Publications

@article{pmid23671563,

title = {Human rotavirus VP6-specific antibodies mediate intracellular neutralization by binding to a quaternary structure in the transcriptional pore},

author = {Mohammed S Aiyegbo and Gopal Sapparapu and Benjamin W Spiller and Ilyas M Eli and Dewight R Williams and Robert Kim and David E Lee and Tong Liu and Sheng Li and Virgil L Woods and David P Nannemann and Jens Meiler and Phoebe L Stewart and James E Crowe},

doi = {10.1371/journal.pone.0061101},

issn = {1932-6203},

year  = {2013},

date = {2013-01-01},

journal = {PLoS One},

volume = {8},

number = {5},

pages = {e61101},

abstract = {Several live attenuated rotavirus (RV) vaccines have been licensed, but the mechanisms of protective immunity are still poorly understood. The most frequent human B cell response is directed to the internal protein VP6 on the surface of double-layered particles, which is normally exposed only in the intracellular environment. Here, we show that the canonical VP6 antibodies secreted by humans bind to such particles and inhibit viral transcription. Polymeric IgA RV antibodies mediated an inhibitory effect against virus replication inside cells during IgA transcytosis. We defined the recognition site on VP6 as a quaternary epitope containing a high density of charged residues. RV human mAbs appear to bind to a negatively-charged patch on the surface of the Type I channel in the transcriptionally active particle, and they sterically block the channel. This unique mucosal mechanism of viral neutralization, which is not apparent from conventional immunoassays, may contribute significantly to human immunity to RV.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23093496,

title = {Identification of determinants required for agonistic and inverse agonistic ligand properties at the ADP receptor P2Y12},

author = {Philipp Schmidt and Lars Ritscher and Elizabeth N Dong and Thomas Hermsdorf and Maxi Cöster and Doreen Wittkopf and Jens Meiler and Torsten Schöneberg},

doi = {10.1124/mol.112.082198},

issn = {1521-0111},

year  = {2013},

date = {2013-01-01},

journal = {Mol Pharmacol},

volume = {83},

number = {1},

pages = {256--266},

abstract = {The ADP receptor P2Y(12) belongs to the superfamily of G protein-coupled receptors (GPCRs), and its activation triggers platelet aggregation. Therefore, potent antagonists, such as clopidogrel, are of high clinical relevance in prophylaxis and treatment of thromboembolic events. P2Y(12) displays an elevated basal activity in vitro, and as such, inverse agonists may be therapeutically beneficial compared with antagonists. Only a few inverse agonists of P2Y(12) have been described. To expand this limited chemical space and improve understanding of structural determinants of inverse agonist-receptor interaction, this study screened a purine compound library for lead structures using wild-type (WT) human P2Y(12) and 28 constitutively active mutants. Results showed that ATP and ATP derivatives are agonists at P2Y(12). The potency at P2Y(12) was 2-(methylthio)-ADP > 2-(methylthio)-ATP > ADP > ATP. Determinants required for agonistic ligand activity were identified. Molecular docking studies revealed a binding pocket for the ATP derivatives that is bordered by transmembrane helices 3, 5, 6, and 7 in human P2Y(12,) with Y(105), E(188), R(256), Y(259), and K(280) playing a particularly important role in ligand interaction. N-Methyl-anthraniloyl modification at the 3'-OH of the 2'-deoxyribose leads to ligands (mant-deoxy-ATP [dATP], mant-deoxy-ADP) with inverse agonist activity. Inverse agonist activity of mant-dATP was found at the WT human P2Y(12) and half of the constitutive active P2Y(12) mutants. This study showed that, in addition to ADP and ATP, other ATP derivatives are not only ligands of P2Y(12) but also agonists. Modification of the ribose within ATP can result in inverse activity of ATP-derived ligands.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23840735,

title = {Towards ligand docking including explicit interface water molecules},

author = {Gordon Lemmon and Jens Meiler},

doi = {10.1371/journal.pone.0067536},

issn = {1932-6203},

year  = {2013},

date = {2013-01-01},

journal = {PLoS One},

volume = {8},

number = {6},

pages = {e67536},

abstract = {Small molecule docking predicts the interaction of a small molecule ligand with a protein at atomic-detail accuracy including position and conformation the ligand but also conformational changes of the protein upon ligand binding. While successful in the majority of cases, docking algorithms including RosettaLigand fail in some cases to predict the correct protein/ligand complex structure. In this study we show that simultaneous docking of explicit interface water molecules greatly improves Rosetta's ability to distinguish correct from incorrect ligand poses. This result holds true for both protein-centric water docking wherein waters are located relative to the protein binding site and ligand-centric water docking wherein waters move with the ligand during docking. Protein-centric docking is used to model 99 HIV-1 protease/protease inhibitor structures. We find protease inhibitor placement improving at a ratio of 9:1 when one critical interface water molecule is included in the docking simulation. Ligand-centric docking is applied to 341 structures from the CSAR benchmark of diverse protein/ligand complexes [1]. Across this diverse dataset we see up to 56% recovery of failed docking studies, when waters are included in the docking simulation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23744289,

title = {Small-molecule ligand docking into comparative models with Rosetta},

author = {Steven A Combs and Samuel L Deluca and Stephanie H Deluca and Gordon H Lemmon and David P Nannemann and Elizabeth D Nguyen and Jordan R Willis and Jonathan H Sheehan and Jens Meiler},

doi = {10.1038/nprot.2013.074},

issn = {1750-2799},

year  = {2013},

date = {2013-01-01},

journal = {Nat Protoc},

volume = {8},

number = {7},

pages = {1277--1298},

abstract = {Structure-based drug design is frequently used to accelerate the development of small-molecule therapeutics. Although substantial progress has been made in X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, the availability of high-resolution structures is limited owing to the frequent inability to crystallize or obtain sufficient NMR restraints for large or flexible proteins. Computational methods can be used to both predict unknown protein structures and model ligand interactions when experimental data are unavailable. This paper describes a comprehensive and detailed protocol using the Rosetta modeling suite to dock small-molecule ligands into comparative models. In the protocol presented here, we review the comparative modeling process, including sequence alignment, threading and loop building. Next, we cover docking a small-molecule ligand into the protein comparative model. In addition, we discuss criteria that can improve ligand docking into comparative models. Finally, and importantly, we present a strategy for assessing model quality. The entire protocol is presented on a single example selected solely for didactic purposes. The results are therefore not representative and do not replace benchmarks published elsewhere. We also provide an additional tutorial so that the user can gain hands-on experience in using Rosetta. The protocol should take 5-7 h, with additional time allocated for computer generation of models.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23299552,

title = {Benchmarking ligand-based virtual High-Throughput Screening with the PubChem database},

author = {Mariusz Butkiewicz and Edward W Lowe and Ralf Mueller and Jeffrey L Mendenhall and Pedro L Teixeira and C David Weaver and Jens Meiler},

doi = {10.3390/molecules18010735},

issn = {1420-3049},

year  = {2013},

date = {2013-01-01},

journal = {Molecules},

volume = {18},

number = {1},

pages = {735--756},

abstract = {With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid24039810,

title = {RosettaEPR: rotamer library for spin label structure and dynamics},

author = {Nathan S Alexander and Richard A Stein and Hanane A Koteiche and Kristian W Kaufmann and Hassane S McHaourab and Jens Meiler},

doi = {10.1371/journal.pone.0072851},

issn = {1932-6203},

year  = {2013},

date = {2013-01-01},

journal = {PLoS One},

volume = {8},

number = {9},

pages = {e72851},

abstract = {An increasingly used parameter in structural biology is the measurement of distances between spin labels bound to a protein. One limitation to these measurements is the unknown position of the spin label relative to the protein backbone. To overcome this drawback, we introduce a rotamer library of the methanethiosulfonate spin label (MTSSL) into the protein modeling program Rosetta. Spin label rotamers were derived from conformations observed in crystal structures of spin labeled T4 lysozyme and previously published molecular dynamics simulations. Rosetta's ability to accurately recover spin label conformations and EPR measured distance distributions was evaluated against 19 experimentally determined MTSSL labeled structures of T4 lysozyme and the membrane protein LeuT and 73 distance distributions from T4 lysozyme and the membrane protein MsbA. For a site in the core of T4 lysozyme, the correct spin label conformation (Χ1 and Χ2) is recovered in 99.8% of trials. In surface positions 53% of the trajectories agree with crystallized conformations in Χ1 and Χ2. This level of recovery is on par with Rosetta performance for the 20 natural amino acids. In addition, Rosetta predicts the distance between two spin labels with a mean error of 4.4 Å. The width of the experimental distance distribution, which reflects the flexibility of the two spin labels, is predicted with a mean error of 1.3 Å. RosettaEPR makes full-atom spin label modeling available to a wide scientific community in conjunction with the powerful suite of modeling methods within Rosetta.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23977165,

title = {Octarellin VI: using rosetta to design a putative artificial (β/α)8 protein},

author = {Maximiliano Figueroa and Nicolas Oliveira and Annabelle Lejeune and Kristian W Kaufmann and Brent M Dorr and André Matagne and Joseph A Martial and Jens Meiler and Cécile Van de Weerdt},

doi = {10.1371/journal.pone.0071858},

issn = {1932-6203},

year  = {2013},

date = {2013-01-01},

journal = {PLoS One},

volume = {8},

number = {8},

pages = {e71858},

abstract = {The computational protein design protocol Rosetta has been applied successfully to a wide variety of protein engineering problems. Here the aim was to test its ability to design de novo a protein adopting the TIM-barrel fold, whose formation requires about twice as many residues as in the largest proteins successfully designed de novo to date. The designed protein, Octarellin VI, contains 216 residues. Its amino acid composition is similar to that of natural TIM-barrel proteins. When produced and purified, it showed a far-UV circular dichroism spectrum characteristic of folded proteins, with α-helical and β-sheet secondary structure. Its stable tertiary structure was confirmed by both tryptophan fluorescence and circular dichroism in the near UV. It proved heat stable up to 70°C. Dynamic light scattering experiments revealed a unique population of particles averaging 4 nm in diameter, in good agreement with our model. Although these data suggest the successful creation of an artificial α/β protein of more than 200 amino acids, Octarellin VI shows an apparent noncooperative chemical unfolding and low solubility.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23091036,

title = {Conformation of receptor-bound visual arrestin},

author = {Miyeon Kim and Sergey A Vishnivetskiy and Ned Van Eps and Nathan S Alexander and Whitney M Cleghorn and Xuanzhi Zhan and Susan M Hanson and Takefumi Morizumi and Oliver P Ernst and Jens Meiler and Vsevolod V Gurevich and Wayne L Hubbell},

doi = {10.1073/pnas.1216304109},

issn = {1091-6490},

year  = {2012},

date = {2012-11-01},

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

volume = {109},

number = {45},

pages = {18407--18412},

abstract = {Arrestin-1 (visual arrestin) binds to light-activated phosphorylated rhodopsin (P-Rh*) to terminate G-protein signaling. To map conformational changes upon binding to the receptor, pairs of spin labels were introduced in arrestin-1 and double electron-electron resonance was used to monitor interspin distance changes upon P-Rh* binding. The results indicate that the relative position of the N and C domains remains largely unchanged, contrary to expectations of a "clam-shell" model. A loop implicated in P-Rh* binding that connects β-strands V and VI (the "finger loop," residues 67-79) moves toward the expected location of P-Rh* in the complex, but does not assume a fully extended conformation. A striking and unexpected movement of a loop containing residue 139 away from the adjacent finger loop is observed, which appears to facilitate P-Rh* binding. This change is accompanied by smaller movements of distal loops containing residues 157 and 344 at the tips of the N and C domains, which correspond to "plastic" regions of arrestin-1 that have distinct conformations in monomers of the crystal tetramer. Remarkably, the loops containing residues 139, 157, and 344 appear to have high flexibility in both free arrestin-1 and the P-Rh*complex.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22592386,

title = {Iterative experimental and virtual high-throughput screening identifies metabotropic glutamate receptor subtype 4 positive allosteric modulators},

author = {Ralf Mueller and Eric S Dawson and Colleen M Niswender and Mariusz Butkiewicz and Corey R Hopkins and C David Weaver and Craig W Lindsley and P Jeffrey Conn and Jens Meiler},

doi = {10.1007/s00894-012-1441-0},

issn = {0948-5023},

year  = {2012},

date = {2012-09-01},

journal = {J Mol Model},

volume = {18},

number = {9},

pages = {4437--4446},

abstract = {Activation of metabotropic glutamate receptor subtype 4 has been shown to be efficacious in rodent models of Parkinson's disease. Artificial neural networks were trained based on a recently reported high throughput screen which identified 434 positive allosteric modulators of metabotropic glutamate receptor subtype 4 out of a set of approximately 155,000 compounds. A jury system containing three artificial neural networks achieved a theoretical enrichment of 15.4 when selecting the top 2 % compounds of an independent test dataset. The model was used to screen an external commercial database of approximately 450,000 drug-like compounds. 1,100 predicted active small molecules were tested experimentally using two distinct assays of mGlu(4) activity. This experiment yielded 67 positive allosteric modulators of metabotropic glutamate receptor subtype 4 that confirmed in both experimental systems. Compared to the 0.3 % active compounds in the primary screen, this constituted an enrichment of 22 fold.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22302372,

title = {Ab initio protein modeling into CryoEM density maps using EM-Fold},

author = {Steffen Lindert and Tommy Hofmann and Nils Wötzel and Mert Karakaş and Phoebe L Stewart and Jens Meiler},

doi = {10.1002/bip.22027},

issn = {0006-3525},

year  = {2012},

date = {2012-09-01},

journal = {Biopolymers},

volume = {97},

number = {9},

pages = {669--677},

abstract = {EM-Fold was used to build models for nine proteins in the maps of GroEL (7.7 Å resolution) and ribosome (6.4 Å resolution) in the ab initio modeling category of the 2010 cryo-electron microscopy modeling challenge. EM-Fold assembles predicted secondary structure elements (SSEs) into regions of the density map that were identified to correspond to either α-helices or β-strands. The assembly uses a Monte Carlo algorithm where loop closure, density-SSE length agreement, and strength of connecting density between SSEs are evaluated. Top-scoring models are refined by translating, rotating, and bending SSEs to yield better agreement with the density map. EM-Fold produces models that contain backbone atoms within SSEs only. The RMSD values of the models with respect to native range from 2.4 to 3.5 Å for six of the nine proteins. EM-Fold failed to predict the correct topology in three cases. Subsequently, Rosetta was used to build loops and side chains for the very best scoring models after EM-Fold refinement. The refinement within Rosetta's force field is driven by a density agreement score that calculates a cross-correlation between a density map simulated from the model and the experimental density map. All-atom RMSDs as low as 3.4 Å are achieved in favorable cases. Values above 10.0 Å are observed for two proteins with low overall content of secondary structure and hence particularly complex loop modeling problems. RMSDs over residues in secondary structure elements range from 2.5 to 4.8 Å.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22778259,

title = {Ligand-mimicking receptor variant discloses binding and activation mode of prolactin-releasing peptide},

author = {Daniel Rathmann and Diana Lindner and Stephanie H DeLuca and Kristian W Kaufmann and Jens Meiler and Annette G Beck-Sickinger},

doi = {10.1074/jbc.M112.349852},

issn = {1083-351X},

year  = {2012},

date = {2012-09-01},

journal = {J Biol Chem},

volume = {287},

number = {38},

pages = {32181--32194},

abstract = {The prolactin-releasing peptide receptor and its bioactive RF-amide peptide (PrRP20) have been investigated to explore the ligand binding mode of peptide G-protein-coupled receptors (GPCRs). By receptor mutagenesis, we identified the conserved aspartate in the upper transmembrane helix 6 (Asp(6.59)) of the receptor as the first position that directly interacts with arginine 19 of the ligand (Arg(19)). Replacement of Asp(6.59) with Arg(19) of PrRP20 led to D6.59R, which turned out to be a constitutively active receptor mutant (CAM). This suggests that the mutated residue at the top of transmembrane helix 6 mimics Arg(19) by interacting with additional binding partners in the receptor. Next, we generated an initial comparative model of this CAM because no ligand docking was required, and we selected the next set of receptor mutants to find the engaged partners of the binding pocket. In an iterative process, we identified two acidic residues and two hydrophobic residues that form the peptide ligand binding pocket. As all residues are localized on top or in the upper part of the transmembrane domains, we clearly can show that the extracellular surface of the receptor is sufficient for full signal transduction for prolactin-releasing peptide, rather than a deep, membrane-embedded binding pocket. This contributes to the knowledge of the binding of peptide ligands to GPCRs and might facilitate the development of GPCR ligands, but it also provides new targeting of CAMs involved in hereditary diseases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22907158,

title = {BCL::EMAS--enantioselective molecular asymmetry descriptor for 3D-QSAR},

author = {Gregory Sliwoski and Edward W Lowe and Mariusz Butkiewicz and Jens Meiler},

doi = {10.3390/molecules17089971},

issn = {1420-3049},

year  = {2012},

date = {2012-08-01},

journal = {Molecules},

volume = {17},

number = {8},

pages = {9971--9989},

abstract = {Stereochemistry is an important determinant of a molecule's biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS) that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF) determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r² = 0.89, q² = 0.78). Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS) for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22708927,

title = {Selective mode of action of guanidine-containing non-peptides at human NPFF receptors},

author = {Maria Findeisen and Cäcilia Würker and Daniel Rathmann and René Meier and Jens Meiler and Roger Olsson and Annette G Beck-Sickinger},

doi = {10.1021/jm300535s},

issn = {1520-4804},

year  = {2012},

date = {2012-07-01},

journal = {J Med Chem},

volume = {55},

number = {13},

pages = {6124--6136},

abstract = {The binding pocket of both NPFF receptors was investigated, focusing on subtype-selective behavior. By use of four nonpeptidic compounds and the peptide mimetics RF9 and BIBP3226, agonistic and antagonistic properties were characterized. A set of Ala receptor mutants was generated. The binding pocket was narrowed down to the upper part of transmembrane helices V, VI, VII and the extracellular loop 2. Positions 5.27 and 6.59 have been shown to have a strong impact on receptor activation and were suggested to form an acidic, negatively charged binding pocket in both NPFF receptor subtypes. Additionally, position 7.35 was identified to play an important role in functional selectivity. According to docking experiments, the aryl group of AC-216 interacts with position 7.35 in the NPFF(1) but not in the NPFF(2) receptor. These results provide distinct insights into the receptor specific binding pockets, which is necessary for the development of drugs to address the NPFF system.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22321894,

title = {Prediction of HIV-1 protease/inhibitor affinity using RosettaLigand},

author = {Gordon Lemmon and Kristian Kaufmann and Jens Meiler},

doi = {10.1111/j.1747-0285.2012.01356.x},

issn = {1747-0285},

year  = {2012},

date = {2012-06-01},

journal = {Chem Biol Drug Des},

volume = {79},

number = {6},

pages = {888--896},

abstract = {Predicting HIV-1 protease/inhibitor binding affinity as the difference between the free energy of the inhibitor bound and unbound state remains difficult as the unbound state exists as an ensemble of conformations with various degrees of flap opening. We improve computational prediction of protease/inhibitor affinity by invoking the hypothesis that the free energy of the unbound state while difficult to predict is less sensitive to mutation. Thereby the HIV-1 protease/inhibitor binding affinity can be approximated with the free energy of the bound state alone. Bound state free energy can be predicted from comparative models of HIV-1 protease mutant/inhibitor complexes. Absolute binding energies are predicted with R = 0.71 and SE = 5.91 kJ/mol. Changes in binding free energy upon mutation can be predicted with R = 0.85 and SE = 4.49 kJ/mol. Resistance mutations that lower inhibitor binding affinity can thereby be recognized early in HIV-1 protease inhibitor development.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22515365,

title = {Second-site suppressors of HIV-1 capsid mutations: restoration of intracellular activities without correction of intrinsic capsid stability defects},

author = {Ruifeng Yang and Jiong Shi and In-Ja L Byeon and Jinwoo Ahn and Jonathan H Sheehan and Jens Meiler and Angela M Gronenborn and Christopher Aiken},

doi = {10.1186/1742-4690-9-30},

issn = {1742-4690},

year  = {2012},

date = {2012-04-01},

journal = {Retrovirology},

volume = {9},

pages = {30},

abstract = {BACKGROUND: Disassembly of the viral capsid following penetration into the cytoplasm, or uncoating, is a poorly understood stage of retrovirus infection. Based on previous studies of HIV-1 CA mutants exhibiting altered capsid stability, we concluded that formation of a capsid of optimal intrinsic stability is crucial for HIV-1 infection.nnRESULTS: To further examine the connection between HIV-1 capsid stability and infectivity, we isolated second-site suppressors of HIV-1 mutants exhibiting unstable (P38A) or hyperstable (E45A) capsids. We identified the respective suppressor mutations, T216I and R132T, which restored virus replication in a human T cell line and markedly enhanced the fitness of the original mutants as revealed in single-cycle infection assays. Analysis of the corresponding purified N-terminal domain CA proteins by NMR spectroscopy demonstrated that the E45A and R132T mutations induced structural changes that are localized to the regions of the mutations, while the P38A mutation resulted in changes extending to neighboring regions in space. Unexpectedly, neither suppressor mutation corrected the intrinsic viral capsid stability defect associated with the respective original mutation. Nonetheless, the R132T mutation rescued the selective infectivity impairment exhibited by the E45A mutant in aphidicolin-arrested cells, and the double mutant regained sensitivity to the small molecule inhibitor PF74. The T216I mutation rescued the impaired ability of the P38A mutant virus to abrogate restriction by TRIMCyp and TRIM5α.nnCONCLUSIONS: The second-site suppressor mutations in CA that we have identified rescue virus infection without correcting the intrinsic capsid stability defects associated with the P38A and E45A mutations. The suppressors also restored wild type virus function in several cell-based assays. We propose that while proper HIV-1 uncoating in target cells is dependent on the intrinsic stability of the viral capsid, the effects of stability-altering mutations can be mitigated by additional mutations that affect interactions with host factors in target cells or the consequences of these interactions. The ability of mutations at other CA surfaces to compensate for effects at the NTD-NTD interface further indicates that uncoating in target cells is controlled by multiple intersubunit interfaces in the viral capsid.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22267125,

title = {Discovery of 2-(2-benzoxazoyl amino)-4-aryl-5-cyanopyrimidine as negative allosteric modulators (NAMs) of metabotropic glutamate receptor 5 (mGlu₅): from an artificial neural network virtual screen to an in vivo tool compound},

author = {Ralf Mueller and Eric S Dawson and Jens Meiler and Alice L Rodriguez and Brian A Chauder and Brittney S Bates and Andrew S Felts and Jeffrey P Lamb and Usha N Menon and Sataywan B Jadhav and Alexander S Kane and Carrie K Jones and Karen J Gregory and Colleen M Niswender and P Jeffrey Conn and Christopher M Olsen and Danny G Winder and Kyle A Emmitte and Craig W Lindsley},

doi = {10.1002/cmdc.201100510},

issn = {1860-7187},

year  = {2012},

date = {2012-03-01},

journal = {ChemMedChem},

volume = {7},

number = {3},

pages = {406--414},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22329686,

title = {Potential of fragment recombination for rational design of proteins},

author = {Simone Eisenbeis and William Proffitt and Murray Coles and Vincent Truffault and Sooruban Shanmugaratnam and Jens Meiler and Birte Höcker},

doi = {10.1021/ja211657k},

issn = {1520-5126},

year  = {2012},

date = {2012-03-01},

journal = {J Am Chem Soc},

volume = {134},

number = {9},

pages = {4019--4022},

abstract = {It is hypothesized that protein domains evolved from smaller intrinsically stable subunits via combinatorial assembly. Illegitimate recombination of fragments that encode protein subunits could have quickly led to diversification of protein folds and their functionality. This evolutionary concept presents an attractive strategy to protein engineering, e.g., to create new scaffolds for enzyme design. We previously combined structurally similar parts from two ancient protein folds, the (βα)(8)-barrel and the flavodoxin-like fold. The resulting "hopeful monster" differed significantly from the intended (βα)(8)-barrel fold by an extra β-strand in the core. In this study, we ask what modifications are necessary to form the intended structure and what potential this approach has for the rational design of functional proteins. Guided by computational design, we optimized the interface between the fragments with five targeted mutations yielding a stable, monomeric protein whose predicted structure was verified experimentally. We further tested binding of a phosphorylated compound and detected that some affinity was already present due to an intact phosphate-binding site provided by one fragment. The affinity could be improved quickly to the level of natural proteins by introducing two additional mutations. The study illustrates the potential of recombining protein fragments with unique properties to design new and functional proteins, offering both a possible pathway of protein evolution and a protocol to rapidly engineer proteins for new applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22405005,

title = {EM-fold: de novo atomic-detail protein structure determination from medium-resolution density maps},

author = {Steffen Lindert and Nathan Alexander and Nils Wötzel and Mert Karakaş and Phoebe L Stewart and Jens Meiler},

doi = {10.1016/j.str.2012.01.023},

issn = {1878-4186},

year  = {2012},

date = {2012-03-01},

journal = {Structure},

volume = {20},

number = {3},

pages = {464--478},

abstract = {Electron density maps of membrane proteins or large macromolecular complexes are frequently only determined at medium resolution between 4 Å and 10 Å, either by cryo-electron microscopy or X-ray crystallography. In these density maps, the general arrangement of secondary structure elements (SSEs) is revealed, whereas their directionality and connectivity remain elusive. We demonstrate that the topology of proteins with up to 250 amino acids can be determined from such density maps when combined with a computational protein folding protocol. Furthermore, we accurately reconstruct atomic detail in loop regions and amino acid side chains not visible in the experimental data. The EM-Fold algorithm assembles the SSEs de novo before atomic detail is added using Rosetta. In a benchmark of 27 proteins, the protocol consistently and reproducibly achieves models with root mean square deviation values <3 Å.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23173050,

title = {BCL::Fold--de novo prediction of complex and large protein topologies by assembly of secondary structure elements},

author = {Mert Karakaş and Nils Woetzel and Rene Staritzbichler and Nathan Alexander and Brian E Weiner and Jens Meiler},

doi = {10.1371/journal.pone.0049240},

issn = {1932-6203},

year  = {2012},

date = {2012-01-01},

journal = {PLoS One},

volume = {7},

number = {11},

pages = {e49240},

abstract = {Computational de novo protein structure prediction is limited to small proteins of simple topology. The present work explores an approach to extend beyond the current limitations through assembling protein topologies from idealized α-helices and β-strands. The algorithm performs a Monte Carlo Metropolis simulated annealing folding simulation. It optimizes a knowledge-based potential that analyzes radius of gyration, β-strand pairing, secondary structure element (SSE) packing, amino acid pair distance, amino acid environment, contact order, secondary structure prediction agreement and loop closure. Discontinuation of the protein chain favors sampling of non-local contacts and thereby creation of complex protein topologies. The folding simulation is accelerated through exclusion of flexible loop regions further reducing the size of the conformational search space. The algorithm is benchmarked on 66 proteins with lengths between 83 and 293 amino acids. For 61 out of these proteins, the best SSE-only models obtained have an RMSD100 below 8.0 Å and recover more than 20% of the native contacts. The algorithm assembles protein topologies with up to 215 residues and a relative contact order of 0.46. The method is tailored to be used in conjunction with low-resolution or sparse experimental data sets which often provide restraints for regions of defined secondary structure.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23173051,

title = {BCL::Score--knowledge based energy potentials for ranking protein models represented by idealized secondary structure elements},

author = {Nils Woetzel and Mert Karakaş and Rene Staritzbichler and Ralf Müller and Brian E Weiner and Jens Meiler},

doi = {10.1371/journal.pone.0049242},

issn = {1932-6203},

year  = {2012},

date = {2012-01-01},

journal = {PLoS One},

volume = {7},

number = {11},

pages = {e49242},

abstract = {The topology of most experimentally determined protein domains is defined by the relative arrangement of secondary structure elements, i.e. α-helices and β-strands, which make up 50-70% of the sequence. Pairing of β-strands defines the topology of β-sheets. The packing of side chains between α-helices and β-sheets defines the majority of the protein core. Often, limited experimental datasets restrain the position of secondary structure elements while lacking detail with respect to loop or side chain conformation. At the same time the regular structure and reduced flexibility of secondary structure elements make these interactions more predictable when compared to flexible loops and side chains. To determine the topology of the protein in such settings, we introduce a tailored knowledge-based energy function that evaluates arrangement of secondary structure elements only. Based on the amino acid C(β) atom coordinates within secondary structure elements, potentials for amino acid pair distance, amino acid environment, secondary structure element packing, β-strand pairing, loop length, radius of gyration, contact order and secondary structure prediction agreement are defined. Separate penalty functions exclude conformations with clashes between amino acids or secondary structure elements and loops that cannot be closed. Each individual term discriminates for native-like protein structures. The composite potential significantly enriches for native-like models in three different databases of 10,000-12,000 protein models in 80-94% of the cases. The corresponding application, "BCL::ScoreProtein," is available at www.meilerlab.org.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22183535,

title = {Rosetta Ligand docking with flexible XML protocols},

author = {Gordon Lemmon and Jens Meiler},

doi = {10.1007/978-1-61779-465-0_10},

issn = {1940-6029},

year  = {2012},

date = {2012-01-01},

journal = {Methods Mol Biol},

volume = {819},

pages = {143--155},

abstract = {RosettaLigand is premiere software for predicting how a protein and a small molecule interact. Benchmark studies demonstrate that 70% of the top scoring RosettaLigand predicted interfaces are within 2Å RMSD from the crystal structure [1]. The latest release of Rosetta ligand software includes many new features, such as (1) docking of multiple ligands simultaneously, (2) representing ligands as fragments for greater flexibility, (3) redesign of the interface during docking, and (4) an XML script based interface that gives the user full control of the ligand docking protocol.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23239984,

title = {Using RosettaLigand for small molecule docking into comparative models},

author = {Kristian W Kaufmann and Jens Meiler},

doi = {10.1371/journal.pone.0050769},

issn = {1932-6203},

year  = {2012},

date = {2012-01-01},

journal = {PLoS One},

volume = {7},

number = {12},

pages = {e50769},

abstract = {Computational small molecule docking into comparative models of proteins is widely used to query protein function and in the development of small molecule therapeutics. We benchmark RosettaLigand docking into comparative models for nine proteins built during CASP8 that contain ligands. We supplement the study with 21 additional protein/ligand complexes to cover a wider space of chemotypes. During a full docking run in 21 of the 30 cases, RosettaLigand successfully found a native-like binding mode among the top ten scoring binding modes. From the benchmark cases we find that careful template selection based on ligand occupancy provides the best chance of success while overall sequence identity between template and target do not appear to improve results. We also find that binding energy normalized by atom number is often less than -0.4 in native-like binding modes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22027343,

title = {Expanding the utility of NMR restraints with paramagnetic compounds: background and practical aspects},

author = {Julia Koehler and Jens Meiler},

doi = {10.1016/j.pnmrs.2011.05.001},

issn = {1873-3301},

year  = {2011},

date = {2011-11-01},

journal = {Prog Nucl Magn Reson Spectrosc},

volume = {59},

number = {4},

pages = {360--389},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21978247,

title = {Exploring symmetry as an avenue to the computational design of large protein domains},

author = {Carie Fortenberry and Elizabeth Anne Bowman and Will Proffitt and Brent Dorr and Steven Combs and Joel Harp and Laura Mizoue and Jens Meiler},

doi = {10.1021/ja2051217},

issn = {1520-5126},

year  = {2011},

date = {2011-11-01},

journal = {J Am Chem Soc},

volume = {133},

number = {45},

pages = {18026--18029},

abstract = {It has been demonstrated previously that symmetric, homodimeric proteins are energetically favored, which explains their abundance in nature. It has been proposed that such symmetric homodimers underwent gene duplication and fusion to evolve into protein topologies that have a symmetric arrangement of secondary structure elements--"symmetric superfolds". Here, the ROSETTA protein design software was used to computationally engineer a perfectly symmetric variant of imidazole glycerol phosphate synthase and its corresponding symmetric homodimer. The new protein, termed FLR, adopts the symmetric (βα)(8) TIM-barrel superfold. The protein is soluble and monomeric and exhibits two-fold symmetry not only in the arrangement of secondary structure elements but also in sequence and at atomic detail, as verified by crystallography. When cut in half, FLR dimerizes readily to form the symmetric homodimer. The successful computational design of FLR demonstrates progress in our understanding of the underlying principles of protein stability and presents an attractive strategy for the in silico construction of larger protein domains from smaller pieces.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21905701,

title = {Design of native-like proteins through an exposure-dependent environment potential},

author = {Samuel DeLuca and Brent Dorr and Jens Meiler},

doi = {10.1021/bi200664b},

issn = {1520-4995},

year  = {2011},

date = {2011-10-01},

journal = {Biochemistry},

volume = {50},

number = {40},

pages = {8521--8528},

abstract = {We hypothesize that the degree of surface exposure of amino acid side chains within a globular, soluble protein has been optimized in evolution, not only to minimize the solvation free energy of the monomeric protein but also to prevent protein aggregation. This effect needs to be taken into account when engineering proteins de novo. We test this hypothesis through addition of a knowledge-based, exposure-dependent energy term to the RosettaDesign solvation potential [Lazaridis, T., and Karplus, M. (1999) Proteins 35, 133-152]. Correlation between amino acid type and surface exposure is determined from a representative set of experimental protein structures. The amino acid solvent accessible surface area (SASA) is estimated with a neighbor vector measure that increases in accuracy compared to the neighbor count measure while remaining pairwise decomposable [Durham, E., et al. (2009) J. Mol. Model. 15, 1093-1108]. Benchmarking of this potential in protein design displays a 3.2% improvement in the overall sequence recovery and an 8.5% improvement in recovery of amino acid types tolerated in evolution.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21565271,

title = {BCL::EM-Fit: rigid body fitting of atomic structures into density maps using geometric hashing and real space refinement},

author = {Nils Woetzel and Steffen Lindert and Phoebe L Stewart and Jens Meiler},

doi = {10.1016/j.jsb.2011.04.016},

issn = {1095-8657},

year  = {2011},

date = {2011-09-01},

journal = {J Struct Biol},

volume = {175},

number = {3},

pages = {264--276},

abstract = {Cryo-electron microscopy (cryoEM) can visualize large macromolecular assemblies at resolutions often below 10Å and recently as good as 3.8-4.5 Å. These density maps provide important insights into the biological functioning of molecular machineries such as viruses or the ribosome, in particular if atomic-resolution crystal structures or models of individual components of the assembly can be placed into the density map. The present work introduces a novel algorithm termed BCL::EM-Fit that accurately fits atomic-detail structural models into medium resolution density maps. In an initial step, a "geometric hashing" algorithm provides a short list of likely placements. In a follow up Monte Carlo/Metropolis refinement step, the initial placements are optimized by their cross correlation coefficient. The resolution of density maps for a reliable fit was determined to be 10 Å or better using tests with simulated density maps. The algorithm was applied to fitting of capsid proteins into an experimental cryoEM density map of human adenovirus at a resolution of 6.8 and 9.0 Å, and fitting of the GroEL protein at 5.4 Å. In the process, the handedness of the cryoEM density map was unambiguously identified. The BCL::EM-Fit algorithm offers an alternative to the established Fourier/Real space fitting programs. BCL::EM-Fit is free for academic use and available from a web server or as downloadable binary file at http://www.meilerlab.org.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21730057,

title = {A conserved asparagine residue in transmembrane segment 1 (TM1) of serotonin transporter dictates chloride-coupled neurotransmitter transport},

author = {L Keith Henry and Hideki Iwamoto and Julie R Field and Kristian Kaufmann and Eric S Dawson and Miriam T Jacobs and Chelsea Adams and Bruce Felts and Igor Zdravkovic and Vanessa Armstrong and Steven Combs and Ernesto Solis and Gary Rudnick and Sergei Y Noskov and Louis J DeFelice and Jens Meiler and Randy D Blakely},

doi = {10.1074/jbc.M111.250308},

issn = {1083-351X},

year  = {2011},

date = {2011-09-01},

journal = {J Biol Chem},

volume = {286},

number = {35},

pages = {30823--30836},

abstract = {Na(+)- and Cl(-)-dependent uptake of neurotransmitters via transporters of the SLC6 family, including the human serotonin transporter (SLC6A4), is critical for efficient synaptic transmission. Although residues in the human serotonin transporter involved in direct Cl(-) coordination of human serotonin transport have been identified, the role of Cl(-) in the transport mechanism remains unclear. Through a combination of mutagenesis, chemical modification, substrate and charge flux measurements, and molecular modeling studies, we reveal an unexpected role for the highly conserved transmembrane segment 1 residue Asn-101 in coupling Cl(-) binding to concentrative neurotransmitter uptake.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21349882,

title = {Computational design of an endo-1,4-beta-xylanase ligand binding site},

author = {Andrew Morin and Kristian W Kaufmann and Carie Fortenberry and Joel M Harp and Laura S Mizoue and Jens Meiler},

doi = {10.1093/protein/gzr006},

issn = {1741-0134},

year  = {2011},

date = {2011-06-01},

journal = {Protein Eng Des Sel},

volume = {24},

number = {6},

pages = {503--516},

abstract = {The field of computational protein design has experienced important recent success. However, the de novo computational design of high-affinity protein-ligand interfaces is still largely an open challenge. Using the Rosetta program, we attempted the in silico design of a high-affinity protein interface to a small peptide ligand. We chose the thermophilic endo-1,4-β-xylanase from Nonomuraea flexuosa as the protein scaffold on which to perform our designs. Over the course of the study, 12 proteins derived from this scaffold were produced and assayed for binding to the target ligand. Unfortunately, none of the designed proteins displayed evidence of high-affinity binding. Structural characterization of four designed proteins revealed that although the predicted structure of the protein model was highly accurate, this structural accuracy did not translate into accurate prediction of binding affinity. Crystallographic analyses indicate that the lack of binding affinity is possibly due to unaccounted for protein dynamics in the 'thumb' region of our design scaffold intrinsic to the family 11 β-xylanase fold. Further computational analysis revealed two specific, single amino acid substitutions responsible for an observed change in backbone conformation, and decreased dynamic stability of the catalytic cleft. These findings offer new insight into the dynamic and structural determinants of the β-xylanase proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21606326,

title = {Interaction of a G protein with an activated receptor opens the interdomain interface in the alpha subunit},

author = {Ned Van Eps and Anita M Preininger and Nathan Alexander and Ali I Kaya and Scott Meier and Jens Meiler and Heidi E Hamm and Wayne L Hubbell},

doi = {10.1073/pnas.1105810108},

issn = {1091-6490},

year  = {2011},

date = {2011-06-01},

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

volume = {108},

number = {23},

pages = {9420--9424},

abstract = {In G-protein signaling, an activated receptor catalyzes GDP/GTP exchange on the G(α) subunit of a heterotrimeric G protein. In an initial step, receptor interaction with G(α) acts to allosterically trigger GDP release from a binding site located between the nucleotide binding domain and a helical domain, but the molecular mechanism is unknown. In this study, site-directed spin labeling and double electron-electron resonance spectroscopy are employed to reveal a large-scale separation of the domains that provides a direct pathway for nucleotide escape. Cross-linking studies show that the domain separation is required for receptor enhancement of nucleotide exchange rates. The interdomain opening is coupled to receptor binding via the C-terminal helix of G(α), the extension of which is a high-affinity receptor binding element.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21295366,

title = {Computational design of protein-ligand interfaces: potential in therapeutic development},

author = {Andrew Morin and Jens Meiler and Laura S Mizoue},

doi = {10.1016/j.tibtech.2011.01.002},

issn = {1879-3096},

year  = {2011},

date = {2011-04-01},

journal = {Trends Biotechnol},

volume = {29},

number = {4},

pages = {159--166},

abstract = {Computational design of protein-ligand interfaces finds optimal amino acid sequences within a small-molecule binding site of a protein for tight binding of a specific small molecule. It requires a search algorithm that can rapidly sample the vast sequence and conformational space, and a scoring function that can identify low energy designs. This review focuses on recent advances in computational design methods and their application to protein-small molecule binding sites. Strategies for increasing affinity, altering specificity, creating broad-spectrum binding, and building novel enzymes from scratch are described. Future prospects for applications in drug development are discussed, including limitations that will need to be overcome to achieve computational design of protein therapeutics with novel modes of action.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21481766,

title = {Membrane protein structure determination using paramagnetic tags},

author = {Soumya Ganguly and Brian E Weiner and Jens Meiler},

doi = {10.1016/j.str.2011.03.008},

issn = {1878-4186},

year  = {2011},

date = {2011-04-01},

journal = {Structure},

volume = {19},

number = {4},

pages = {441--443},

abstract = {The combination of paramagnetic tagging strategies with NMR or EPR spectroscopic techniques can revolutionize de novo structure determination of helical membrane proteins. Leveraging the full potential of this approach requires optimal labeling strategies and prediction of membrane protein topology from sparse and low-resolution distance restraints, as addressed by Chen et al. (2011).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21029778,

title = {RosettaEPR: an integrated tool for protein structure determination from sparse EPR data},

author = {Stephanie J Hirst and Nathan Alexander and Hassane S McHaourab and Jens Meiler},

doi = {10.1016/j.jsb.2010.10.013},

issn = {1095-8657},

year  = {2011},

date = {2011-03-01},

journal = {J Struct Biol},

volume = {173},

number = {3},

pages = {506--514},

abstract = {Site-directed spin labeling electron paramagnetic resonance (SDSL-EPR) is often used for the structural characterization of proteins that elude other techniques, such as X-ray crystallography and nuclear magnetic resonance (NMR). However, high-resolution structures are difficult to obtain due to uncertainty in the spin label location and sparseness of experimental data. Here, we introduce RosettaEPR, which has been designed to improve de novo high-resolution protein structure prediction using sparse SDSL-EPR distance data. The "motion-on-a-cone" spin label model is converted into a knowledge-based potential, which was implemented as a scoring term in Rosetta. RosettaEPR increased the fractions of correctly folded models ( [Formula: see text] <7.5Å) and models accurate at medium resolution ( [Formula: see text] <3.5Å) by 25%. The correlation of score and model quality increased from 0.42 when using no restraints to 0.51 when using bounded restraints and again to 0.62 when using RosettaEPR. This allowed for the selection of accurate models by score. After full-atom refinement, RosettaEPR yielded a 1.7Å model of T4-lysozyme, thus indicating that atomic detail models can be achieved by combining sparse EPR data with Rosetta. While these results indicate RosettaEPR's potential utility in high-resolution protein structure prediction, they are based on a single example. In order to affirm the method's general performance, it must be tested on a larger and more versatile dataset of proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21074624,

title = {Algorithm for selection of optimized EPR distance restraints for de novo protein structure determination},

author = {Kelli Kazmier and Nathan S Alexander and Jens Meiler and Hassane S McHaourab},

doi = {10.1016/j.jsb.2010.11.003},

issn = {1095-8657},

year  = {2011},

date = {2011-03-01},

journal = {J Struct Biol},

volume = {173},

number = {3},

pages = {549--557},

abstract = {A hybrid protein structure determination approach combining sparse Electron Paramagnetic Resonance (EPR) distance restraints and Rosetta de novo protein folding has been previously demonstrated to yield high quality models (Alexander et al. (2008)). However, widespread application of this methodology to proteins of unknown structures is hindered by the lack of a general strategy to place spin label pairs in the primary sequence. In this work, we report the development of an algorithm that optimally selects spin labeling positions for the purpose of distance measurements by EPR. For the α-helical subdomain of T4 lysozyme (T4L), simulated restraints that maximize sequence separation between the two spin labels while simultaneously ensuring pairwise connectivity of secondary structure elements yielded vastly improved models by Rosetta folding. 54% of all these models have the correct fold compared to only 21% and 8% correctly folded models when randomly placed restraints or no restraints are used, respectively. Moreover, the improvements in model quality require a limited number of optimized restraints, which is determined by the pairwise connectivities of T4L α-helices. The predicted improvement in Rosetta model quality was verified by experimental determination of distances between spin labels pairs selected by the algorithm. Overall, our results reinforce the rationale for the combined use of sparse EPR distance restraints and de novo folding. By alleviating the experimental bottleneck associated with restraint selection, this algorithm sets the stage for extending computational structure determination to larger, traditionally elusive protein topologies of critical structural and biochemical importance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid27818847,

title = {bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System},

author = {Nathan Alexander and Nils Woetzel and Jens Meiler},

doi = {10.1109/ICCABS.2011.5729867},

issn = {2164-229X},

year  = {2011},

date = {2011-02-01},

journal = {IEEE Int Conf Comput Adv Bio Med Sci},

volume = {2011},

pages = {13--18},

abstract = {Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid22778858,

title = {Y95 and E444 interaction required for high-affinity S-citalopram binding in the human serotonin transporter},

author = {Steven Combs and Kristian Kaufmann and Julie R Field and Randy D Blakely and Jens Meiler},

doi = {10.1021/cn100066p},

issn = {1948-7193},

year  = {2011},

date = {2011-02-01},

journal = {ACS Chem Neurosci},

volume = {2},

number = {2},

pages = {75--81},

abstract = {The human serotonin (5-hydroxytryptamine, 5-HT) transporter (hSERT) is responsible for the reuptake of 5-HT following synaptic release, as well as for import of the biogenic amine into several non-5-HT synthesizing cells including platelets. The antidepressant citalopram blocks SERT and thereby inhibits the transport of 5-HT. To identify key residues establishing high-affinity citalopram binding, we have built a comparative model of hSERT and Drosophila melanogaster SERT (dSERT) based on the Aquifex aeolicus leucine transporter (LeuT(Aa)) crystal structure. In this study, citalopram has been docked into the homology model of hSERT and dSERT using RosettaLigand. Our models reproduce the differential binding affinities for the R- and S-isomers of citalopram in hSERT and the impact of several hSERT mutants. Species-selective binding affinities for hSERT and dSERT also can be reproduced. Interestingly, the model predicts a hydrogen bond between E444 in transmembrane domain 8 (TM8) and Y95 in TM1 that places Y95 in a downward position, thereby removing Y95 from a direct interaction with S-citalopram. Mutation of E444D results in a 10-fold reduced binding affinity for S-citalopram, supporting the hypothesis that Y95 and E444 form a stabilizing interaction in the S-citalopram/hSERT complex.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20461427,

title = {A physical model for PDZ-domain/peptide interactions},

author = {Kristian Kaufmann and Nicole Shen and Laura Mizoue and Jens Meiler},

doi = {10.1007/s00894-010-0725-5},

issn = {0948-5023},

year  = {2011},

date = {2011-02-01},

journal = {J Mol Model},

volume = {17},

number = {2},

pages = {315--324},

abstract = {The PDZ domain is an interaction motif that recognizes and binds the C-terminal peptides of target proteins. PDZ domains are ubiquitous in nature and help assemble multiprotein complexes that control cellular organization and signaling cascades. We present an optimized energy function to predict the binding free energy (ΔΔG) of PDZ domain/peptide interactions computationally. Geometry-optimized models of PDZ domain/peptide interfaces were built using ROSETTA: , and protein and peptide side chain and backbone degrees of freedom are minimized simultaneously. Using leave-one-out cross-validation, ROSETTA: 's energy function is adjusted to reproduce experimentally determined ΔΔG values with a correlation coefficient of 0.66 and a standard deviation of 0.79 kcal mol(-1). The energy function places an increased weight on hydrogen bonding interactions when compared to a previously developed method to analyze protein/protein interactions. Binding free enthalpies (ΔΔH) and entropies (ΔS) are predicted with reduced accuracies of R = 0.60 and R = 0.17, respectively. The computational method improves prediction of PDZ domain specificity from sequence and allows design of novel PDZ domain/peptide interactions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20926757,

title = {Development of a selective small-molecule inhibitor of Kir1.1, the renal outer medullary potassium channel},

author = {Gautam Bhave and Brian A Chauder and Wen Liu and Eric S Dawson and Rishin Kadakia and Thuy T Nguyen and L Michelle Lewis and Jens Meiler and C David Weaver and Lisa M Satlin and Craig W Lindsley and Jerod S Denton},

doi = {10.1124/mol.110.066928},

issn = {1521-0111},

year  = {2011},

date = {2011-01-01},

journal = {Mol Pharmacol},

volume = {79},

number = {1},

pages = {42--50},

abstract = {The renal outer medullary potassium (K+) channel, ROMK (Kir1.1), is a putative drug target for a novel class of loop diuretic that would lower blood volume and pressure without causing hypokalemia. However, the lack of selective ROMK inhibitors has hindered efforts to assess its therapeutic potential. In a high-throughput screen for small-molecule modulators of ROMK, we previously identified a potent and moderately selective ROMK antagonist, 7,13-bis(4-nitrobenzyl)-1,4,10-trioxa-7,13-diazacyclopentadecane (VU590), that also inhibits Kir7.1. Because ROMK and Kir7.1 are coexpressed in the nephron, VU590 is not a good probe of ROMK function in the kidney. Here we describe the development of the structurally related inhibitor 2,2'-oxybis(methylene)bis(5-nitro-1H-benzo[d]imidazole) (VU591), which is as potent as VU590 but is selective for ROMK over Kir7.1 and more than 65 other potential off-targets. VU591 seems to block the intracellular pore of the channel. The development of VU591 may enable studies to explore the viability of ROMK as a diuretic target.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20637216,

title = {Allosteric modulation of metabotropic glutamate receptors: structural insights and therapeutic potential},

author = {Karen J Gregory and Elizabeth N Dong and Jens Meiler and P Jeffrey Conn},

doi = {10.1016/j.neuropharm.2010.07.007},

issn = {1873-7064},

year  = {2011},

date = {2011-01-01},

journal = {Neuropharmacology},

volume = {60},

number = {1},

pages = {66--81},

abstract = {Allosteric modulation of G protein-coupled receptors (GPCRs) represents a novel approach to the development of probes and therapeutics that is expected to enable subtype-specific regulation of central nervous system target receptors. The metabotropic glutamate receptors (mGlus) are class C GPCRs that play important neuromodulatory roles throughout the brain, as such they are attractive targets for therapeutic intervention for a number of psychiatric and neurological disorders including anxiety, depression, Fragile X Syndrome, Parkinson's disease and schizophrenia. Over the last fifteen years, selective allosteric modulators have been identified for many members of the mGlu family. The vast majority of these allosteric modulators are thought to bind within the transmembrane-spanning domains of the receptors to enhance or inhibit functional responses. A combination of mutagenesis-based studies and pharmacological approaches are beginning to provide a better understanding of mGlu allosteric sites. Collectively, when mapped onto a homology model of the different mGlu subtypes based on the β(2)-adrenergic receptor, the previous mutagenesis studies suggest commonalities in the location of allosteric sites across different members of the mGlu family. In addition, there is evidence for multiple allosteric binding pockets within the transmembrane region that can interact to modulate one another. In the absence of a class C GPCR crystal structure, this approach has shown promise with respect to the interpretation of mutagenesis data and understanding structure-activity relationships of allosteric modulator pharmacophores.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21187238,

title = {ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules},

author = {Andrew Leaver-Fay and Michael Tyka and Steven M Lewis and Oliver F Lange and James Thompson and Ron Jacak and Kristian Kaufman and P Douglas Renfrew and Colin A Smith and Will Sheffler and Ian W Davis and Seth Cooper and Adrien Treuille and Daniel J Mandell and Florian Richter and Yih-En Andrew Ban and Sarel J Fleishman and Jacob E Corn and David E Kim and Sergey Lyskov and Monica Berrondo and Stuart Mentzer and Zoran Popović and James J Havranek and John Karanicolas and Rhiju Das and Jens Meiler and Tanja Kortemme and Jeffrey J Gray and Brian Kuhlman and David Baker and Philip Bradley},

doi = {10.1016/B978-0-12-381270-4.00019-6},

issn = {1557-7988},

year  = {2011},

date = {2011-01-01},

journal = {Methods Enzymol},

volume = {487},

pages = {545--574},

abstract = {We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21731610,

title = {RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite},

author = {Sarel J Fleishman and Andrew Leaver-Fay and Jacob E Corn and Eva-Maria Strauch and Sagar D Khare and Nobuyasu Koga and Justin Ashworth and Paul Murphy and Florian Richter and Gordon Lemmon and Jens Meiler and David Baker},

doi = {10.1371/journal.pone.0020161},

issn = {1932-6203},

year  = {2011},

date = {2011-01-01},

journal = {PLoS One},

volume = {6},

number = {6},

pages = {e20161},

abstract = {Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20939100,

title = {Computational modeling of laminin N-terminal domains using sparse distance constraints from disulfide bonds and chemical cross-linking},

author = {Stefan Kalkhof and Sebastian Haehn and Mats Paulsson and Neil Smyth and Jens Meiler and Andrea Sinz},

doi = {10.1002/prot.22848},

issn = {1097-0134},

year  = {2010},

date = {2010-12-01},

journal = {Proteins},

volume = {78},

number = {16},

pages = {3409--3427},

abstract = {Basement membranes are thin extracellular protein layers, which separate endothelial and epithelial cells from the underlying connecting tissue. The main noncollagenous components of basement membranes are laminins, trimeric glycoproteins, which form polymeric networks by interactions of their N-terminal (LN) domains; however, no high-resolution structure of laminin LN domains exists so far. To construct models for laminin β(1) and γ(1) LN domains, 14 potentially suited template structures were determined using fold recognition methods. For each target/template-combination comparative models were created with Rosetta. Final models were selected based on their agreement with experimentally obtained distance constraints from natural cross-links, that is, disulfide bonds as well as chemical cross-links obtained from reactions with two amine-reactive cross-linkers. We predict that laminin β(1) and γ(1) LN domains share the galactose-binding domain-like fold.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20732812,

title = {3D-QSAR CoMFA study of benzoxazepine derivatives as mGluR5 positive allosteric modulators},

author = {Edward W Lowe and Alysia Ferrebee and Alice L Rodriguez and P Jeffrey Conn and Jens Meiler},

doi = {10.1016/j.bmcl.2010.07.061},

issn = {1464-3405},

year  = {2010},

date = {2010-10-01},

journal = {Bioorg Med Chem Lett},

volume = {20},

number = {19},

pages = {5922--5924},

abstract = {Positive allosteric modulation of the metabotropic glutamate receptor subtype 5 was studied by conducting a comparative molecular field analysis on 118 benzoxazepine derivatives. The model with the best predictive ability retained significant cross-validated correlation coefficients of q(2) = 0.58 (r(2) = 0.81) yielding a standard error of 0.20 in pEC(50) for this class of compounds. The subsequent contour maps highlight the structural features pertinent to the bioactivity values of benzoxazepines.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20525731,

title = {Design and directed evolution of a dideoxy purine nucleoside phosphorylase},

author = {David P Nannemann and Kristian W Kaufmann and Jens Meiler and Brian O Bachmann},

doi = {10.1093/protein/gzq033},

issn = {1741-0134},

year  = {2010},

date = {2010-08-01},

journal = {Protein Eng Des Sel},

volume = {23},

number = {8},

pages = {607--616},

abstract = {Purine nucleoside phosphorylase (PNP) catalyzes the synthesis and phosphorolysis of purine nucleosides, interconverting nucleosides with their corresponding purine base and ribose-1-phosphate. While PNP plays significant roles in human and pathogen physiology, we are interested in developing PNP as a catalyst for the formation of nucleoside analog drugs of clinical relevance. Towards this aim, we describe the engineering of human PNP to accept 2',3'-dideoxyinosine (ddI, Videx((R))) as a substrate for phosphorolysis using a combination of site-directed mutagenesis and directed evolution. In human PNP, we identified a single amino acid, Tyr-88, as a likely modulator of ribose selectivity. RosettaLigand was employed to calculate binding energies for substrate and substrate analog transition state complexes for single mutants of PNP where Tyr-88 was replaced with another amino acid. In parallel, these mutants were generated by site-directed mutagenesis, expressed and purified. A tyrosine to phenylalanine mutant (Y88F) was predicted by Rosetta to improve PNP catalytic activity with respect to ddI. Kinetic characterization of this mutant determined a 9-fold improvement in k(cat) and greater than 2-fold reduction in K(M). Subsequently, we used directed evolution to select for improved variants of PNP-Y88F in Escherichia coli cell extracts resulting in an additional 3-fold improvement over the progenitor strain. The engineered PNP may form the basis for catalysts and pathways for the biosynthesis of ddI.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20414370,

title = {Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening},

author = {Ralf Mueller and Alice L Rodriguez and Eric S Dawson and Mariusz Butkiewicz and Thuy T Nguyen and Stephen Oleszkiewicz and Annalen Bleckmann and C David Weaver and Craig W Lindsley and P Jeffrey Conn and Jens Meiler},

doi = {10.1021/cn9000389},

issn = {1948-7193},

year  = {2010},

date = {2010-04-01},

journal = {ACS Chem Neurosci},

volume = {1},

number = {4},

pages = {288--305},

abstract = {Selective potentiators of glutamate response at metabotropic glutamate receptor subtype 5 (mGluR5) have exciting potential for the development of novel treatment strategies for schizophrenia. A total of 1,382 compounds with positive allosteric modulation (PAM) of the mGluR5 glutamate response were identified through high-throughput screening (HTS) of a diverse library of 144,475 substances utilizing a functional assay measuring receptor-induced intracellular release of calcium. Primary hits were tested for concentration-dependent activity, and potency data (EC(50) values) were used for training artificial neural network (ANN) quantitative structure-activity relationship (QSAR) models that predict biological potency from the chemical structure. While all models were trained to predict EC(50), the quality of the models was assessed by using both continuous measures and binary classification. Numerical descriptors of chemical structure were used as input for the machine learning procedure and optimized in an iterative protocol. The ANN models achieved theoretical enrichment ratios of up to 38 for an independent data set not used in training the model. A database of approximately 450,000 commercially available drug-like compounds was targeted in a virtual screen. A set of 824 compounds was obtained for testing based on the highest predicted potency values. Biological testing found 28.2% (232/824) of these compounds with various activities at mGluR5 including 177 pure potentiators and 55 partial agonists. These results represent an enrichment factor of 23 for pure potentiation of the mGluR5 glutamate response and 30 for overall mGluR5 modulation activity when compared with those of the original mGluR5 experimental screening data (0.94% hit rate). The active compounds identified contained 72% close derivatives of previously identified PAMs as well as 28% nontrivial derivatives of known active compounds.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20235548,

title = {Practically useful: what the Rosetta protein modeling suite can do for you},

author = {Kristian W Kaufmann and Gordon H Lemmon and Samuel L Deluca and Jonathan H Sheehan and Jens Meiler},

doi = {10.1021/bi902153g},

issn = {1520-4995},

year  = {2010},

date = {2010-04-01},

journal = {Biochemistry},

volume = {49},

number = {14},

pages = {2987--2998},

abstract = {The objective of this review is to enable researchers to use the software package Rosetta for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with Rosetta. For each of these six tasks, we provide a tutorial that illustrates a basic Rosetta protocol. The Rosetta method was originally developed for de novo protein structure prediction and is regularly one of the best performers in the community-wide biennial Critical Assessment of Structure Prediction. Predictions for protein domains with fewer than 125 amino acids regularly have a backbone root-mean-square deviation of better than 5.0 A. More impressively, there are several cases in which Rosetta has been used to predict structures with atomic level accuracy better than 2.5 A. In addition to de novo structure prediction, Rosetta also has methods for molecular docking, homology modeling, determining protein structures from sparse experimental NMR or EPR data, and protein design. Rosetta has been used to accurately design a novel protein structure, predict the structure of protein-protein complexes, design altered specificity protein-protein and protein-DNA interactions, and stabilize proteins and protein complexes. Most recently, Rosetta has been used to solve the X-ray crystallographic phase problem.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid19772383,

title = {BCL::contact-low confidence fold recognition hits boost protein contact prediction and de novo structure determination},

author = {Mert Karakaş and Nils Woetzel and Jens Meiler},

doi = {10.1089/cmb.2009.0030},

issn = {1557-8666},

year  = {2010},

date = {2010-02-01},

journal = {J Comput Biol},

volume = {17},

number = {2},

pages = {153--168},

abstract = {Knowledge of all residue-residue contacts within a protein allows determination of the protein fold. Accurate prediction of even a subset of long-range contacts (contacts between amino acids far apart in sequence) can be instrumental for determining tertiary structure. Here we present BCL::Contact, a novel contact prediction method that utilizes artificial neural networks (ANNs) and specializes in the prediction of medium to long-range contacts. BCL::Contact comes in two modes: sequence-based and structure-based. The sequence-based mode uses only sequence information and has individual ANNs specialized for helix-helix, helix-strand, strand-helix, strand-strand, and sheet-sheet contacts. The structure-based mode combines results from 32-fold recognition methods with sequence information to a consensus prediction. The two methods were presented in the 6(th) and 7(th) Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiments. The present work focuses on elucidating the impact of fold recognition results onto contact prediction via a direct comparison of both methods on a joined benchmark set of proteins. The sequence-based mode predicted contacts with 42% accuracy (7% false positive rate), while the structure-based mode achieved 45% accuracy (2% false positive rate). Predictions by both modes of BCL::Contact were supplied as input to the protein tertiary structure prediction program Rosetta for a benchmark of 17 proteins with no close sequence homologs in the protein data bank (PDB). Rosetta created higher accuracy models, signified by an improvement of 1.3 A on average root mean square deviation (RMSD), when driven by the predicted contacts. Further, filtering Rosetta models by agreement with the predicted contacts enriches for native-like fold topologies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid20581474,

title = {Unique gating properties of C. elegans ClC anion channel splice variants are determined by altered CBS domain conformation and the R-helix linker},

author = {Sonya Dave and Jonathan H Sheehan and Jens Meiler and Kevin Strange},

doi = {10.4161/chan.4.4.12445},

issn = {1933-6969},

year  = {2010},

date = {2010-01-01},

journal = {Channels (Austin)},

volume = {4},

number = {4},

pages = {289--301},

abstract = {All eukaryotic and some prokaryotic ClC anion transport proteins have extensive cytoplasmic C-termini containing two cystathionine-β-synthase (CBS) domains. CBS domain secondary structure is highly conserved and consists of two α-helices and three β-strands arranged as β1-α1-β2-β3-α2. ClC CBS domain mutations cause muscle and bone disease and alter ClC gating. However, the precise functional roles of CBS domains and the structural bases by which they regulate ClC function are poorly understood. CLH-3a and CLH-3b are C. elegans ClC anion channel splice variants with strikingly different biophysical properties. Splice variation occurs at cytoplasmic N- and C-termini and includes several amino acids that form α2 of the second CBS domain (CBS2). We demonstrate that interchanging α2 between CLH-3a and CLH-3b interchanges their gating properties. The "R-helix" of ClC proteins forms part of the ion-conducting pore and selectivity filter and is connected to the cytoplasmic C-terminus via a short stretch of cytoplasmic amino acids termed the "R-helix linker". C-terminus conformation changes could cause R-helix structural rearrangements via this linker. X-ray structures of three ClC protein cytoplasmic C-termini suggest that α2 of CBS2 and the R-helix linker could be closely apposed and may therefore interact. We found that mutating apposing amino acids in α2 and the R-helix linker of CLH-3b was sufficient to give rise to CLH-3a-like gating. We postulate that the R-helix linker interacts with CBS2 α2, and that this putative interaction provides a pathway by which cytoplasmic C-terminus conformational changes induce conformational changes in membrane domains that in turn modulate ClC function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid21961051,

title = {Discovery and characterization of novel subtype-selective allosteric agonists for the investigation of M(1) receptor function in the central nervous system},

author = {Evan P Lebois and Thomas M Bridges and L Michelle Lewis and Eric S Dawson and Alexander S Kane and Zixiu Xiang and Satyawan B Jadhav and Huiyong Yin and J Phillip Kennedy and Jens Meiler and Colleen M Niswender and Carrie K Jones and P Jeffrey Conn and C David Weaver and Craig W Lindsley},

doi = {10.1021/cn900003h},

issn = {1948-7193},

year  = {2010},

date = {2010-01-01},

journal = {ACS Chem Neurosci},

volume = {1},

number = {2},

pages = {104--121},

abstract = {Cholinergic transmission in the forebrain is mediated primarily by five subtypes of muscarinic acetylcholine receptors (mAChRs), termed M(1)-M(5). Of the mAChR subtypes, M(1) is among the most heavily expressed in regions that are critical for learning and memory, and has been viewed as the most critical mAChR subtype for memory and attention mechanisms. Unfortunately, it has been difficult to develop selective activators of M(1) and other individual mAChR subtypes, which has prevented detailed studies of the functional roles of selective activation of M(1). Using a functional HTS screen and subsequent diversity-oriented synthesis approach we have discovered a novel series of highly selective M(1) allosteric agonists. These compounds activate M(1) with EC(50) values in the 150 nM to 500 nM range and have unprecedented, clean ancillary pharmacology (no substantial activity at 10μM across a large panel of targets). Targeted mutagenesis revealed a potentially novel allosteric binding site in the third extracellular loop of the M(1) receptor for these allosteric agonists. Optimized compounds, such as VU0357017, provide excellent brain exposure after systemic dosing and have robust in vivo efficacy in reversing scopolamine-induced deficits in a rodent model of contextual fear conditioning. This series of selective M(1) allosteric agonists provides critical research tools to allow dissection of M(1)-mediated effects in the CNS and potential leads for novel treatments for Alzheimer's disease and schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid19652920,

title = {Accessing ns-micros side chain dynamics in ubiquitin with methyl RDCs},

author = {Christophe Farès and Nils-Alexander Lakomek and Korvin F A Walter and Benedikt T C Frank and Jens Meiler and Stefan Becker and Christian Griesinger},

doi = {10.1007/s10858-009-9354-7},

issn = {1573-5001},

year  = {2009},

date = {2009-09-01},

journal = {J Biomol NMR},

volume = {45},

number = {1-2},

pages = {23--44},

abstract = {This study presents the first application of the model-free analysis (MFA) (Meiler in J Am Chem Soc 123:6098-6107, 2001; Lakomek in J Biomol NMR 34:101-115, 2006) to methyl group RDCs measured in 13 different alignment media in order to describe their supra-tau (c) dynamics in ubiquitin. Our results indicate that methyl groups vary from rigid to very mobile with good correlation to residue type, distance to backbone and solvent exposure, and that considerable additional dynamics are effective at rates slower than the correlation time tau (c). In fact, the average amplitude of motion expressed in terms of order parameters S (2) associated with the supra-tau (c) window brings evidence to the existence of fluctuations contributing as much additional mobility as those already present in the faster ps-ns time scale measured from relaxation data. Comparison to previous results on ubiquitin demonstrates that the RDC-derived order parameters are dominated both by rotameric interconversions and faster libration-type motions around equilibrium positions. They match best with those derived from a combined J-coupling and residual dipolar coupling approach (Chou in J Am Chem Soc 125:8959-8966, 2003) taking backbone motion into account. In order to appreciate the dynamic scale of side chains over the entire protein, the methyl group order parameters are compared to existing dynamic ensembles of ubiquitin. Of those recently published, the broadest one, namely the EROS ensemble (Lange in Science 320:1471-1475, 2008), fits the collection of methyl group order parameters presented here best. Last, we used the MFA-derived averaged spherical harmonics to perform highly-parameterized rotameric searches of the side chains conformation and find expanded rotamer distributions with excellent fit to our data. These rotamer distributions suggest the presence of concerted motions along the side chains.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}