binds talin with higher affinity than DDR1a. In cells, DDR1b, but not DDR1a, colocalizes with talin and integrin β1 to focal adhesions and enhances integrin β1-mediated cell migration. Moreover, we show that DDR1b promotes cell migration by enhancing Rac1 activation. Mechanistically DDR1b interacts with the GTPase-activating protein (GAP) Breakpoint cluster region protein (BCR) thus reducing its GAP activity and enhancing Rac activation. Our study identifies DDR1b as a major driver of cell migration and talin and BCR as key players in the interplay between integrins and DDR1b in regulating cell migration.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35264967,

title = {Introduction to the BioChemical Library (BCL): An Application-Based Open-Source Toolkit for Integrated Cheminformatics and Machine Learning in Computer-Aided Drug Discovery},

author = {Benjamin P Brown and Oanh Vu and Alexander R Geanes and Sandeepkumar Kothiwale and Mariusz Butkiewicz and Edward W Lowe and Ralf Mueller and Richard Pape and Jeffrey Mendenhall and Jens Meiler},

doi = {10.3389/fphar.2022.833099},

issn = {1663-9812},

year  = {2022},

date = {2022-01-01},

journal = {Front Pharmacol},

volume = {13},

pages = {833099},

abstract = {The BioChemical Library (BCL) cheminformatics toolkit is an application-based academic open-source software package designed to integrate traditional small molecule cheminformatics tools with machine learning-based quantitative structure-activity/property relationship (QSAR/QSPR) modeling. In this pedagogical article we provide a detailed introduction to core BCL cheminformatics functionality, showing how traditional tasks (e.g., computing chemical properties, estimating druglikeness) can be readily combined with machine learning. In addition, we have included multiple examples covering areas of advanced use, such as reaction-based library design. We anticipate that this manuscript will be a valuable resource for researchers in computer-aided drug discovery looking to integrate modular cheminformatics and machine learning tools into their pipelines.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35544469,

title = {The human antibody sequence space and structural design of the V, J regions, and CDRH3 with Rosetta},

author = {Samuel Schmitz and Emily A Schmitz and James E Crowe and Jens Meiler},

doi = {10.1080/19420862.2022.2068212},

issn = {1942-0870},

year  = {2022},

date = {2022-01-01},

journal = {MAbs},

volume = {14},

number = {1},

pages = {2068212},

abstract = {The human adaptive immune response enables the targeting of epitopes on pathogens with high specificity. Infection with a pathogen induces somatic hyper-mutation and B-cell selection processes that govern the shape and diversity of the antibody sequence landscape. To date, even the largest immunome repertoires of adaptive immune receptors acquired by next-generation sequencing cannot fully capture the vast antibody sequence space of a single individual, which is estimated to be at least 10 potential sequences. Degeneracy of the genetic code means that the number of possible nucleotide triplets (64) is greater than the number of canonical amino acids (20), resulting in some amino acids being encoded by multiple triplets and different amino acids sharing the same nucleotide in 1 or 2 positions in the triplet. We hypothesize that the degeneracy of the genetic code can be used to statistically model an enlarged space of human antibody amino acid sequences, accommodating for the discrepancy between the observed and the hypothesized antibody sequence space. Facilitated by Bayesian statistics and immunome repertoire clustering, we calculated amino acid probabilities from single nucleotide frequencies to infer a human amino acid sequence space that is used to design human-like antibodies with Rosetta. We show that antibodies designed with our restraints are on average up to 16.6% more human-like in the V and J regions compared to the Rosetta designs produced without constraints. The human-likeness of the heavy-chain CDR3 region (CDRH3) could be increased for 8 of 27 antibodies compared to Rosetta designs with a similar number of mutations and could be successfully applied on  antibodies to demonstrate humanization.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36512534,

title = {Rosetta FlexPepDock to predict peptide-MHC binding: An approach for non-canonical amino acids},

author = {Nathaniel Bloodworth and Natália Ruggeri Barbaro and Rocco Moretti and David G Harrison and Jens Meiler},

doi = {10.1371/journal.pone.0275759},

issn = {1932-6203},

year  = {2022},

date = {2022-01-01},

journal = {PLoS One},

volume = {17},

number = {12},

pages = {e0275759},

abstract = {Computation methods that predict the binding of peptides to MHC-I are important tools for screening and identifying immunogenic antigens and have the potential to accelerate vaccine and drug development. However, most available tools are sequence-based and optimized only for peptides containing the twenty canonical amino acids. This omits a large number of peptides containing non-canonical amino acids (NCAA), or residues that undergo varied post-translational modifications such as glycosylation or phosphorylation. These modifications fundamentally alter peptide immunogenicity. Similarly, existing structure-based methods are biased towards canonical peptide backbone structures, which may or may not be preserved when NCAAs are present. Rosetta FlexPepDock ab-initio is a structure-based computational protocol able to evaluate peptide-receptor interaction where no prior information of the peptide backbone is known. We benchmarked FlexPepDock ab-initio for docking canonical peptides to MHC-I, and illustrate for the first time the method's ability to accurately model MHC-I bound epitopes containing NCAAs. FlexPepDock ab-initio protocol was able to recapitulate near-native structures (≤1.5Å) in the top lowest-energy models for 20 out of 25 cases in our initial benchmark. Using known experimental binding affinities of twenty peptides derived from an influenza-derived peptide, we showed that FlexPepDock protocol is able to predict relative binding affinity as Rosetta energies correlate well with experimental values (r = 0.59, p = 0.006). ROC analysis revealed 80% true positive and a 40% false positive rate, with a prediction power of 93%. Finally, we demonstrate the protocol's ability to accurately recapitulate HLA-A*02:01 bound phosphopeptide backbone structures and relative binding affinity changes, the theoretical structure of the lymphocytic choriomeningitis derived glycosylated peptide GP392 bound to MHC-I H-2Db, and isolevuglandin-adducted peptides. The ability to use non-canonical amino acids in the Rosetta FlexPepDock protocol may provide useful insight into critical amino acid positions where the post-translational modification modulates immunologic responses.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34915025,

title = {Mapping of the fibrinogen-binding site on the staphylocoagulase C-terminal repeat region},

author = {Ashoka A Maddur and Markus Voehler and Peter Panizzi and Jens Meiler and Paul E Bock and Ingrid M Verhamme},

doi = {10.1016/j.jbc.2021.101493},

issn = {1083-351X},

year  = {2022},

date = {2022-01-01},

journal = {J Biol Chem},

volume = {298},

number = {1},

pages = {101493},

abstract = {Fibrin (Fbn) deposits are a hallmark of staphylocoagulase (SC)-positive endocarditis. Binding of the N terminus of Staphylococcus aureus SC to host prothrombin triggers formation of an active SC·prothrombin∗ complex that cleaves host fibrinogen to Fbn. In addition, the C-terminal domain of the prototypical SC contains one pseudorepeat (PR) and seven repeats (R1 → R7) that bind fibrinogen/Fbn fragment D (frag D) by a mechanism that is unclear. Here, we define affinities and stoichiometries of frag D binding to C-terminal SC constructs, using fluorescence equilibrium binding, NMR titration, alanine scanning, and native PAGE. We found that constructs containing the PR and single repeats bound frag D with K ∼50 to 130 nM and a 1:1 stoichiometry, indicating a conserved binding site bridging the PR and each repeat. NMR titration of PR-R7 with frag D revealed that residues 22 to 49, bridging PR and R7, constituted the minimal peptide (MP) for binding, corroborated by alanine scanning, and binding of labeled MP to frag D. MP alignment with the PR-R and inter-repeat junctions identified critical conserved residues. Full-length PR-(R1 → R7) bound frag D with K ∼20 nM and a stoichiometry of 1:5, whereas constructs containing the PR and various three repeats competed with PR-(R1 → R7) for frag D binding, with a 1:3 stoichiometry. These findings are consistent with binding at PR-R and R-R junctions with modest inter-repeat sequence variability. CD of PR-R7 and PR-(R1 → R7) suggested a disordered flexible structure, allowing binding of multiple fibrin(ogen) molecules. Taken together, these results provide insights into pathogen localization on host fibrin networks.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35639743,

title = {PlaceWaters: Real-time, explicit interface water sampling during Rosetta ligand docking},

author = {Shannon T Smith and Laura Shub and Jens Meiler},

doi = {10.1371/journal.pone.0269072},

issn = {1932-6203},

year  = {2022},

date = {2022-01-01},

journal = {PLoS One},

volume = {17},

number = {5},

pages = {e0269072},

abstract = {Water molecules at the protein-small molecule interface often form hydrogen bonds with both the small molecule ligand and the protein, affecting the structural integrity and energetics of a binding event. The inclusion of these 'bridging waters' has been shown to improve the accuracy of predicted docked structures; however, due to increased computational costs, this step is typically omitted in ligand docking simulations. In this study, we introduce a resource-efficient, Rosetta-based protocol named "PlaceWaters" to predict the location of explicit interface bridging waters during a ligand docking simulation. In contrast to other explicit water methods, this protocol is independent of knowledge of number and location of crystallographic waters in homologous structures. We test this method on a diverse protein-small molecule benchmark set in comparison to other Rosetta-based protocols. Our results suggest that this coarse-grained, structure-based approach quickly and accurately predicts the location of bridging waters, improving our ability to computationally screen drug candidates.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34822209,

title = {Binding of Natural Peptide Ligands to the Neuropeptide Y Receptor},

author = {Sarina Rudolf and Kerstin Kaempf and Oanh Vu and Jens Meiler and Annette G Beck-Sickinger and Irene Coin},

doi = {10.1002/anie.202108738},

issn = {1521-3773},

year  = {2022},

date = {2022-01-01},

journal = {Angew Chem Int Ed Engl},

volume = {61},

number = {5},

pages = {e202108738},

abstract = {The binding mode of natural peptide ligands to the Y G protein-coupled receptor (Y R), an attractive therapeutic target for the treatment of obesity, is largely unknown. Here, we apply complementary biochemical and computational approaches, including scanning of the receptor surface with a genetically encoded crosslinker, Ala-scanning of the ligand and double-cycle mutagenesis, to map interactions in the ligand-receptor interface and build a structural model of the NPY-Y R complex guided by the experimental data. In the model, the carboxyl (C)-terminus of bound NPY is placed close to the extracellular loop (ECL) 3, whereas the characteristic α-helical segment of the ligand drapes over ECL1 and is tethered towards ECL2 by a hydrophobic cluster. We further show that the other two natural ligands of Y R, peptide YY (PYY) and pancreatic polypeptide (PP) dock to the receptor in a similar pose.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35720345,

title = {Computational Structure Prediction for Antibody-Antigen Complexes From Hydrogen-Deuterium Exchange Mass Spectrometry: Challenges and Outlook},

author = {Minh H Tran and Clara T Schoeder and Kevin L Schey and Jens Meiler},

doi = {10.3389/fimmu.2022.859964},

issn = {1664-3224},

year  = {2022},

date = {2022-01-01},

journal = {Front Immunol},

volume = {13},

pages = {859964},

abstract = {Although computational structure prediction has had great successes in recent years, it regularly fails to predict the interactions of large protein complexes with residue-level accuracy, or even the correct orientation of the protein partners. The performance of computational docking can be notably enhanced by incorporating experimental data from structural biology techniques. A rapid method to probe protein-protein interactions is hydrogen-deuterium exchange mass spectrometry (HDX-MS). HDX-MS has been increasingly used for epitope-mapping of antibodies (Abs) to their respective antigens (Ags) in the past few years. In this paper, we review the current state of HDX-MS in studying protein interactions, specifically Ab-Ag interactions, and how it has been used to inform computational structure prediction calculations. Particularly, we address the limitations of HDX-MS in epitope mapping and techniques and protocols applied to overcome these barriers. Furthermore, we explore computational methods that leverage HDX-MS to aid structure prediction, including the computational simulation of HDX-MS data and the combination of HDX-MS and protein docking. We point out challenges in interpreting and incorporating HDX-MS data into Ab-Ag complex docking and highlight the opportunities they provide to build towards a more optimized hybrid method, allowing for more reliable, high throughput epitope identification.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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{pmid34756884,

title = {Systematic profiling of temperature- and retinal-sensitive rhodopsin variants by deep mutational scanning},

author = {Andrew G McKee and Charles P Kuntz and Joseph T Ortega and Hope Woods and Victoria Most and Francis J Roushar and Jens Meiler and Beata Jastrzebska and Jonathan P Schlebach},

doi = {10.1016/j.jbc.2021.101359},

issn = {1083-351X},

year  = {2021},

date = {2021-12-01},

journal = {J Biol Chem},

volume = {297},

number = {6},

pages = {101359},

abstract = {Membrane protein variants with diminished conformational stability often exhibit enhanced cellular expression at reduced growth temperatures. The expression of "temperature-sensitive" variants is also typically sensitive to corrector molecules that bind and stabilize the native conformation. There are many examples of temperature-sensitive rhodopsin variants, the misfolding of which is associated with the molecular basis of retinitis pigmentosa. In this work, we employ deep mutational scanning to compare the effects of reduced growth temperature and 9-cis-retinal, an investigational corrector, on the plasma membrane expression of 700 rhodopsin variants in HEK293T cells. We find that the change in expression at reduced growth temperatures correlates with the response to 9-cis-retinal among variants bearing mutations within a hydrophobic transmembrane domain (TM2). The most sensitive variants appear to disrupt a native helical kink within this transmembrane domain. By comparison, mutants that alter the structure of a polar transmembrane domain (TM7) exhibit weaker responses to temperature and retinal that are poorly correlated. Statistical analyses suggest that this observed insensitivity cannot be attributed to a single variable, but likely arises from the composite effects of mutations on the energetics of membrane integration, the stability of the native conformation, and the integrity of the retinal-binding pocket. Finally, we show that the characteristics of purified temperature- and retinal-sensitive variants suggest that the proteostatic effects of retinal may be manifested during translation and cotranslational folding. Together, our findings highlight several biophysical constraints that appear to influence the sensitivity of genetic variants to temperature and small-molecule correctors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}