Publications

@article{pmid32156702,

title = {Specificity and affinity of the N-terminal residues in staphylocoagulase in binding to prothrombin},

author = {Ashoka A Maddur and Heather K Kroh and Mary E Aschenbrenner and Breanne H Y Gibson and Peter Panizzi and Jonathan H Sheehan and Jens Meiler and Paul E Bock and Ingrid M Verhamme},

doi = {10.1074/jbc.RA120.012588},

issn = {1083-351X},

year  = {2020},

date = {2020-04-01},

journal = {J Biol Chem},

volume = {295},

number = {17},

pages = {5614--5625},

abstract = {In -caused endocarditis, the pathogen secretes staphylocoagulase (SC), thereby activating human prothrombin (ProT) and evading immune clearance. A previous structural comparison of the SC(1-325) fragment bound to thrombin and its inactive precursor prethrombin 2 has indicated that SC activates ProT by inserting its N-terminal dipeptide Ile-Val into the ProT Ile pocket, forming a salt bridge with ProT's Asp, thereby stabilizing the active conformation. We hypothesized that these N-terminal SC residues modulate ProT binding and activation. Here, we generated labeled SC(1-246) as a probe for competitively defining the affinities of N-terminal SC(1-246) variants preselected by modeling. Using ProT(R155Q,R271Q,R284Q) (ProT), a variant refractory to prothrombinase- or thrombin-mediated cleavage, we observed variant affinities between ∼1 and 650 nm and activation potencies ranging from 1.8-fold that of WT SC(1-246) to complete loss of function. Substrate binding to ProT caused allosteric tightening of the affinity of most SC(1-246) variants, consistent with zymogen activation through occupation of the specificity pocket. Conservative changes at positions 1 and 2 were well-tolerated, with Val-Val, Ile-Ala, and Leu-Val variants exhibiting ProT affinity and activation potency comparable with WT SC(1-246). Weaker binding variants typically had reduced activation rates, although at near-saturating ProT levels, several variants exhibited limiting rates similar to or higher than that of WT SC(1-246). The Ile pocket in ProT appears to favor nonpolar, nonaromatic residues at SC positions 1 and 2. Our results suggest that SC variants other than WT Ile-Val-Thr might emerge with similar ProT-activating efficiency.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32181350,

title = {Probing biophysical sequence constraints within the transmembrane domains of rhodopsin by deep mutational scanning},

author = {Wesley D Penn and Andrew G McKee and Charles P Kuntz and Hope Woods and Veronica Nash and Timothy C Gruenhagen and Francis J Roushar and Mahesh Chandak and Chris Hemmerich and Douglas B Rusch and Jens Meiler and Jonathan P Schlebach},

doi = {10.1126/sciadv.aay7505},

issn = {2375-2548},

year  = {2020},

date = {2020-03-01},

journal = {Sci Adv},

volume = {6},

number = {10},

pages = {eaay7505},

abstract = {Membrane proteins must balance the sequence constraints associated with folding and function against the hydrophobicity required for solvation within the bilayer. We recently found the expression and maturation of rhodopsin are limited by the hydrophobicity of its seventh transmembrane domain (TM7), which contains polar residues that are essential for function. On the basis of these observations, we hypothesized that rhodopsin's expression should be less tolerant of mutations in TM7 relative to those within hydrophobic TM domains. To test this hypothesis, we used deep mutational scanning to compare the effects of 808 missense mutations on the plasma membrane expression of rhodopsin in HEK293T cells. Our results confirm that a higher proportion of mutations within TM7 (37%) decrease rhodopsin's plasma membrane expression relative to those within a hydrophobic TM domain (TM2, 25%). These results in conjunction with an evolutionary analysis suggest solvation energetics likely restricts the evolutionary sequence space of polar TM domains.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32096762,

title = {Structure and physiological function of the human KCNQ1 channel voltage sensor intermediate state},

author = {Keenan C Taylor and Po Wei Kang and Panpan Hou and Nien-Du Yang and Georg Kuenze and Jarrod A Smith and Jingyi Shi and Hui Huang and Kelli McFarland White and Dungeng Peng and Alfred L George and Jens Meiler and Robert L McFeeters and Jianmin Cui and Charles R Sanders},

doi = {10.7554/eLife.53901},

issn = {2050-084X},

year  = {2020},

date = {2020-02-01},

journal = {Elife},

volume = {9},

abstract = {Voltage-gated ion channels feature voltage sensor domains (VSDs) that exist in three distinct conformations during activation: resting, intermediate, and activated. Experimental determination of the structure of a potassium channel VSD in the intermediate state has previously proven elusive. Here, we report and validate the experimental three-dimensional structure of the human KCNQ1 voltage-gated potassium channel VSD in the intermediate state. We also used mutagenesis and electrophysiology in oocytes to functionally map the determinants of S4 helix motion during voltage-dependent transition from the intermediate to the activated state. Finally, the physiological relevance of the intermediate state KCNQ1 conductance is demonstrated using voltage-clamp fluorometry. This work illuminates the structure of the VSD intermediate state and demonstrates that intermediate state conductivity contributes to the unusual versatility of KCNQ1, which can function either as the slow delayed rectifier current (I) of the cardiac action potential or as a constitutively active epithelial leak current.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32032348,

title = {Multi-state design of flexible proteins predicts sequences optimal for conformational change},

author = {Marion F Sauer and Alexander M Sevy and James E Crowe and Jens Meiler},

doi = {10.1371/journal.pcbi.1007339},

issn = {1553-7358},

year  = {2020},

date = {2020-02-01},

journal = {PLoS Comput Biol},

volume = {16},

number = {2},

pages = {e1007339},

abstract = {Computational protein design of an ensemble of conformations for one protein-i.e., multi-state design-determines the side chain identity by optimizing the energetic contributions of that side chain in each of the backbone conformations. Sampling the resulting large sequence-structure search space limits the number of conformations and the size of proteins in multi-state design algorithms. Here, we demonstrated that the REstrained CONvergence (RECON) algorithm can simultaneously evaluate the sequence of large proteins that undergo substantial conformational changes. Simultaneous optimization of side chain conformations across all conformations increased sequence conservation when compared to single-state designs in all cases. More importantly, the sequence space sampled by RECON MSD resembled the evolutionary sequence space of flexible proteins, particularly when confined to predicting the mutational preferences of limited common ancestral descent, such as in the case of influenza type A hemagglutinin. Additionally, we found that sequence positions which require substantial changes in their local environment across an ensemble of conformations are more likely to be conserved. These increased conservation rates are better captured by RECON MSD over multiple conformations and thus multiple local residue environments during design. To quantify this rewiring of contacts at a certain position in sequence and structure, we introduced a new metric designated 'contact proximity deviation' that enumerates contact map changes. This measure allows mapping of global conformational changes into local side chain proximity adjustments, a property not captured by traditional global similarity metrics such as RMSD or local similarity metrics such as changes in φ and ψ angles.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32431610,

title = {Structures Illuminate Cardiac Ion Channel Functions in Health and in Long QT Syndrome},

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

doi = {10.3389/fphar.2020.00550},

issn = {1663-9812},

year  = {2020},

date = {2020-01-01},

journal = {Front Pharmacol},

volume = {11},

pages = {550},

abstract = {The cardiac action potential is critical to the production of a synchronized heartbeat. This electrical impulse is governed by the intricate activity of cardiac ion channels, among them the cardiac voltage-gated potassium (K) channels KCNQ1 and hERG as well as the voltage-gated sodium (Na) channel encoded by . Each channel performs a highly distinct function, despite sharing a common topology and structural components. These three channels are also the primary proteins mutated in congenital long QT syndrome (LQTS), a genetic condition that predisposes to cardiac arrhythmia and sudden cardiac death due to impaired repolarization of the action potential and has a particular proclivity for reentrant ventricular arrhythmias. Recent cryo-electron microscopy structures of human KCNQ1 and hERG, along with the rat homolog of SCN5A and other mammalian sodium channels, provide atomic-level insight into the structure and function of these proteins that advance our understanding of their distinct functions in the cardiac action potential, as well as the molecular basis of LQTS. In this review, the gating, regulation, LQTS mechanisms, and pharmacological properties of KCNQ1, hERG, and SCN5A are discussed in light of these recent structural findings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33044994,

title = {Assessing multiple score functions in Rosetta for drug discovery},

author = {Shannon T Smith and Jens Meiler},

doi = {10.1371/journal.pone.0240450},

issn = {1932-6203},

year  = {2020},

date = {2020-01-01},

journal = {PLoS One},

volume = {15},

number = {10},

pages = {e0240450},

abstract = {Rosetta is a computational software suite containing algorithms for a wide variety of macromolecular structure prediction and design tasks including small molecule protocols commonly used in drug discovery or enzyme design. Here, we benchmark RosettaLigand score functions and protocols in comparison to results of other software recently published in the Comparative Assessment of Score Functions (CASF-2016). The CASF-2016 benchmark covers a wide variety of tests including scoring and ranking multiple compounds against a target, ligand docking of a small molecule to a target, and virtual screening to extract binders from a compound library. Direct comparison to the score functions provided by CASF-2016 results shows that the original RosettaLigand score function ranks among the top software for scoring, ranking, docking and screening tests. Most notably, the RosettaLigand score function ranked 2/34 among other report score functions in CASF-2016. We additionally perform a ligand docking test with full sampling to mimic typical use cases. Despite improved performance of newer score functions in canonical protein structure prediction and design, we demonstrate here that more recent Rosetta score functions have reduced performance across all small molecule benchmarks. The tests described here have also been uploaded to the Rosetta scientific benchmarking server and will be run weekly to track performance as the code is continually being developed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31892409,

title = {Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction},

author = {Diego Del Alamo and Maxx H Tessmer and Richard A Stein and Jimmy B Feix and Hassane S Mchaourab and Jens Meiler},

doi = {10.1016/j.bpj.2019.12.011},

issn = {1542-0086},

year  = {2020},

date = {2020-01-01},

journal = {Biophys J},

volume = {118},

number = {2},

pages = {366--375},

abstract = {Despite advances in sampling and scoring strategies, Monte Carlo modeling methods still struggle to accurately predict de novo the structures of large proteins, membrane proteins, or proteins of complex topologies. Previous approaches have addressed these shortcomings by leveraging sparse distance data gathered using site-directed spin labeling and electron paramagnetic resonance spectroscopy to improve protein structure prediction and refinement outcomes. However, existing computational implementations entail compromises between coarse-grained models of the spin label that lower the resolution and explicit models that lead to resource-intense simulations. These methods are further limited by their reliance on distance distributions, which are calculated from a primary refocused echo decay signal and contain uncertainties that may require manual refinement. Here, we addressed these challenges by developing RosettaDEER, a scoring method within the Rosetta software suite capable of simulating double electron-electron resonance spectroscopy decay traces and distance distributions between spin labels fast enough to fold proteins de novo. We demonstrate that the accuracy of resulting distance distributions match or exceed those generated by more computationally intensive methods. Moreover, decay traces generated from these distributions recapitulate intermolecular background coupling parameters even when the time window of data collection is truncated. As a result, RosettaDEER can discriminate between poorly folded and native-like models by using decay traces that cannot be accurately converted into distance distributions using regularized fitting approaches. Finally, using two challenging test cases, we demonstrate that RosettaDEER leverages these experimental data for protein fold prediction more effectively than previous methods. These benchmarking results confirm that RosettaDEER can effectively leverage sparse experimental data for a wide array of modeling applications built into the Rosetta software suite.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32397786,

title = {Human-likeness of antibody biologics determined by back-translation and comparison with large antibody variable gene repertoires},

author = {Samuel Schmitz and Cinque Soto and James E Crowe and Jens Meiler},

doi = {10.1080/19420862.2020.1758291},

issn = {1942-0870},

year  = {2020},

date = {2020-01-01},

journal = {MAbs},

volume = {12},

number = {1},

pages = {1758291},

abstract = {The antibody (Ab) germline gene rearrangement of variable (V), diversity (D), and joining (J) gene segments, as well as somatic hypermutation, give rise to the human Ab variable gene sequence repertoire. It is common to characterize single nucleotide frequencies of the variable region by alignment to species-specific wildtype germline genes. The increasing application of next-generation sequencing to immune repertoire studies has led to the compilation of increasing large adaptive immunome receptor repertoire datasets. We have developed a method that maps the sequence of a target Ab onto an immunome dataset of 326 million human Ab sequences. For this purpose, we created a position- and gene-specific scoring matrix (PGSSM) and its corresponding antibody similarity score. We characterized our PGSSM score and found that it strongly correlated with the phylogenetic distance of 181,355 Ab sequences from GenBank across 20 species. The most likely human nucleotide back-translation was obtained given only PGSSMs and the amino acid sequence of an Ab achieving a nucleotide sequence recovery of 95.9% and 97.2% for human heavy and light chains, respectively. In conclusion, the scoring of our back-translation is a valuable estimate for the similarity of an Ab sequence to the natural human repertoire. As expected, Ab therapeutic molecules developed from a human source showed a higher similarity to the repertoire than engineered Abs. Thus, the PGSSM metric introduced here can be used to engineer human-like Ab therapeutics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31936129,

title = {Delineating the Molecular Basis of the Calmodulin‒bMunc13-2 Interaction by Cross-Linking/Mass Spectrometry-Evidence for a Novel CaM Binding Motif in bMunc13-2},

author = {Christine Piotrowski and Rocco Moretti and Christian H Ihling and André Haedicke and Thomas Liepold and Noa Lipstein and Jens Meiler and Olaf Jahn and Andrea Sinz},

doi = {10.3390/cells9010136},

issn = {2073-4409},

year  = {2020},

date = {2020-01-01},

journal = {Cells},

volume = {9},

number = {1},

abstract = {Exploring the interactions between the Ca binding protein calmodulin (CaM) and its target proteins remains a challenging task. Members of the Munc13 protein family play an essential role in short-term synaptic plasticity, modulated via the interaction with CaM at the presynaptic compartment. In this study, we focus on the bMunc13-2 isoform expressed in the brain, as strong changes in synaptic transmission were observed upon its mutagenesis or deletion. The CaM‒bMunc13-2 interaction was previously characterized at the molecular level using short bMunc13-2-derived peptides only, revealing a classical 1‒5‒10 CaM binding motif. Using larger protein constructs, we have now identified for the first time a novel and unique CaM binding site in bMunc13-2 that contains an -terminal extension of a classical 1‒5‒10 CaM binding motif. We characterize this motif using a range of biochemical and biophysical methods and highlight its importance for the CaM‒bMunc13-2 interaction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31292988,

title = {Protein structure prediction using sparse NOE and RDC restraints with Rosetta in CASP13},

author = {Georg Kuenze and Jens Meiler},

doi = {10.1002/prot.25769},

issn = {1097-0134},

year  = {2019},

date = {2019-12-01},

journal = {Proteins},

volume = {87},

number = {12},

pages = {1341--1350},

abstract = {Computational methods that produce accurate protein structure models from limited experimental data, for example, from nuclear magnetic resonance (NMR) spectroscopy, hold great potential for biomedical research. The NMR-assisted modeling challenge in CASP13 provided a blind test to explore the capabilities and limitations of current modeling techniques in leveraging NMR data which had high sparsity, ambiguity, and error rate for protein structure prediction. We describe our approach to predict the structure of these proteins leveraging the Rosetta software suite. Protein structure models were predicted de novo using a two-stage protocol. First, low-resolution models were generated with the Rosetta de novo method guided by nonambiguous nuclear Overhauser effect (NOE) contacts and residual dipolar coupling (RDC) restraints. Second, iterative model hybridization and fragment insertion with the Rosetta comparative modeling method was used to refine and regularize models guided by all ambiguous and nonambiguous NOE contacts and RDCs. Nine out of 16 of the Rosetta de novo models had the correct fold (global distance test total score > 45) and in three cases high-resolution models were achieved (root-mean-square deviation < 3.5 å). We also show that a meta-approach applying iterative Rosetta + NMR refinement on server-predicted models which employed non-NMR-contacts and structural templates leads to substantial improvement in model quality. Integrating these data-assisted refinement strategies with innovative non-data-assisted approaches which became possible in CASP13 such as high precision contact prediction will in the near future enable structure determination for large proteins that are outside of the realm of conventional NMR.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31801472,

title = {Immune repertoire fingerprinting by principal component analysis reveals shared features in subject groups with common exposures},

author = {Alexander M Sevy and Cinque Soto and Robin G Bombardi and Jens Meiler and James E Crowe},

doi = {10.1186/s12859-019-3281-8},

issn = {1471-2105},

year  = {2019},

date = {2019-12-01},

journal = {BMC Bioinformatics},

volume = {20},

number = {1},

pages = {629},

abstract = {BACKGROUND: Advances in next-generation sequencing (NGS) of antibody repertoires have led to an explosion in B cell receptor sequence data from donors with many different disease states. These data have the potential to detect patterns of immune response across populations. However, to this point it has been difficult to interpret such patterns of immune response between disease states in the absence of functional data. There is a need for a robust method that can be used to distinguish general patterns of immune responses at the antibody repertoire level.nnRESULTS: We developed a method for reducing the complexity of antibody repertoire datasets using principal component analysis (PCA) and refer to our method as "repertoire fingerprinting." We reduce the high dimensional space of an antibody repertoire to just two principal components that explain the majority of variation in those repertoires. We show that repertoires from individuals with a common experience or disease state can be clustered by their repertoire fingerprints to identify common antibody responses.nnCONCLUSIONS: Our repertoire fingerprinting method for distinguishing immune repertoires has implications for characterizing an individual disease state. Methods to distinguish disease states based on pattern recognition in the adaptive immune response could be used to develop biomarkers with diagnostic or prognostic utility in patient care. Extending our analysis to larger cohorts of patients in the future should permit us to define more precisely those characteristics of the immune response that result from natural infection or autoimmunity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31522945,

title = {Integrative Protein Modeling in RosettaNMR from Sparse Paramagnetic Restraints},

author = {Georg Kuenze and Richard Bonneau and Julia Koehler Leman and Jens Meiler},

doi = {10.1016/j.str.2019.08.012},

issn = {1878-4186},

year  = {2019},

date = {2019-11-01},

journal = {Structure},

volume = {27},

number = {11},

pages = {1721--1734.e5},

abstract = {Computational methods to predict protein structure from nuclear magnetic resonance (NMR) restraints that only require assignment of backbone signals, hold great potential to study larger proteins. Ideally, computational methods designed to work with sparse data need to add atomic detail that is missing in the experimental restraints. We introduce a comprehensive framework into the Rosetta suite that uses NMR restraints derived from paramagnetic labeling. Specifically, RosettaNMR incorporates pseudocontact shifts, residual dipolar couplings, and paramagnetic relaxation enhancements. It continues to use backbone chemical shifts and nuclear Overhauser effect distance restraints. We assess RosettaNMR for protein structure prediction by folding 28 monomeric proteins and 8 homo-oligomeric proteins. Furthermore, the general applicability of RosettaNMR is demonstrated on two protein-protein and three protein-ligand docking examples. Paramagnetic restraints generated more accurate models for 85% of the benchmark proteins and, when combined with chemical shifts, sampled high-accuracy models (≤2Å) in 50% of the cases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31641091,

title = {Human  Gene-Encoded Human Monoclonal Antibodies against Staphylococcus aureus IsdB Use at Least Three Distinct Modes of Binding To Inhibit Bacterial Growth and Pathogenesis},

author = {Monique R Bennett and Jinhui Dong and Robin G Bombardi and Cinque Soto and Helen M Parrington and Rachel S Nargi and Clara T Schoeder and Marcus B Nagel and Kevin L Schey and Jens Meiler and Eric P Skaar and James E Crowe},

doi = {10.1128/mBio.02473-19},

issn = {2150-7511},

year  = {2019},

date = {2019-10-01},

journal = {mBio},

volume = {10},

number = {5},

abstract = { is an important human pathogen that infects nearly every human tissue. Like most organisms, the acquisition of nutrient iron is necessary for its survival. One route by which it obtains this metal is through the iron-regulated surface determinant (Isd) system that scavenges iron from the hemoglobin of the host. We show that the heavy chain variable region  gene commonly encodes human monoclonal antibodies (mAbs) targeting IsdB-NEAT2. Remarkably, these antibodies bind to multiple antigenic sites. One class of -encoded mAbs blocks  heme acquisition by binding to the heme-binding site of NEAT2, while two additional classes reduce the bacterial burden  by an alternative Fc receptor-mediated mechanism. We further identified clonal lineages of -encoded mAbs using donor samples, showing that each lineage diversifies during infection by somatic hypermutation. These studies reveal that encoded antibodies contribute to a protective immune response, furthering our understanding of the correlates of protection against  infection. The human pathogen  causes a wide range of infections, including skin abscesses and sepsis. There is currently no licensed vaccine to prevent  infection, and its treatment has become increasingly difficult due to antibiotic resistance. One potential way to inhibit  pathogenesis is to prevent iron acquisition. The iron-regulated surface determinant (Isd) system has evolved in  to acquire hemoglobin from the human host as a source of heme-iron. In this study, we investigated the molecular and structural basis for antibody-mediated correlates against a member of the Isd system, IsdB. The association of immunoglobulin heavy chain variable region  gene-encoded human monoclonal antibodies with the response against  IsdB is described using structural and functional studies to define the importance of this antibody class. We also determine that somatic hypermutation in the development of these antibodies hinders rather than fine-tunes the immune response to IsdB.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31504490,

title = {The Impact of Natural Selection on the Evolution and Function of Placentally Expressed Galectins},

author = {Zackery A Ely and Jiyun M Moon and Gregory R Sliwoski and Amandeep K Sangha and Xing-Xing Shen and Abigail L Labella and Jens Meiler and John A Capra and Antonis Rokas},

doi = {10.1093/gbe/evz183},

issn = {1759-6653},

year  = {2019},

date = {2019-09-01},

journal = {Genome Biol Evol},

volume = {11},

number = {9},

pages = {2574--2592},

abstract = {Immunity genes have repeatedly experienced natural selection during mammalian evolution. Galectins are carbohydrate-binding proteins that regulate diverse immune responses, including maternal-fetal immune tolerance in placental pregnancy. Seven human galectins, four conserved across vertebrates and three specific to primates, are involved in placental development. To comprehensively study the molecular evolution of these galectins, both across mammals and within humans, we conducted a series of between- and within-species evolutionary analyses. By examining patterns of sequence evolution between species, we found that primate-specific galectins showed uniformly high substitution rates, whereas two of the four other galectins experienced accelerated evolution in primates. By examining human population genomic variation, we found that galectin genes and variants, including variants previously linked to immune diseases, showed signatures of recent positive selection in specific human populations. By examining one nonsynonymous variant in Galectin-8 previously associated with autoimmune diseases, we further discovered that it is tightly linked to three other nonsynonymous variants; surprisingly, the global frequency of this four-variant haplotype is ∼50%. To begin understanding the impact of this major haplotype on Galectin-8 protein structure, we modeled its 3D protein structure and found that it differed substantially from the reference protein structure. These results suggest that placentally expressed galectins experienced both ancient and more recent selection in a lineage- and population-specific manner. Furthermore, our discovery that the major Galectin-8 haplotype is structurally distinct from and more commonly found than the reference haplotype illustrates the significance of understanding the evolutionary processes that sculpted variants associated with human genetic disease.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31132237,

title = {Identification of Novel Allosteric Modulators of Metabotropic Glutamate Receptor Subtype 5 Acting at Site Distinct from 2-Methyl-6-(phenylethynyl)-pyridine Binding},

author = {Mariusz Butkiewicz and Alice L Rodriguez and Shane E Rainey and Joshua Wieting and Vincent B Luscombe and Shaun R Stauffer and Craig W Lindsley and P Jeffrey Conn and Jens Meiler},

doi = {10.1021/acschemneuro.8b00227},

issn = {1948-7193},

year  = {2019},

date = {2019-08-01},

journal = {ACS Chem Neurosci},

volume = {10},

number = {8},

pages = {3427--3436},

abstract = {As part of the G-protein coupled receptor (GPCR) family, metabotropic glutamate (mGlu) receptors play an important role as drug targets of cognitive diseases. Selective allosteric modulators of mGlu subtype 5 (mGlu) have the potential to alleviate symptoms of numerous central nervous system disorders such as schizophrenia in a more targeted fashion. Multiple mGlu positive allosteric modulators (PAMs), such as 1-(3-fluorophenyl)--((3-fluorophenyl)-methylideneamino)-methanimine (DFB), 3-cyano--(1,3-diphenyl-1-pyrazol-5-yl)-benzamide (CDPPB), and 4-nitro--(1,3-diphenyl-1-pyrazol-5-yl)-benzamide (VU-29), exert their actions by binding to a defined allosteric site on mGlu located in the seven-transmembrane domain (7TM) and shared by mGlu negative allosteric modulator (NAM) 2-methyl-6-(phenylethynyl)-pyridine (MPEP). Actions of the PAM -{4-chloro-2-[(1,3-dioxo-1,3-dihydro-2-isoindol-2-yl)methyl]phenyl}-2-hydroxybenzamide (CPPHA) are mediated by a distinct allosteric site in the 7TM domain different from the MPEP binding site. Experimental evidence confirms these findings through mutagenesis experiments involving residues F585 (TM1) and A809 (TM7). In an effort to investigate mGlu PAM selectivity for this alternative allosteric site distinct from MPEP binding, we employed  quantitative structure-activity relationship (QSAR) modeling. Subsequent ligand-based virtual screening prioritized a set of 63 candidate compounds predicted from a library of over 4 million commercially available compounds to bind exclusively to this novel site. Experimental validation verified the biological activity for seven of 63 selected candidates. Further, medicinal chemistry optimizations based on these molecules revealed compound VU6003586 with an experimentally validated potency of 174 nM. Radioligand binding experiments showed only partial inhibition at very high concentrations, most likely indicative of binding at a non-MPEP site. Selective positive allosteric modulators for mGlu have the potential for tremendous impact concerning devastating neurological disorders such as schizophrenia and Huntington's disease. These identified and validated novel selective compounds can serve as starting points for more specifically tailored lead and probe molecules and thus help the development of potential therapeutic agents with reduced adverse effects.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31243635,

title = {A unified structural model of the mammalian translocator protein (TSPO)},

author = {Yan Xia and Kaitlyn Ledwitch and Georg Kuenze and Amanda Duran and Jun Li and Charles R Sanders and Charles Manning and Jens Meiler},

doi = {10.1007/s10858-019-00257-1},

issn = {1573-5001},

year  = {2019},

date = {2019-07-01},

journal = {J Biomol NMR},

volume = {73},

number = {6-7},

pages = {347--364},

abstract = {The translocator protein (TSPO), previously known as the peripheral benzodiazepine receptor (PBR), is a membrane protein located on the outer mitochondrial membrane. Experimentally-derived structures of mouse TSPO (mTSPO) and its homologs from bacterial species have been determined by NMR spectroscopy and X-ray crystallography, respectively. These structures and ligand interactions within the TSPO binding pocket display distinct differences. Here, we leverage experimental and computational studies to derive a unified structural model of mTSPO in the presence and absence of the TSPO ligand, PK11195, and study the effects of DPC detergent micelles on the TSPO structure and ligand binding. From this work, we conclude that that the lipid-mimetic system used to solubilize mTSPO for NMR studies thermodynamically destabilizes the protein, introduces structural perturbations, and alters the characteristics of ligand binding. Furthermore, we used Rosetta to construct a unified mTSPO model that reconciles deviating features of the mammalian and bacterial TSPO. These deviating features are likely a consequence of the detergent system used for structure determination of mTSPO by NMR. The unified mTSPO model agrees with available experimental NMR data, appears to be physically realistic (i.e. thermodynamically not frustrated as judged by the Rosetta energy function), and simultaneously shares the structural features observed in sequence-conserved regions of the bacterial proteins. Finally, we identified the binding site for an imaging ligand VUIIS8310 that is currently positioned for clinical translation using NMR spectroscopy and propose a computational model of the VUIIS8310-mTSPO complex.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30796031,

title = {On-target Resistance to the Mutant-Selective EGFR Inhibitor Osimertinib Can Develop in an Allele-Specific Manner Dependent on the Original EGFR-Activating Mutation},

author = {Benjamin P Brown and Yun-Kai Zhang and David Westover and Yingjun Yan and Huan Qiao and Vincent Huang and Zhenfang Du and Jarrod A Smith and Jeffrey S Ross and Vincent A Miller and Siraj Ali and Lyudmila Bazhenova and Alexa B Schrock and Jens Meiler and Christine M Lovly},

doi = {10.1158/1078-0432.CCR-18-3829},

issn = {1557-3265},

year  = {2019},

date = {2019-06-01},

journal = {Clin Cancer Res},

volume = {25},

number = {11},

pages = {3341--3351},

abstract = {PURPOSE: The third-generation EGFR inhibitor, osimertinib, is the first mutant-selective inhibitor that has received regulatory approval for the treatment of patients with -mutant lung cancer. Despite the development of highly selective third-generation inhibitors, acquired resistance remains a significant clinical challenge. Recently, we and others have identified a novel osimertinib resistance mutation, G724S, which was not predicted in  screens. Here, we investigate how G724S confers resistance to osimertinib. We combine structure-based predictive modeling of G724S in combination with the 2 most common EGFR-activating mutations, exon 19 deletion (Ex19Del) and L858R, with  drug-response models and patient genomic profiling.nnRESULTS: Our simulations suggest that the G724S mutation selectively reduces osimertinib-binding affinity in the context of Ex19Del. Consistent with our simulations, cell lines transduced with Ex19Del/G724S demonstrate resistance to osimertinib, whereas cells transduced with L858R/G724S are sensitive to osimertinib. Subsequent clinical genomic profiling data further suggest G724S occurs with Ex19Del but not L858R. Furthermore, we demonstrate that Ex19Del/G724S retains sensitivity to afatinib, but not to erlotinib, suggesting a possible therapy for patients at the time of disease relapse.nnCONCLUSIONS: Altogether, these data suggest that G724S is an allele-specific resistance mutation emerging in the context of Ex19Del but not L858R. Our results fundamentally reframe the problem of targeted therapy resistance from one focused on the "drug-resistance mutation" pair to one focused on the "activating mutation-drug-resistance mutation" trio. This has broad implications across clinical oncology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30993913,

title = {IgG4-related disease: Association with a rare gene variant expressed in cytotoxic T cells},

author = {John H Newman and Aaron Shaver and Jonathan H Sheehan and Simon Mallal and John H Stone and Shiv Pillai and Lisa Bastarache and Derek Riebau and Hugues Allard-Chamard and William M Stone and Cory Perugino and Mark Pilkinton and Scott A Smith and Wyatt J McDonnell and John A Capra and Jens Meiler and Joy Cogan and Kelly Xing and Vinay S Mahajan and Hamid Mattoo and Rizwan Hamid and John A Phillips and },

doi = {10.1002/mgg3.686},

issn = {2324-9269},

year  = {2019},

date = {2019-06-01},

journal = {Mol Genet Genomic Med},

volume = {7},

number = {6},

pages = {e686},

abstract = {BACKGROUND: Family screening of a 48-year-old male with recently diagnosed IgG4-related disease (IgG4-RD) revealed unanticipated elevations in plasma IgG4 in his two healthy teenaged sons.nnMETHODS: We performed gene sequencing, immune cell studies, HLA typing, and analyses of circulating cytotoxic CD4+ T lymphocytes and plasmablasts to seek clues to pathogenesis. DNA from a separate cohort of 99 patients with known IgG4-RD was also sequenced for the presence of genetic variants in a specific gene, FGFBP2.nnRESULTS: The three share a previously unreported heterozygous single base deletion in fibroblast growth factor binding protein type 2 (FGFBP2), which causes a frameshift in the coding sequence. The FGFBP2 protein is secreted by cytotoxic T-lymphocytes and binds fibroblast growth factor. The variant sequence in the FGFBP2 protein is predicted to form a disordered random coil rather than a helical-turn-helix structure, unable to adopt a stable conformation. The proband and the two sons had 5-10-fold higher numbers of circulating cytotoxic CD4 + T cells and plasmablasts compared to matched controls. The three members also share a homozygous missense common variant in FGFBP2 found in heterozygous form in ~40% of the population. This common variant was found in 73% of an independent, well characterized IgG4-RD cohort, showing enrichment in idiopathic IgG4-RD.nnCONCLUSIONS: The presence of a shared deleterious variant and homozygous common variant in FGFBP2 in the proband and sons strongly implicates this cytotoxic T cell product in the pathophysiology of IgG4-RD. The high prevalence of a common FGFBP2 variant in sporadic IgG4-RD supports the likelihood of participation in disease.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30085373,

title = {Mono(2-ethylhexyl) phthalate (MEHP) and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) but not di(2-ethylhexyl) phthalate (DEHP) bind productively to the peroxisome proliferator-activated receptor γ},

author = {Isabel Kratochvil and Tommy Hofmann and Sandra Rother and Rita Schlichting and Rocco Moretti and Dieter Scharnweber and Vera Hintze and Beate I Escher and Jens Meiler and Stefan Kalkhof and Martin von Bergen},

doi = {10.1002/rcm.8258},

issn = {1097-0231},

year  = {2019},

date = {2019-05-01},

journal = {Rapid Commun Mass Spectrom},

volume = {33 Suppl 1},

number = {Suppl 1},

pages = {75--85},

abstract = {RATIONALE: The most frequently occurring phthalate, di(2-ethylhexyl) phthalate (DEHP), causes adverse effects on glucose homeostasis and insulin sensitivity in several cell models and epidemiological studies. However, thus far, there is no information available on the molecular interaction of phthalates and one of the key regulators of the metabolism, the peroxisome proliferator-activated receptor gamma (PPARγ). Since the endogenous ligand of PPARγ, 15-deoxy-delta-12,14-prostaglandin J (15Δ-PGJ ), features structural similarity to DEHP and its main metabolites produced in human hepatic metabolism, mono(2-ethylhexyl) phthalate (MEHP) and mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), we tested the hypothesis of direct interactions between PPARγ and DEHP or its transformation products.nnMETHODS: Hydrogen/deuterium exchange mass spectrometry (HDX-MS) and docking were conducted to obtain structural insights into the interactions and surface plasmon resonance (SPR) analysis to reveal information about binding levels. To confirm the activation of PPARγ upon ligand binding on the cellular level, the GeneBLAzer® bioassay was performed.nnRESULTS: HDX-MS and SPR analyses demonstrated that the metabolites MEHP and MEOHP, but not DEHP itself, bind to the ligand binding pocket of PPARγ. This binding leads to typical activation-associated conformational changes, as observed with its endogenous ligand 15Δ-PGJ . Furthermore, the reporter gene assay confirmed productive interaction. DEHP was inactive up to a concentration of 14 μM, while the metabolites MEHP and MEOHP were active at low micromolar concentrations.nnCONCLUSIONS: In summary, this study gives structural insights into the direct interaction of PPARγ with MEHP and MEOHP and shows that the DEHP transformation products may modulate the lipid metabolism through PPARγ pathways.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30955193,

title = {BCL::Mol2D-a robust atom environment descriptor for QSAR modeling and lead optimization},

author = {Oanh Vu and Jeffrey Mendenhall and Doaa Altarawy and Jens Meiler},

doi = {10.1007/s10822-019-00199-8},

issn = {1573-4951},

year  = {2019},

date = {2019-05-01},

journal = {J Comput Aided Mol Des},

volume = {33},

number = {5},

pages = {477--486},

abstract = {Comparing fragment based molecular fingerprints of drug-like molecules is one of the most robust and frequently used approaches in computer-assisted drug discovery. Molprint2D, a popular atom environment (AE) descriptor, yielded the best enrichment of active compounds across a diverse set of targets in a recent large-scale study. We present here BCL::Mol2D descriptors that outperformed Molprint2D on nine PubChem datasets spanning a wide range of protein classes. Because BCL::Mol2D records the number of AEs from a universal AE library, a novel aspect of BCL::Mol2D over the Molprint2D is its reversibility. This property enables decomposition of prediction from machine learning models to particular molecular substructures. Artificial neural networks with dropout, when trained on BCL::Mol2D descriptors outperform those trained on Molprint2D descriptors by up to 26% in logAUC metric. When combined with the Reduced Short Range descriptor set, our previously published set of descriptors optimized for QSARs, BCL::Mol2D yields a modest improvement. Finally, we demonstrate how the reversibility of BCL::Mol2D enables visualization of a 'pharmacophore map' that could guide lead optimization for serine/threonine kinase 33 inhibitors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30835430,

title = {The STAT5b Linker Domain Mediates the Selectivity of Catechol Bisphosphates for STAT5b over STAT5a},

author = {Julian Gräb and Angela Berg and Linda Blechschmidt and Barbara Klüver and Stefan Rubner and Darwin Y Fu and Jens Meiler and Martin Gräber and Thorsten Berg},

doi = {10.1021/acschembio.9b00137},

issn = {1554-8937},

year  = {2019},

date = {2019-04-01},

journal = {ACS Chem Biol},

volume = {14},

number = {4},

pages = {796--805},

abstract = {STAT family proteins are important mediators of cell signaling and represent therapeutic targets for the treatment of human diseases. Most STAT inhibitors target the protein-protein interaction domain, the SH2 domain, but specificity for a single STAT protein is often limited. Recently, we developed catechol bisphosphates as the first inhibitors of STAT5b demonstrated to exhibit a high degree of selectivity over the close homologue STAT5a. Here, we show that the amino acid in position 566 of the linker domain, not the SH2 domain, is the main determinant of specificity. Arg566 in wild-type STAT5b favors tight binding of catechol bisphosphates, while Trp566 in wild-type STAT5a does not. Amino acid 566 also determines the affinity for a tyrosine-phosphorylated peptide derived from the EPO receptor for STAT5a and STAT5b, demonstrating the functional relevance of the STAT5 linker domain for the adjacent SH2 domain. These results provide the first demonstration that a residue in the linker domain can determine the affinity of nonpeptidic small-molecule inhibitors for the SH2 domain of STAT proteins. We propose targeting the interface between the SH2 domain and linker domain as a novel design approach for the development of potent and selective STAT inhibitors. In addition, our data suggest that the linker domain could contribute to the enigmatically divergent biological functions of the two STAT5 proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30686667,

title = {Structural Model of Ghrelin Bound to its G Protein-Coupled Receptor},

author = {Brian Joseph Bender and Gerrit Vortmeier and Stefan Ernicke and Mathias Bosse and Anette Kaiser and Sylvia Els-Heindl and Ulrike Krug and Annette Beck-Sickinger and Jens Meiler and Daniel Huster},

doi = {10.1016/j.str.2018.12.004},

issn = {1878-4186},

year  = {2019},

date = {2019-03-01},

journal = {Structure},

volume = {27},

number = {3},

pages = {537--544.e4},

abstract = {The peptide ghrelin targets the growth hormone secretagogue receptor 1a (GHSR) to signal changes in cell metabolism and is a sought-after therapeutic target, although no structure is known to date. To investigate the structural basis of ghrelin binding to GHSR, we used solid-state nuclear magnetic resonance (NMR) spectroscopy, site-directed mutagenesis, and Rosetta modeling. The use of saturation transfer difference NMR identified key residues in the peptide for receptor binding beyond the known motif. This information combined with assignment of the secondary structure of ghrelin in its receptor-bound state was incorporated into Rosetta using an approach that accounts for flexible binding partners. The NMR data and models revealed an extended binding surface that was confirmed via mutagenesis. Our results agree with a growing evidence of peptides interacting via two sites at G protein-coupled receptors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30737217,

title = {Correction: An Acquired   Gatekeeper Mutation Induces Resistance to Neratinib in a Patient with HER2 Mutant-Driven Breast Cancer},

author = {Ariella B Hanker and Monica Red Brewer and Jonathan H Sheehan and James P Koch and Gregory R Sliwoski and Rebecca Nagy and Richard Lanman and Michael F Berger and David M Hyman and David B Solit and Jie He and Vincent Miller and Richard E Cutler and Alshad S Lalani and Darren Cross and Christine M Lovly and Jens Meiler and Carlos L Arteaga},

doi = {10.1158/2159-8290.CD-18-1515},

issn = {2159-8290},

year  = {2019},

date = {2019-02-01},

journal = {Cancer Discov},

volume = {9},

number = {2},

pages = {303},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30770491,

title = {Correction:  C2 Domain Deletions Hyperactivate Phosphoinositide 3-kinase (PI3K), Generate Oncogene Dependence, and Are Exquisitely Sensitive to PI3Kα Inhibitors},

author = {Sarah Croessmann and Jonathan H Sheehan and Kyung-Min Lee and Gregory Sliwoski and Jie He and Rebecca Nagy and David Riddle and Ingrid A Mayer and Justin M Balko and Richard Lanman and Vincent A Miller and Lewis C Cantley and Jens Meiler and Carlos L Arteaga},

doi = {10.1158/1078-0432.CCR-18-4269},

issn = {1557-3265},

year  = {2019},

date = {2019-02-01},

journal = {Clin Cancer Res},

volume = {25},

number = {4},

pages = {1432},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30707580,

title = {BCL::MolAlign: Three-Dimensional Small Molecule Alignment for Pharmacophore Mapping},

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

doi = {10.1021/acs.jcim.9b00020},

issn = {1549-960X},

year  = {2019},

date = {2019-02-01},

journal = {J Chem Inf Model},

volume = {59},

number = {2},

pages = {689--701},

abstract = {Small molecule flexible alignment is a critical component of both ligand- and structure-based methods in computer-aided drug discovery. Despite its importance, the availability of high-quality flexible alignment software packages is limited. Here, we present BCL::MolAlign, a freely available property-based molecular alignment program. BCL::MolAlign accommodates ligand flexibility through a combination of pregenerated conformers and on-the-fly bond rotation. BCL::MolAlign converges on alignment poses by sampling the relative orientations of mutually matching atom pairs between molecules through Monte Carlo Metropolis sampling. Across six diverse ligand data sets, BCL::MolAlign flexible alignment outperforms MOE, ROCS, and FLEXS in recovering native ligand binding poses. Moreover, the BCL::MolAlign alignment score is more predictive of ligand activity than maximum common substructure similarity across 10 data sets. Finally, on a recently published benchmark set of 20 high quality congeneric ligand-protein complexes, BCL::MolAlign is able to recover a larger fraction of native binding poses than maximum common substructure-based alignment and RosettaLigand. BCL::MolAlign can be obtained as part of the Biology and Chemistry Library (BCL) software package freely with an academic license or can be accessed via Web server at http://meilerlab.org/index.php/servers/molalign .},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30664251,

title = {Insight on mutation-induced resistance to anaplastic lymphoma kinase inhibitor ceritinib from molecular dynamics simulations},

author = {Mu-Yang He and Wei-Kang Li and Jens Meiler and Qing-Chuan Zheng and Hong-Xing Zhang},

doi = {10.1002/bip.23257},

issn = {1097-0282},

year  = {2019},

date = {2019-02-01},

journal = {Biopolymers},

volume = {110},

number = {2},

pages = {e23257},

abstract = {Ceritinib, an advanced anaplastic lymphoma kinase (ALK) next-generation inhibitor, has been proved excellent antitumor activity in the treatment of ALK-associated cancers. However, the accumulation of acquired resistance mutations compromise the therapeutic efficacy of ceritinib. Despite abundant mutagenesis data, the structural determinants for reduced ceritinib binding in mutants remains elusive. Focusing on the G1123S and F1174C mutations, we applied molecular dynamics (MD) simulations to study possible reasons for drug resistance caused by these mutations. The MD simulations predict that the studied mutations allosterically impact the configurations of the ATP-binding pocket. An important hydrophobic cluster is identified that connects P-loop and the αC-helix, which has effects on stabilizing the conformation of ATP-binding pocket. It is suggested, in this study, that the G1123S and F1174C mutations can induce the conformational change of P-loop thereby causing the reduced ceritinib affinity and causing drug resistance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30755521,

title = {Structural, functional, and behavioral insights of dopamine dysfunction revealed by a deletion in },

author = {Nicholas G Campbell and Aparna Shekar and Jenny I Aguilar and Dungeng Peng and Vikas Navratna and Dongxue Yang and Alexander N Morley and Amanda M Duran and Greta Galli and Brian O'Grady and Ramnarayan Ramachandran and James S Sutcliffe and Harald H Sitte and Kevin Erreger and Jens Meiler and Thomas Stockner and Leon M Bellan and Heinrich J G Matthies and Eric Gouaux and Hassane S Mchaourab and Aurelio Galli},

doi = {10.1073/pnas.1816247116},

issn = {1091-6490},

year  = {2019},

date = {2019-02-01},

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

volume = {116},

number = {9},

pages = {3853--3862},

abstract = {The human dopamine (DA) transporter (hDAT) mediates clearance of DA. Genetic variants in hDAT have been associated with DA dysfunction, a complication associated with several brain disorders, including autism spectrum disorder (ASD). Here, we investigated the structural and behavioral bases of an ASD-associated in-frame deletion in hDAT at N336 (∆N336). We uncovered that the deletion promoted a previously unobserved conformation of the intracellular gate of the transporter, likely representing the rate-limiting step of the transport process. It is defined by a "half-open and inward-facing" state (HOIF) of the intracellular gate that is stabilized by a network of interactions conserved phylogenetically, as we demonstrated in hDAT by Rosetta molecular modeling and fine-grained simulations, as well as in its bacterial homolog leucine transporter by electron paramagnetic resonance analysis and X-ray crystallography. The stabilization of the HOIF state is associated both with DA dysfunctions demonstrated in isolated brains of  expressing hDAT ∆N336 and with abnormal behaviors observed at high-time resolution. These flies display increased fear, impaired social interactions, and locomotion traits we associate with DA dysfunction and the HOIF state. Together, our results describe how a genetic variation causes DA dysfunction and abnormal behaviors by stabilizing a HOIF state of the transporter.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30616825,

title = {Modeling the complete chemokine-receptor interaction},

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

doi = {10.1016/bs.mcb.2018.09.005},

issn = {0091-679X},

year  = {2019},

date = {2019-01-01},

journal = {Methods Cell Biol},

volume = {149},

pages = {289--314},

abstract = {Chemokines are soluble, secreted proteins that induce chemotaxis of leukocytes and other cells. Migratory cells can sense the chemokine concentration gradient following chemokine binding and activation of chemokine receptors, a subset of the G protein-coupled receptor (GPCR) superfamily. Chemokine receptor signaling plays a central role in cell migration during inflammatory responses as well as in cancer and other diseases. Given their important role in mediating essential pathologic and physiologic processes, chemokines and their receptors are attractive targets for therapeutic development. A better understanding of the molecular basis of chemokine-GPCR interactions will aid in the understanding of the mechanistic basis for chemokine function in disease-related processes, as well as aid in the design of new therapeutics. High resolution protein structures are critical for determining these mechanisms and investigating the interactions between approximately 50 chemokines and 20 chemokine receptors. Currently, three unique structures of chemokine-GPCR complexes have been determined and have greatly broadened our knowledge of this large protein-protein interaction. While these structures represent only a small fraction of clinically relevant chemokines and receptors, they can be exploited as scaffolds for homology modeling to understand the chemokine-GPCR interactions. This chapter presents a specialized methodology to construct and validate models of chemokine-GPCR complexes using the Rosetta software suite.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30537820,

title = {Contribution of Cotranslational Folding Defects to Membrane Protein Homeostasis},

author = {Francis J Roushar and Timothy C Gruenhagen and Wesley D Penn and Bian Li and Jens Meiler and Beata Jastrzebska and Jonathan P Schlebach},

doi = {10.1021/jacs.8b08243},

issn = {1520-5126},

year  = {2019},

date = {2019-01-01},

journal = {J Am Chem Soc},

volume = {141},

number = {1},

pages = {204--215},

abstract = {Membrane proteins are prone to misfolding and degradation within the cell, yet the nature of the conformational defects involved in this process remain poorly understood. The earliest stages of membrane protein folding are mediated by the Sec61 translocon, a molecular machine that facilitates the lateral partitioning of the polypeptide into the membrane. Proper membrane integration is an essential prerequisite for folding of the nascent chain. However, the marginal energetic drivers of this reaction suggest the translocon may operate with modest fidelity. In this work, we employed biophysical modeling in conjunction with quantitative biochemical measurements in order to evaluate the extent to which cotranslational folding defects influence membrane protein homeostasis. Protein engineering was employed to selectively perturb the topological energetics of human rhodopsin, and the expression and cellular trafficking of engineered variants were quantitatively compared. Our results reveal clear relationships between topological energetics and the efficiency of rhodopsin biogenesis, which appears to be limited by the propensity of a polar transmembrane domain to achieve its correct topological orientation. Though the polarity of this segment is functionally constrained, we find that its topology can be stabilized in a manner that enhances biogenesis without compromising the functional properties of rhodopsin. Furthermore, sequence alignments reveal this topological instability has been conserved throughout the course of evolution. These results suggest that topological defects significantly contribute to the inefficiency of membrane protein folding in the cell. Additionally, our findings suggest that the marginal stability of rhodopsin may represent an evolved trait.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31518351,

title = {Upgraded molecular models of the human KCNQ1 potassium channel},

author = {Georg Kuenze and Amanda M Duran and Hope Woods and Kathryn R Brewer and Eli Fritz McDonald and Carlos G Vanoye and Alfred L George and Charles R Sanders and Jens Meiler},

doi = {10.1371/journal.pone.0220415},

issn = {1932-6203},

year  = {2019},

date = {2019-01-01},

journal = {PLoS One},

volume = {14},

number = {9},

pages = {e0220415},

abstract = {The voltage-gated potassium channel KCNQ1 (KV7.1) assembles with the KCNE1 accessory protein to generate the slow delayed rectifier current, IKS, which is critical for membrane repolarization as part of the cardiac action potential. Loss-of-function (LOF) mutations in KCNQ1 are the most common cause of congenital long QT syndrome (LQTS), type 1 LQTS, an inherited genetic predisposition to cardiac arrhythmia and sudden cardiac death. A detailed structural understanding of KCNQ1 is needed to elucidate the molecular basis for KCNQ1 LOF in disease and to enable structure-guided design of new anti-arrhythmic drugs. In this work, advanced structural models of human KCNQ1 in the resting/closed and activated/open states were developed by Rosetta homology modeling guided by newly available experimentally-based templates: X. leavis KCNQ1 and various resting voltage sensor structures. Using molecular dynamics (MD) simulations, the capacity of the models to describe experimentally established channel properties including state-dependent voltage sensor gating charge interactions and pore conformations, PIP2 binding sites, and voltage sensor-pore domain interactions were validated. Rosetta energy calculations were applied to assess the utility of each model in interpreting mutation-evoked KCNQ1 dysfunction by predicting the change in protein thermodynamic stability for 50 experimentally characterized KCNQ1 variants with mutations located in the voltage-sensing domain. Energetic destabilization was successfully predicted for folding-defective KCNQ1 LOF mutants whereas wild type-like mutants exhibited no significant energetic frustrations, which supports growing evidence that mutation-induced protein destabilization is an especially common cause of KCNQ1 dysfunction. The new KCNQ1 Rosetta models provide helpful tools in the study of the structural basis for KCNQ1 function and can be used to generate hypotheses to explain KCNQ1 dysfunction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31303974,

title = {Interfaces Between Alpha-helical Integral Membrane Proteins: Characterization, Prediction, and Docking},

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

doi = {10.1016/j.csbj.2019.05.005},

issn = {2001-0370},

year  = {2019},

date = {2019-01-01},

journal = {Comput Struct Biotechnol J},

volume = {17},

pages = {699--711},

abstract = {Protein-protein interaction (PPI) is an essential mechanism by which proteins perform their biological functions. For globular proteins, the molecular characteristics of such interactions have been well analyzed, and many computational tools are available for predicting PPI sites and constructing structural models of the complex. In contrast, little is known about the molecular features of the interaction between integral membrane proteins (IMPs) and few methods exist for constructing structural models of their complexes. Here, we analyze the interfaces from a non-redundant set of complexes of α-helical IMPs whose structures have been determined to a high resolution. We find that the interface is not significantly different from the rest of the surface in terms of average hydrophobicity. However, the interface is significantly better conserved and, on average, inter-subunit contacting residue pairs correlate more strongly than non-contacting pairs, especially in obligate complexes. We also develop a neural network-based method, with an area under the receiver operating characteristic curve of 0.75 and a Pearson correlation coefficient of 0.70, for predicting interface residues and their weighted contact numbers (WCNs). We further show that predicted interface residues and their WCNs can be used as restraints to reconstruct the structure α-helical IMP dimers through docking for fourteen out of a benchmark set of sixteen complexes. The RMSD100 values of the best-docked ligand subunit to its native structure are <2.5 Å for these fourteen cases. The structural analysis conducted in this work provides molecular details about the interface between α-helical IMPs and the WCN restraints represent an efficient means to score α-helical IMP docking candidates.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30642961,

title = {Multistate design of influenza antibodies improves affinity and breadth against seasonal viruses},

author = {Alexander M Sevy and Nicholas C Wu and Iuliia M Gilchuk and Erica H Parrish and Sebastian Burger and Dina Yousif and Marcus B M Nagel and Kevin L Schey and Ian A Wilson and James E Crowe and Jens Meiler},

doi = {10.1073/pnas.1806004116},

issn = {1091-6490},

year  = {2019},

date = {2019-01-01},

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

volume = {116},

number = {5},

pages = {1597--1602},

abstract = {Influenza is a yearly threat to global public health. Rapid changes in influenza surface proteins resulting from antigenic drift and shift events make it difficult to readily identify antibodies with broadly neutralizing activity against different influenza subtypes with high frequency, specifically antibodies targeting the receptor binding domain (RBD) on influenza HA protein. We developed an optimized computational design method that is able to optimize an antibody for recognition of large panels of antigens. To demonstrate the utility of this multistate design method, we used it to redesign an antiinfluenza antibody against a large panel of more than 500 seasonal HA antigens of the H1 subtype. As a proof of concept, we tested this method on a variety of known antiinfluenza antibodies and identified those that could be improved computationally. We generated redesigned variants of antibody C05 to the HA RBD and experimentally characterized variants that exhibited improved breadth and affinity against our panel. C05 mutants exhibited improved affinity for three of the subtypes used in design by stabilizing the CDRH3 loop and creating favorable electrostatic interactions with the antigen. These mutants possess increased breadth and affinity of binding while maintaining high-affinity binding to existing targets, surpassing a major limitation up to this point.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30828412,

title = {Protein structure aids predicting functional perturbation of missense variants in  and },

author = {Brett M Kroncke and Jeffrey Mendenhall and Derek K Smith and Charles R Sanders and John A Capra and Alfred L George and Jeffrey D Blume and Jens Meiler and Dan M Roden},

doi = {10.1016/j.csbj.2019.01.008},

issn = {2001-0370},

year  = {2019},

date = {2019-01-01},

journal = {Comput Struct Biotechnol J},

volume = {17},

pages = {206--214},

abstract = {Rare variants in the cardiac potassium channel K7.1 () and sodium channel Na1.5 () are implicated in genetic disorders of heart rhythm, including congenital long QT and Brugada syndromes (LQTS, BrS), but also occur in reference populations. We previously reported two sets of Na1.5 ( = 356) and K7.1 ( = 144) variants with in vitro characterized channel currents gathered from the literature. Here we investigated the ability to predict commonly reported Na1.5 and K7.1 variant functional perturbations by leveraging diverse features including variant classifiers PROVEAN, PolyPhen-2, and SIFT; evolutionary rate and BLAST position specific scoring matrices (PSSM); and structure-based features including "functional densities" which is a measure of the density of pathogenic variants near the residue of interest. Structure-based functional densities were the most significant features for predicting Na1.5 peak current (adj. R = 0.27) and K7.1 + KCNE1 half-maximal voltage of activation (adj. R = 0.29). Additionally, use of structure-based functional density values improves loss-of-function classification of  variants with an ROC-AUC of 0.78 compared with other predictive classifiers (AUC = 0.69; two-sided DeLong test  = .01). These results suggest structural data can inform predictions of the effect of uncharacterized  and  variants to provide a deeper understanding of their burden on carriers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30571187,

title = {High-Throughput Functional Evaluation of KCNQ1 Decrypts Variants of Unknown Significance},

author = {Carlos G Vanoye and Reshma R Desai and Katarina L Fabre and Shannon L Gallagher and Franck Potet and Jean-Marc DeKeyser and Daniela Macaya and Jens Meiler and Charles R Sanders and Alfred L George},

doi = {10.1161/CIRCGEN.118.002345},

issn = {2574-8300},

year  = {2018},

date = {2018-11-01},

journal = {Circ Genom Precis Med},

volume = {11},

number = {11},

pages = {e002345},

abstract = {BACKGROUND: The explosive growth in known human gene variation presents enormous challenges to current approaches for variant classification that have implications for diagnosis and treatment of many genetic diseases. For disorders caused by mutations in cardiac ion channels as in congenital arrhythmia syndromes, in vitro electrophysiological evidence has high value in discriminating pathogenic from benign variants, but these data are often lacking because assays are cost, time, and labor intensive.nnMETHODS: We implemented a strategy for performing high-throughput functional evaluations of ion channel variants that repurposed an automated electrophysiological recording platform developed previously for drug discovery.nnRESULTS: We demonstrated the success of this approach by evaluating 78 variants in KCNQ1, a major gene involved in genetic disorders of cardiac arrhythmia susceptibility. We benchmarked our results with traditional electrophysiological approaches and observed a high level of concordance. This strategy also enabled studies of dominant-negative behavior of variants exhibiting severe loss-of-function. Overall, our results provided functional data useful for reclassifying >65% of the studied KCNQ1 variants.nnCONCLUSIONS: Our results illustrate an efficient and high-throughput paradigm linking genotype to function for a human cardiac ion channel that will enable data-driven classification of large numbers of variants and create new opportunities for precision medicine.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29552726,

title = {α- and α-Adrenoceptors as Potential Targets for Dopamine and Dopamine Receptor Ligands},

author = {Marta Sánchez-Soto and Verònica Casadó-Anguera and Hideaki Yano and Brian Joseph Bender and Ning-Sheng Cai and Estefanía Moreno and Enric I Canela and Antoni Cortés and Jens Meiler and Vicent Casadó and Sergi Ferré},

doi = {10.1007/s12035-018-1004-1},

issn = {1559-1182},

year  = {2018},

date = {2018-11-01},

journal = {Mol Neurobiol},

volume = {55},

number = {11},

pages = {8438--8454},

abstract = {The poor norepinephrine innervation and high density of Gi/o-coupled α- and α-adrenoceptors in the striatum and the dense striatal dopamine innervation have prompted the possibility that dopamine could be an effective adrenoceptor ligand. Nevertheless, the reported adrenoceptor agonistic properties of dopamine are still inconclusive. In this study, we analyzed the binding of norepinephrine, dopamine, and several compounds reported as selective dopamine D-like receptor ligands, such as the D receptor agonist 7-OH-PIPAT and the D receptor agonist RO-105824, to α-adrenoceptors in cortical and striatal tissue, which express α-adrenoceptors and both α- and α-adrenoceptors, respectively. The affinity of dopamine for α-adrenoceptors was found to be similar to that for D-like and D-like receptors. Moreover, the exogenous dopamine receptor ligands also showed high affinity for α- and α-adrenoceptors. Their ability to activate Gi/o proteins through α- and α-adrenoceptors was also analyzed in transfected cells with bioluminescent resonance energy transfer techniques. The relative ligand potencies and efficacies were dependent on the Gi/o protein subtype. Furthermore, dopamine binding to α-adrenoceptors was functional, inducing changes in dynamic mass redistribution, adenylyl cyclase activity, and ERK1/2 phosphorylation. Binding events were further studied with computer modeling of ligand docking. Docking of dopamine at α- and α-adrenoceptors was nearly identical to its binding to the crystallized D receptor. Therefore, we provide conclusive evidence that α- and α-adrenoceptors are functional receptors for norepinephrine, dopamine, and other previously assumed selective D-like receptor ligands, which calls for revisiting previous studies with those ligands.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29895592,

title = {Discovery, Characterization, and Effects on Renal Fluid and Electrolyte Excretion of the Kir4.1 Potassium Channel Pore Blocker, VU0134992},

author = {Sujay V Kharade and Haruto Kurata and Aaron M Bender and Anna L Blobaum and Eric E Figueroa and Amanda Duran and Meghan Kramer and Emily Days and Paige Vinson and Daniel Flores and Lisa M Satlin and Jens Meiler and C David Weaver and Craig W Lindsley and Corey R Hopkins and Jerod S Denton},

doi = {10.1124/mol.118.112359},

issn = {1521-0111},

year  = {2018},

date = {2018-08-01},

journal = {Mol Pharmacol},

volume = {94},

number = {2},

pages = {926--937},

abstract = {The inward rectifier potassium (Kir) channel Kir4.1 () carries out important physiologic roles in epithelial cells of the kidney, astrocytes in the central nervous system, and stria vascularis of the inner ear. Loss-of-function mutations in  lead to EAST/SeSAME syndrome, which is characterized by epilepsy, ataxia, renal salt wasting, and sensorineural deafness. Although genetic approaches have been indispensable for establishing the importance of Kir4.1 in the normal function of these tissues, the availability of pharmacological tools for acutely manipulating the activity of Kir4.1 in genetically normal animals has been lacking. We therefore carried out a high-throughput screen of 76,575 compounds from the Vanderbilt Institute of Chemical Biology library for small-molecule modulators of Kir4.1. The most potent inhibitor identified was 2-(2-bromo-4-isopropylphenoxy)--(2,2,6,6-tetramethylpiperidin-4-yl)acetamide (VU0134992). In whole-cell patch-clamp electrophysiology experiments, VU0134992 inhibits Kir4.1 with an IC value of 0.97 M and is 9-fold selective for homomeric Kir4.1 over Kir4.1/5.1 concatemeric channels (IC = 9 M) at -120 mV. In thallium (Tl) flux assays, VU0134992 is greater than 30-fold selective for Kir4.1 over Kir1.1, Kir2.1, and Kir2.2; is weakly active toward Kir2.3, Kir6.2/SUR1, and Kir7.1; and is equally active toward Kir3.1/3.2, Kir3.1/3.4, and Kir4.2. This potency and selectivity profile is superior to Kir4.1 inhibitors amitriptyline, nortriptyline, and fluoxetine. Medicinal chemistry identified components of VU0134992 that are critical for inhibiting Kir4.1. Patch-clamp electrophysiology, molecular modeling, and site-directed mutagenesis identified pore-lining glutamate 158 and isoleucine 159 as critical residues for block of the channel. VU0134992 displayed a large free unbound fraction () in rat plasma ( = 0.213). Consistent with the known role of Kir4.1 in renal function, oral dosing of VU0134992 led to a dose-dependent diuresis, natriuresis, and kaliuresis in rats. Thus, VU0134992 represents the first in vivo active tool compound for probing the therapeutic potential of Kir4.1 as a novel diuretic target for the treatment of hypertension.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29771498,

title = {Structure and Function of the Transmembrane Domain of NsaS, an Antibiotic Sensing Histidine Kinase in Staphylococcus aureus},

author = {Manasi P Bhate and Thomas Lemmin and Georg Kuenze and Bruk Mensa and Soumya Ganguly and Jason M Peters and Nathan Schmidt and Jeffrey G Pelton and Carol A Gross and Jens Meiler and William F DeGrado},

doi = {10.1021/jacs.7b09670},

issn = {1520-5126},

year  = {2018},

date = {2018-06-01},

journal = {J Am Chem Soc},

volume = {140},

number = {24},

pages = {7471--7485},

abstract = {NsaS is one of four intramembrane histidine kinases (HKs) in Staphylococcus aureus that mediate the pathogen's response to membrane active antimicrobials and human innate immunity. We describe the first integrative structural study of NsaS using a combination of solution state NMR spectroscopy, chemical-cross-linking, molecular modeling and dynamics. Three key structural features emerge: First, NsaS has a short N-terminal amphiphilic helix that anchors its transmembrane (TM) bundle into the inner leaflet of the membrane such that it might sense neighboring proteins or membrane deformations. Second, the transmembrane domain of NsaS is a 4-helix bundle with significant dynamics and structural deformations at the membrane interface. Third, the intracellular linker connecting the TM domain to the cytoplasmic catalytic domains of NsaS is a marginally stable helical dimer, with one state likely to be a coiled-coil. Data from chemical shifts, heteronuclear NOE, H/D exchange measurements and molecular modeling suggest that this linker might adopt different conformations during antibiotic induced signaling.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29641200,

title = {Holistic Approach to Partial Covalent Interactions in Protein Structure Prediction and Design with Rosetta},

author = {Steven A Combs and Benjamin K Mueller and Jens Meiler},

doi = {10.1021/acs.jcim.7b00398},

issn = {1549-960X},

year  = {2018},

date = {2018-05-01},

journal = {J Chem Inf Model},

volume = {58},

number = {5},

pages = {1021--1036},

abstract = {Partial covalent interactions (PCIs) in proteins, which include hydrogen bonds, salt bridges, cation-π, and π-π interactions, contribute to thermodynamic stability and facilitate interactions with other biomolecules. Several score functions have been developed within the Rosetta protein modeling framework that identify and evaluate these PCIs through analyzing the geometry between participating atoms. However, we hypothesize that PCIs can be unified through a simplified electron orbital representation. To test this hypothesis, we have introduced orbital based chemical descriptors for PCIs into Rosetta, called the PCI score function. Optimal geometries for the PCIs are derived from a statistical analysis of high-quality protein structures obtained from the Protein Data Bank (PDB), and the relative orientation of electron deficient hydrogen atoms and electron-rich lone pair or π orbitals are evaluated. We demonstrate that nativelike geometries of hydrogen bonds, salt bridges, cation-π, and π-π interactions are recapitulated during minimization of protein conformation. The packing density of tested protein structures increased from the standard score function from 0.62 to 0.64, closer to the native value of 0.70. Overall, rotamer recovery improved when using the PCI score function (75%) as compared to the standard Rosetta score function (74%). The PCI score function represents an improvement over the standard Rosetta score function for protein model scoring; in addition, it provides a platform for future directions in the analysis of small molecule to protein interactions, which depend on partial covalent interactions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29732444,

title = {RosettaLigandEnsemble: A Small-Molecule Ensemble-Driven Docking Approach},

author = {Darwin Yu Fu and Jens Meiler},

doi = {10.1021/acsomega.7b02059},

issn = {2470-1343},

year  = {2018},

date = {2018-04-01},

journal = {ACS Omega},

volume = {3},

number = {4},

pages = {3655--3664},

abstract = {RosettaLigand is a protein-small-molecule (ligand) docking software capable of predicting binding poses and is used for virtual screening of medium-sized ligand libraries. Structurally similar small molecules are generally found to bind in the same pose to one binding pocket, despite some prominent exceptions. To make use of this information, we have developed RosettaLigandEnsemble (RLE). RLE docks a superimposed ensemble of congeneric ligands simultaneously. The program determines a well-scoring overall pose for this superimposed ensemble before independently optimizing individual protein-small-molecule interfaces. In a cross-docking benchmark of 89 protein-small-molecule co-crystal structures across 20 biological systems, we found that RLE improved sampling efficiency in 62 cases, with an average change of 18%. In addition, RLE generated more consistent docking results within a congeneric series and was capable of rescuing the unsuccessful docking of individual ligands, identifying a nativelike top-scoring model in 10 additional cases. The improvement in RLE is driven by a balance between having a sizable common chemical scaffold and meaningful modifications to distal groups. The new ensemble docking algorithm will work well in conjunction with medicinal chemistry structure-activity relationship (SAR) studies to more accurately recapitulate protein-ligand interfaces. We also tested whether optimizing the rank correlation of RLE-binding scores to SAR data in the refinement step helps the high-resolution positioning of the ligand. However, no significant improvement was observed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29526436,

title = {Integrated Structural Biology for α-Helical Membrane Protein Structure Determination},

author = {Yan Xia and Axel W Fischer and Pedro Teixeira and Brian Weiner and Jens Meiler},

doi = {10.1016/j.str.2018.02.006},

issn = {1878-4186},

year  = {2018},

date = {2018-04-01},

journal = {Structure},

volume = {26},

number = {4},

pages = {657--666.e2},

abstract = {While great progress has been made, only 10% of the nearly 1,000 integral, α-helical, multi-span membrane protein families are represented by at least one experimentally determined structure in the PDB. Previously, we developed the algorithm BCL::MP-Fold, which samples the large conformational space of membrane proteins de novo by assembling predicted secondary structure elements guided by knowledge-based potentials. Here, we present a case study of rhodopsin fold determination by integrating sparse and/or low-resolution restraints from multiple experimental techniques including electron microscopy, electron paramagnetic resonance spectroscopy, and nuclear magnetic resonance spectroscopy. Simultaneous incorporation of orthogonal experimental restraints not only significantly improved the sampling accuracy but also allowed identification of the correct fold, which is demonstrated by a protein size-normalized transmembrane root-mean-square deviation as low as 1.2 Å. The protocol developed in this case study can be used for the determination of unknown membrane protein folds when limited experimental restraints are available.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29670288,

title = {Structural basis of ligand binding modes at the neuropeptide Y Y receptor},

author = {Zhenlin Yang and Shuo Han and Max Keller and Anette Kaiser and Brian J Bender and Mathias Bosse and Kerstin Burkert and Lisa M Kögler and David Wifling and Guenther Bernhardt and Nicole Plank and Timo Littmann and Peter Schmidt and Cuiying Yi and Beibei Li and Sheng Ye and Rongguang Zhang and Bo Xu and Dan Larhammar and Raymond C Stevens and Daniel Huster and Jens Meiler and Qiang Zhao and Annette G Beck-Sickinger and Armin Buschauer and Beili Wu},

doi = {10.1038/s41586-018-0046-x},

issn = {1476-4687},

year  = {2018},

date = {2018-04-01},

journal = {Nature},

volume = {556},

number = {7702},

pages = {520--524},

abstract = {Neuropeptide Y (NPY) receptors belong to the G-protein-coupled receptor superfamily and have important roles in food intake, anxiety and cancer biology  . The NPY-Y receptor system has emerged as one of the most complex networks with three peptide ligands (NPY, peptide YY and pancreatic polypeptide) binding to four receptors in most mammals, namely the Y, Y, Y and Y receptors, with different affinity and selectivity  . NPY is the most powerful stimulant of food intake and this effect is primarily mediated by the Y receptor (YR)  . A number of peptides and small-molecule compounds have been characterized as YR antagonists and have shown clinical potential in the treatment of obesity  , tumour  and bone loss  . However, their clinical usage has been hampered by low potency and selectivity, poor brain penetration ability or lack of oral bioavailability  . Here we report crystal structures of the human YR bound to the two selective antagonists UR-MK299 and BMS-193885 at 2.7 and 3.0 Å resolution, respectively. The structures combined with mutagenesis studies reveal the binding modes of YR to several structurally diverse antagonists and the determinants of ligand selectivity. The YR structure and molecular docking of the endogenous agonist NPY, together with nuclear magnetic resonance, photo-crosslinking and functional studies, provide insights into the binding behaviour of the agonist and for the first time, to our knowledge, determine the interaction of its N terminus with the receptor. These insights into YR can enable structure-based drug discovery that targets NPY receptors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29334381,

title = {The molecular basis of subtype selectivity of human kinin G-protein-coupled receptors},

author = {Lisa Joedicke and Jiafei Mao and Georg Kuenze and Christoph Reinhart and Tejaswi Kalavacherla and Hendrik R A Jonker and Christian Richter and Harald Schwalbe and Jens Meiler and Julia Preu and Hartmut Michel and Clemens Glaubitz},

doi = {10.1038/nchembio.2551},

issn = {1552-4469},

year  = {2018},

date = {2018-03-01},

journal = {Nat Chem Biol},

volume = {14},

number = {3},

pages = {284--290},

abstract = {G-protein-coupled receptors (GPCRs) are the most important signal transducers in higher eukaryotes. Despite considerable progress, the molecular basis of subtype-specific ligand selectivity, especially for peptide receptors, remains unknown. Here, by integrating DNP-enhanced solid-state NMR spectroscopy with advanced molecular modeling and docking, the mechanism of the subtype selectivity of human bradykinin receptors for their peptide agonists has been resolved. The conserved middle segments of the bound peptides show distinct conformations that result in different presentations of their N and C termini toward their receptors. Analysis of the peptide-receptor interfaces reveals that the charged N-terminal residues of the peptides are mainly selected through electrostatic interactions, whereas the C-terminal segments are recognized via both conformations and interactions. The detailed molecular picture obtained by this approach opens a new gateway for exploring the complex conformational and chemical space of peptides and peptide analogs for designing GPCR subtype-selective biochemical tools and drugs.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29532034,

title = {Mechanisms of KCNQ1 channel dysfunction in long QT syndrome involving voltage sensor domain mutations},

author = {Hui Huang and Georg Kuenze and Jarrod A Smith and Keenan C Taylor and Amanda M Duran and Arina Hadziselimovic and Jens Meiler and Carlos G Vanoye and Alfred L George and Charles R Sanders},

doi = {10.1126/sciadv.aar2631},

issn = {2375-2548},

year  = {2018},

date = {2018-03-01},

journal = {Sci Adv},

volume = {4},

number = {3},

pages = {eaar2631},

abstract = {Mutations that induce loss of function (LOF) or dysfunction of the human KCNQ1 channel are responsible for susceptibility to a life-threatening heart rhythm disorder, the congenital long QT syndrome (LQTS). Hundreds of  mutations have been identified, but the molecular mechanisms responsible for impaired function are poorly understood. We investigated the impact of 51 KCNQ1 variants with mutations located within the voltage sensor domain (VSD), with an emphasis on elucidating effects on cell surface expression, protein folding, and structure. For each variant, the efficiency of trafficking to the plasma membrane, the impact of proteasome inhibition, and protein stability were assayed. The results of these experiments combined with channel functional data provided the basis for classifying each mutation into one of six mechanistic categories, highlighting heterogeneity in the mechanisms resulting in channel dysfunction or LOF. More than half of the KCNQ1 LOF mutations examined were seen to destabilize the structure of the VSD, generally accompanied by mistrafficking and degradation by the proteasome, an observation that underscores the growing appreciation that mutation-induced destabilization of membrane proteins may be a common human disease mechanism. Finally, we observed that five of the folding-defective LQTS mutant sites are located in the VSD S0 helix, where they interact with a number of other LOF mutation sites in other segments of the VSD. These observations reveal a critical role for the S0 helix as a central scaffold to help organize and stabilize the KCNQ1 VSD and, most likely, the corresponding domain of many other ion channels.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29455857,

title = {Comprehensive Analysis of Constraint on the Spatial Distribution of Missense Variants in Human Protein Structures},

author = {R Michael Sivley and Xiaoyi Dou and Jens Meiler and William S Bush and John A Capra},

doi = {10.1016/j.ajhg.2018.01.017},

issn = {1537-6605},

year  = {2018},

date = {2018-03-01},

journal = {Am J Hum Genet},

volume = {102},

number = {3},

pages = {415--426},

abstract = {The spatial distribution of genetic variation within proteins is shaped by evolutionary constraint and provides insight into the functional importance of protein regions and the potential pathogenicity of protein alterations. Here, we comprehensively evaluate the 3D spatial patterns of human germline and somatic variation in 6,604 experimentally derived protein structures and 33,144 computationally derived homology models covering 77% of all human proteins. Using a systematic approach, we quantify differences in the spatial distributions of neutral germline variants, disease-causing germline variants, and recurrent somatic variants. Neutral missense variants exhibit a general trend toward spatial dispersion, which is driven by constraint on core residues. In contrast, germline disease-causing variants are generally clustered in protein structures and form clusters more frequently than recurrent somatic variants identified from tumor sequencing. In total, we identify 215 proteins with significant spatial constraints on the distribution of disease-causing missense variants in experimentally derived protein structures, only 65 (30%) of which have been previously reported. This analysis identifies many clusters not detectable from sequence information alone; only 12% of proteins with significant clustering in 3D were identified from similar analyses of linear protein sequence. Furthermore, spatial analyses of mutations in homology-based structural models are highly correlated with those from experimentally derived structures, supporting the use of computationally derived models. Our approach highlights significant differences in the spatial constraints on different classes of mutations in protein structure and identifies regions of potential function within individual proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29284706,

title = { C2 Domain Deletions Hyperactivate Phosphoinositide 3-kinase (PI3K), Generate Oncogene Dependence, and Are Exquisitely Sensitive to PI3K Inhibitors},

author = {Sarah Croessmann and Jonathan H Sheehan and Kyung-Min Lee and Gregory Sliwoski and Jie He and Rebecca Nagy and David Riddle and Ingrid A Mayer and Justin M Balko and Richard Lanman and Vincent A Miller and Lewis C Cantley and Jens Meiler and Carlos L Arteaga},

doi = {10.1158/1078-0432.CCR-17-2141},

issn = {1557-3265},

year  = {2018},

date = {2018-03-01},

journal = {Clin Cancer Res},

volume = {24},

number = {6},

pages = {1426--1435},

abstract = { We describe herein a novel P447_L455 deletion in the C2 domain of  in a patient with an ER breast cancer with an excellent response to the PI3Kα inhibitor alpelisib. Although  deletions are relatively rare, a significant portion of deletions cluster within amino acids 446-460 of the C2 domain, suggesting these residues are critical for p110α function. A computational structural model of  in complex with the p85 regulatory subunit and MCF10A cells expressing  and  were used to understand the phenotype of C2 domain deletions. Computational modeling revealed specific favorable inter-residue contacts that would be lost as a result of the deletion, predicting a significant decrease in binding energy. Coimmunoprecipitation experiments showed reduced binding of the C2 deletion mutants with p85 compared with wild-type p110α. The MCF10A cells expressing  C2 deletions exhibited growth factor-independent growth, an invasive phenotype, and higher phosphorylation of AKT, ERK, and S6 compared with parental MCF10A cells. All these changes were ablated by alpelisib treatment. C2 domain deletions in  generate PI3K dependence and should be considered biomarkers of sensitivity to PI3K inhibitors. .},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29286651,

title = {Predictive Power of Different Types of Experimental Restraints in Small Molecule Docking: A Review},

author = {Darwin Y Fu and Jens Meiler},

doi = {10.1021/acs.jcim.7b00418},

issn = {1549-960X},

year  = {2018},

date = {2018-02-01},

journal = {J Chem Inf Model},

volume = {58},

number = {2},

pages = {225--233},

abstract = {Incorporating experimental restraints is a powerful method of increasing accuracy in computational protein small molecule docking simulations. Different algorithms integrate distinct forms of biochemical data during the docking and/or scoring stages. These so-called hybrid methods make use of receptor-based information such as nuclear magnetic resonance (NMR) restraints or small molecule-based information such as structure-activity relationships (SARs). A third class of methods directly interrogates contacts between the protein receptor and the small molecule. This work reviews the current state of using such restraints in docking simulations, evaluates their feasibility across broad systems, and identifies potential areas of algorithm development.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid28976219,

title = {Finding the needle in the haystack: towards solving the protein-folding problem computationally},

author = {Bian Li and Michaela Fooksa and Sten Heinze and Jens Meiler},

doi = {10.1080/10409238.2017.1380596},

issn = {1549-7798},

year  = {2018},

date = {2018-02-01},

journal = {Crit Rev Biochem Mol Biol},

volume = {53},

number = {1},

pages = {1--28},

abstract = {Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as "the protein folding problem," has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29451898,

title = {Integrating linear optimization with structural modeling to increase HIV neutralization breadth},

author = {Alexander M Sevy and Swetasudha Panda and James E Crowe and Jens Meiler and Yevgeniy Vorobeychik},

doi = {10.1371/journal.pcbi.1005999},

issn = {1553-7358},

year  = {2018},

date = {2018-02-01},

journal = {PLoS Comput Biol},

volume = {14},

number = {2},

pages = {e1005999},

abstract = {Computational protein design has been successful in modeling fixed backbone proteins in a single conformation. However, when modeling large ensembles of flexible proteins, current methods in protein design have been insufficient. Large barriers in the energy landscape are difficult to traverse while redesigning a protein sequence, and as a result current design methods only sample a fraction of available sequence space. We propose a new computational approach that combines traditional structure-based modeling using the Rosetta software suite with machine learning and integer linear programming to overcome limitations in the Rosetta sampling methods. We demonstrate the effectiveness of this method, which we call BROAD, by benchmarking the performance on increasing predicted breadth of anti-HIV antibodies. We use this novel method to increase predicted breadth of naturally-occurring antibody VRC23 against a panel of 180 divergent HIV viral strains and achieve 100% predicted binding against the panel. In addition, we compare the performance of this method to state-of-the-art multistate design in Rosetta and show that we can outperform the existing method significantly. We further demonstrate that sequences recovered by this method recover known binding motifs of broadly neutralizing anti-HIV antibodies. Finally, our approach is general and can be extended easily to other protein systems. Although our modeled antibodies were not tested in vitro, we predict that these variants would have greatly increased breadth compared to the wild-type antibody.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid29361909,

title = {Three-dimensional spatial analysis of missense variants in RTEL1 identifies pathogenic variants in patients with Familial Interstitial Pneumonia},

author = {R Michael Sivley and Jonathan H Sheehan and Jonathan A Kropski and Joy Cogan and Timothy S Blackwell and John A Phillips and William S Bush and Jens Meiler and John A Capra},

doi = {10.1186/s12859-018-2010-z},

issn = {1471-2105},

year  = {2018},

date = {2018-01-01},

journal = {BMC Bioinformatics},

volume = {19},

number = {1},

pages = {18},

abstract = {BACKGROUND: Next-generation sequencing of individuals with genetic diseases often detects candidate rare variants in numerous genes, but determining which are causal remains challenging. We hypothesized that the spatial distribution of missense variants in protein structures contains information about function and pathogenicity that can help prioritize variants of unknown significance (VUS) and elucidate the structural mechanisms leading to disease.nnRESULTS: To illustrate this approach in a clinical application, we analyzed 13 candidate missense variants in regulator of telomere elongation helicase 1 (RTEL1) identified in patients with Familial Interstitial Pneumonia (FIP). We curated pathogenic and neutral RTEL1 variants from the literature and public databases. We then used homology modeling to construct a 3D structural model of RTEL1 and mapped known variants into this structure. We next developed a pathogenicity prediction algorithm based on proximity to known disease causing and neutral variants and evaluated its performance with leave-one-out cross-validation. We further validated our predictions with segregation analyses, telomere lengths, and mutagenesis data from the homologous XPD protein. Our algorithm for classifying RTEL1 VUS based on spatial proximity to pathogenic and neutral variation accurately distinguished 7 known pathogenic from 29 neutral variants (ROC AUC = 0.85) in the N-terminal domains of RTEL1. Pathogenic proximity scores were also significantly correlated with effects on ATPase activity (Pearson r = -0.65, p = 0.0004) in XPD, a related helicase. Applying the algorithm to 13 VUS identified from sequencing of RTEL1 from patients predicted five out of six disease-segregating VUS to be pathogenic. We provide structural hypotheses regarding how these mutations may disrupt RTEL1 ATPase and helicase function.nnCONCLUSIONS: Spatial analysis of missense variation accurately classified candidate VUS in RTEL1 and suggests how such variants cause disease. Incorporating spatial proximity analyses into other pathogenicity prediction tools may improve accuracy for other genes and genetic diseases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}