An Assessment of Quaternary Structure Functionality in Homomer Protein Complexes.

It has been recently suggested that a significant fraction of homomer protein-protein interfaces evolve neutrally, without contributing to function, due to a hydrophobic bias in missense mutations. However, the fraction of such gratuitous complexes is currently unknown. Here, we quantified the fraction of homodimers where multimerization is unlikely to contribute to their biochemical function. We show that: 1) ligand binding-site structure predicts whether a homomer is functional or not; the vast majority of homodimers with multichain binding-sites (MBS) are likely to be functional, while in homodimers with single-chain binding-sites (SBS) and small to medium interfaces, quaternary structure is unlikely to be functional in a significant fraction-35%, even up to 42%-of complexes; 2) the hydrophobicity of interfaces changes little with the strength of selection, and the amino acid composition of interfaces is shaped by the "hydrophobic ratchet" in both types, but they are not in a strict equilibrium with mutations; particularly cysteines are much more abundant in mutations than in interfaces or surfaces; 3) in MBS homomers, the interfaces are conserved, while in a high fraction of SBS homomers, the interface is not more conserved than the solvent-accessible surface; and 4) MBS homomer interfaces coevolve more strongly with ligand binding sites than the interfaces of SBS homomers, and MBS complexes have higher capacity to transfer information from ligands across the interfaces than SBS homomers, explaining the enrichment of allostery in the former.

Activation pathway of a G protein-coupled receptor uncovers conformational intermediates as targets for allosteric drug design.

G protein-coupled receptors (GPCRs) are the most common proteins targeted by approved drugs. A complete mechanistic elucidation of large-scale conformational transitions underlying the activation mechanisms of GPCRs is of critical importance for therapeutic drug development. Here, we apply a combined computational and experimental framework integrating extensive molecular dynamics simulations, Markov state models, site-directed mutagenesis, and conformational biosensors to investigate the conformational landscape of the angiotensin II (AngII) type 1 receptor (AT1 receptor) - a prototypical class A GPCR-activation. Our findings suggest a synergistic transition mechanism for AT1 receptor activation. A key intermediate state is identified in the activation pathway, which possesses a cryptic binding site within the intracellular region of the receptor. Mutation of this cryptic site prevents activation of the downstream G protein signaling and ß-arrestin-mediated pathways by the endogenous AngII octapeptide agonist, suggesting an allosteric regulatory mechanism. Together, these findings provide a deeper understanding of AT1 receptor activation at an atomic level and suggest avenues for the design of allosteric AT1 receptor modulators with a broad range of applications in GPCR biology, biophysics, and medicinal chemistry.

Analytical comparability assessment on glycosylation of ziv-aflibercept and the biosimilar candidate.

Ziv-aflibercept (aflibercept) is a recombinant fusion protein which combines the portions of human vascular endothelial growth factor receptors extracellular domains fused to the Fc portion of human IgG1. It is a highly sialylated glycoprotein with 5 N-glycosylation sites. In this study, a comprehensive strategy for comparability study of the complex glycosylation was developed between aflibercept and the biosimilar candidate including the investigations on N-glycosylation sites, site occupancy, site-specific glycoforms, released glycans and sialic acids. The results indicated that same N-glycosylation sites were identified, site occupancy were 100% except N68 site, site-specific glycoforms and released glycans showed similar glycan species, contents of NANA were at a same level for two products. Minor differences were found between two products. The biosimilar candidate presented lower level of aglycosylation, lower level of glycans containing one terminal sialic acid, higher level of glycans containing two terminal sialic acids, higher level of G0F and Man5, lower level of G1F and G2F compared with aflibercept. However, further studies exhibited no differences were observed in the cell-based biological potency and Fc effector function. Moreover, the biosimilar candidate showed a similar pharmacokinetics curve and bioequivalence compared with aflibercept.

Mechanism of pore opening in the calcium-activated chloride channel TMEM16A.

The anion channel TMEM16A is activated by intracellular Ca2+ in a highly cooperative process. By combining electrophysiology and autocorrelation analysis, we investigated the mechanism of channel activation and the concurrent rearrangement of the gate in the narrow part of the pore. Features in the fluctuation characteristics of steady-state current indicate the sampling of intermediate conformations that are successively occupied during gating. The initial step is related to conformational changes induced by Ca2+ binding, which is ensued by rearrangements that open the pore. Mutations in the gate shift the equilibrium of transitions in a manner consistent with a progressive destabilization of this region during pore opening. We come up with a mechanism of channel activation where the binding of Ca2+ induces conformational changes in the protein that, in a sequential manner, propagate from the binding site and couple to the gate in the narrow pore to allow ion permeation.

Ligand-bound glutamine binding protein assumes multiple metastable binding sites with different binding affinities.

Protein dynamics plays key roles in ligand binding. However, the microscopic description of conformational dynamics-coupled ligand binding remains a challenge. In this study, we integrate molecular dynamics simulations, Markov state model (MSM) analysis and experimental methods to characterize the conformational dynamics of ligand-bound glutamine binding protein (GlnBP). We show that ligand-bound GlnBP has high conformational flexibility and additional metastable binding sites, presenting a more complex energy landscape than the scenario in the absence of ligand. The diverse conformations of GlnBP demonstrate different binding affinities and entail complex transition kinetics, implicating a concerted ligand binding mechanism. Single molecule fluorescence resonance energy transfer measurements and mutagenesis experiments are performed to validate our MSM-derived structure ensemble as well as the binding mechanism. Collectively, our study provides deeper insights into the protein dynamics-coupled ligand binding, revealing an intricate regulatory network underlying the apparent binding affinity.

Adaptive landscape flattening allows the design of both enzyme: Substrate binding and catalytic power.

Designed enzymes are of fundamental and technological interest. Experimental directed evolution still has significant limitations, and computational approaches are a complementary route. A designed enzyme should satisfy multiple criteria: stability, substrate binding, transition state binding. Such multi-objective design is computationally challenging. Two recent studies used adaptive importance sampling Monte Carlo to redesign proteins for ligand binding. By first flattening the energy landscape of the apo protein, they obtained positive design for the bound state and negative design for the unbound. We have now extended the method to design an enzyme for specific transition state binding, i.e., for its catalytic power. We considered methionyl-tRNA synthetase (MetRS), which attaches methionine (Met) to its cognate tRNA, establishing codon identity. Previously, MetRS and other synthetases have been redesigned by experimental directed evolution to accept noncanonical amino acids as substrates, leading to genetic code expansion. Here, we have redesigned MetRS computationally to bind several ligands: the Met analog azidonorleucine, methionyl-adenylate (MetAMP), and the activated ligands that form the transition state for MetAMP production. Enzyme mutants known to have azidonorleucine activity were recovered by the design calculations, and 17 mutants predicted to bind MetAMP were characterized experimentally and all found to be active. Mutants predicted to have low activation free energies for MetAMP production were found to be active and the predicted reaction rates agreed well with the experimental values. We suggest the present method should become the paradigm for computational enzyme design.

Doc2b Ca2+ binding site mutants enhance synaptic release at rest at the expense of sustained synaptic strength.

Communication between neurons involves presynaptic neurotransmitter release which can be evoked by action potentials or occur spontaneously as a result of stochastic vesicle fusion. The Ca2+-binding double C2 proteins Doc2a and -b were implicated in spontaneous and asynchronous evoked release, but the mechanism remains unclear. Here, we compared wildtype Doc2b with two Ca2+ binding site mutants named DN and 6A, previously classified as gain- and loss-of-function mutants. They carry the substitutions D218,220N or D163,218,220,303,357,359A respectively. We found that both mutants bound phospholipids at low Ca2+ concentrations and were membrane-associated in resting neurons, thus mimicking a Ca2+-activated state. Their overexpression in hippocampal primary cultured neurons had similar effects on spontaneous and evoked release, inducing high mEPSC frequencies and increased short-term depression. Together, these data suggest that the DN and 6A mutants both act as gain-of-function mutants at resting conditions.

DNMHMM: An approach to identify the differential nucleosome regions in multiple cell types based on a Hidden Markov Model.

Nucleosome occupancy changes across cell types and environmental conditions and such changes often have profound influence in transcription. It's of importance to identify the differential nucleosome regions (DNRs) where the nucleosome occupancy level differs across cell types. Here we developed DNMHMM, a Hidden Markov Model (HMM) based algorithm, to detect the DNRs with nucleosomal DNA sequenced dataset. The performance evaluation indicates that DNMHMM is advisable for multi-cell type comparison. Upon testing this model in yeast mutants, where the modifiable histone residues were mutated into alanine, we found that DNA sequences of the dynamic nucleosomes lack 10-11 bp periodicities and harbor binding motifs of the nucleosome remodelling complex. Moreover, the highly expressed genes have more dynamic nucleosomes at promoters. We further compared nucleosome occupancy between resting and activated human CD4+ T cells with this model. It was revealed that during the activation of CD4+ T cells, dynamic nucleosomes are enriched at regulatory sites, hence, up to some extent can affect the gene expression level. Taken together, DNMHMM offers the possibility to access precise nucleosome dynamics among multiple cell types and also can describe the closer association between nucleosome and transcription.

Assessment of structurally and functionally high-risk nsSNPs impacts on human bone morphogenetic protein receptor type IA (BMPR1A) by computational approach.

BMPR1A (BMP type 1 receptor) is a transmembrane cell-surface receptor also known as ALK3 (activin-like kinases-3) encodes for a type I serine/threonine kinase receptor and a member of the transforming growth-factor ß-receptor (TGF-ß) super family. The BMPR1A has a significant interaction with BMP-2 for protein activity and also has a low affinity with growth and differentiation factor 5 (GDF5); positively regulates chondrocyte differentiation. The genetic variations can alter the structure and function of the BMPR1A gene that causes several diseases such as juvenile polyposis syndrome or hereditary cancer-predisposing syndrome. The current study was carried out to identify potential deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in BMPR1A by implementing different computational algorithms such as SIFT, PolyPhen2, SNAP2, PROVEAN, PhD-SNP, SNPs&GO, nsSNPAnalyzer, and P-Mut. From 205 nsSNPs in BMPR1A, 7 nsSNPs (C76Y, C124R, C124Y, C376Y, R443C, R480W, and W487R) were predicted as deleterious in 8 prediction algorithms. The Consurf analysis showed that selected 7 nsSNPs were present in the highly conserved regions. Molecular dynamics simulation analysis also performed to explore conformational changes in the variant structure with respect to its native structure. According to the MDS result, all variants flexibility and rigidity were unbalanced, which may alter the structural and functional behavior of the native protein. Although, three nsSNPs i.e., C124R, C376Y, and R443C have already been reported in patients associated with JPS, but their structural and functional molecular studies remain uncharacterized. Therefore, the findings of this study can provide a better understanding of uncharacterized nsSNPS and to find their association with disease susceptibility and also facilitate to the researchers for designing or developing the target dependent drugs.

Repetitive switching between DNA-binding modes enables target finding by the glucocorticoid receptor.

Transcription factor mobility is a determining factor in the regulation of gene expression. Here, we have studied the intranuclear dynamics of the glucocorticoid receptor (GR) by using fluorescence recovery after photobleaching and single-molecule microscopy. First, we have described the dynamic states in which the GR occurs. Second, we have analyzed the transitions between these states by using a continuous-time Markov chain model and functionally investigated these states by making specific mutations in the DNA-binding domain. This analysis revealed that the GR diffuses freely through the nucleus and, once it leaves this free diffusion state, most often enters a repetitive switching mode. In this mode it alternates between slow diffusion as a result of brief nonspecific DNA-binding events, and a state of stable binding to specific DNA target sites. This repetitive switching mechanism results in a compact search strategy that facilitates finding of DNA target sites by the GR.This article has an associated First Person interview with the first author of the paper.

Heterodimeric DNA motif synthesis and validations.

Bound by transcription factors, DNA motifs (i.e. transcription factor binding sites) are prevalent and important for gene regulation in different tissues at different developmental stages of eukaryotes. Although considerable efforts have been made on elucidating monomeric DNA motif patterns, our knowledge on heterodimeric DNA motifs are still far from complete. Therefore, we propose to develop a computational approach to synthesize a heterodimeric DNA motif from two monomeric DNA motifs. The approach is sequentially divided into two components (Phases A and B). In Phase A, we propose to develop the inference models on how two DNA monomeric motifs can be oriented and overlapped with each other at nucleotide level. In Phase B, given the two monomeric DNA motifs oriented, we further propose to develop DNA-binding family-specific input-output hidden Markov models (IOHMMs) to synthesize a heterodimeric DNA motif. To validate the approach, we execute and cross-validate it with the experimentally verified 618 heterodimeric DNA motifs across 49 DNA-binding family combinations. We observe that our approach can even "rescue" the existing heterodimeric DNA motif pattern (i.e. HOXB2_EOMES) previously published on Nature. Lastly, we apply the proposed approach to infer previously uncharacterized heterodimeric motifs. Their motif instances are supported by DNase accessibility, gene ontology, protein-protein interactions, in vivo ChIP-seq peaks, and even structural data from PDB. A public web-server is built for open accessibility and scientific impact. Its address is listed as follows: http://motif.cs.cityu.edu.hk/custom/MotifKirin.

Partner-specific prediction of RNA-binding residues in proteins: A critical assessment.

RNA-protein interactions play essential roles in regulating gene expression. While some RNA-protein interactions are "specific", that is, the RNA-binding proteins preferentially bind to particular RNA sequence or structural motifs, others are "non-RNA specific." Deciphering the protein-RNA recognition code is essential for comprehending the functional implications of these interactions and for developing new therapies for many diseases. Because of the high cost of experimental determination of protein-RNA interfaces, there is a need for computational methods to identify RNA-binding residues in proteins. While most of the existing computational methods for predicting RNA-binding residues in RNA-binding proteins are oblivious to the characteristics of the partner RNA, there is growing interest in methods for partner-specific prediction of RNA binding sites in proteins. In this work, we assess the performance of two recently published partner-specific protein-RNA interface prediction tools, PS-PRIP, and PRIdictor, along with our own new tools. Specifically, we introduce a novel metric, RNA-specificity metric (RSM), for quantifying the RNA-specificity of the RNA binding residues predicted by such tools. Our results show that the RNA-binding residues predicted by previously published methods are oblivious to the characteristics of the putative RNA binding partner. Moreover, when evaluated using partner-agnostic metrics, RNA partner-specific methods are outperformed by the state-of-the-art partner-agnostic methods. We conjecture that either (a) the protein-RNA complexes in PDB are not representative of the protein-RNA interactions in nature, or (b) the current methods for partner-specific prediction of RNA-binding residues in proteins fail to account for the differences in RNA partner-specific versus partner-agnostic protein-RNA interactions, or both.

Systems assessment of transcriptional regulation on central carbon metabolism by Cra and CRP.

Two major transcriptional regulators of carbon metabolism in bacteria are Cra and CRP. CRP is considered to be the main mediator of catabolite repression. Unlike for CRP, in vivo DNA binding information of Cra is scarce. Here we generate and integrate ChIP-exo and RNA-seq data to identify 39 binding sites for Cra and 97 regulon genes that are regulated by Cra in Escherichia coli. An integrated metabolic-regulatory network was formed by including experimentally-derived regulatory information and a genome-scale metabolic network reconstruction. Applying analysis methods of systems biology to this integrated network showed that Cra enables optimal bacterial growth on poor carbon sources by redirecting and repressing glycolysis flux, by activating the glyoxylate shunt pathway, and by activating the respiratory pathway. In these regulatory mechanisms, the overriding regulatory activity of Cra over CRP is fundamental. Thus, elucidation of interacting transcriptional regulation of core carbon metabolism in bacteria by two key transcription factors was possible by combining genome-wide experimental measurement and simulation with a genome-scale metabolic model.

Review and comparative assessment of sequence-based predictors of protein-binding residues.

Understanding of molecular mechanisms that govern protein-protein interactions and accurate modeling of protein-protein docking rely on accurate identification and prediction of protein-binding partners and protein-binding residues. We review over 40 methods that predict protein-protein interactions from protein sequences including methods that predict interacting protein pairs, protein-binding residues for a pair of interacting sequences and protein-binding residues in a single protein chain. We focus on the latter methods that provide residue-level annotations and that can be broadly applied to all protein sequences. We compare their architectures, inputs and outputs, and we discuss aspects related to their assessment and availability. We also perform first-of-its-kind comprehensive empirical comparison of representative predictors of protein-binding residues using a novel and high-quality benchmark data set. We show that the selected predictors accurately discriminate protein-binding and non-binding residues and that newer methods outperform older designs. However, these methods are unable to accurately separate residues that bind other molecules, such as DNA, RNA and small ligands, from the protein-binding residues. This cross-prediction, defined as the incorrect prediction of nucleic-acid- and small-ligand-binding residues as protein binding, is substantial for all evaluated methods and is not driven by the proximity to the native protein-binding residues. We discuss reasons for this drawback and we offer several recommendations. In particular, we postulate the need for a new generation of more accurate predictors and data sets, inclusion of a comprehensive assessment of the cross-predictions in future studies and higher standards of availability of the published methods.

aPPRove: An HMM-Based Method for Accurate Prediction of RNA-Pentatricopeptide Repeat Protein Binding Events.

Pentatricopeptide repeat containing proteins (PPRs) bind to RNA transcripts originating from mitochondria and plastids. There are two classes of PPR proteins. The [Formula: see text] class contains tandem [Formula: see text]-type motif sequences, and the [Formula: see text] class contains alternating [Formula: see text], [Formula: see text] and [Formula: see text] type sequences. In this paper, we describe a novel tool that predicts PPR-RNA interaction; specifically, our method, which we call aPPRove, determines where and how a [Formula: see text]-class PPR protein will bind to RNA when given a PPR and one or more RNA transcripts by using a combinatorial binding code for site specificity proposed by Barkan et al. Our results demonstrate that aPPRove successfully locates how and where a PPR protein belonging to the [Formula: see text] class can bind to RNA. For each binding event it outputs the binding site, the amino-acid-nucleotide interaction, and its statistical significance. Furthermore, we show that our method can be used to predict binding events for [Formula: see text]-class proteins using a known edit site and the statistical significance of aligning the PPR protein to that site. In particular, we use our method to make a conjecture regarding an interaction between CLB19 and the second intronic region of ycf3. The aPPRove web server can be found at www.cs.colostate.edu/~approve.

A pose prediction approach based on ligand 3D shape similarity.

Molecular docking predicts the best pose of a ligand in the target protein binding site by sampling and scoring numerous conformations and orientations of the ligand. Failures in pose prediction are often due to either insufficient sampling or scoring function errors. To improve the accuracy of pose prediction by tackling the sampling problem, we have developed a method of pose prediction using shape similarity. It first places a ligand conformation of the highest 3D shape similarity with known crystal structure ligands into protein binding site and then refines the pose by repacking the side-chains and performing energy minimization with a Monte Carlo algorithm. We have assessed our method utilizing CSARdock 2012 and 2014 benchmark exercise datasets consisting of co-crystal structures from eight proteins. Our results revealed that ligand 3D shape similarity could substitute conformational and orientational sampling if at least one suitable co-crystal structure is available. Our method identified poses within 2 Å RMSD as the top-ranking pose for 85.7 % of the test cases. The median RMSD for our pose prediction method was found to be 0.81 Å and was better than methods performing extensive conformational and orientational sampling within target protein binding sites. Furthermore, our method was better than similar methods utilizing ligand 3D shape similarity for pose prediction.

Binding site druggability assessment in fragment-based drug design.

Target druggability refers to the propensity that a particular target is amenable to bind high-affinity drug-like molecules. A robust yet accurate computational assessment of target druggability would greatly benefit the fields of chemical genomics and drug discovery. Here, we illustrate a structure-based computational protocol to quantitatively assess the target binding-site druggability via in silico screening a fragment-like compound library. In particular, we provide guidelines, suggestions, and critical thoughts on different aspects of this computational protocol, including: construction of fragment library, preparation of target structure, in silico fragment screening, and analysis of druggability.

Designing a small molecule erythropoietin mimetic.

Erythropoietin (EPO) is a protein made by the kidneys in response to low red blood cell count that is secreted into the bloodstream and binds to a receptor on hematopoietic stem cells in the bone marrow inducing them to become new red blood cells. EPO made with recombinant DNA technology was brought to market in the 1980s to treat anemia caused by kidney disease and cancer chemotherapy. Because EPO infusion was able to replace blood transfusions in many cases, it rapidly became a multibillion dollar per year drug and as the first biologic created with recombinant technology it launched the biotech industry. For many years intense research was focused on creating a small molecule orally available EPO mimetic. The Robert Wood Johnson (RWJ) group seemed to definitively establish that only large peptides with a minimum of 60 residues could replace EPO, as anything less was not a full agonist. An intense study of the published work led me to hypothesize that the size of the mimetic is not the real issue, but the symmetry making and breaking of the EPO receptor induced by the ligand is the key to activating the stem cells. This analysis meant that residues in the binding site of the receptor deemed absolutely essential for ligand binding and activation from mutagenesis experiments, were probably not really that important. My fundamental hypotheses were: (a) the symmetric state of the homodimeric receptor is the most stable state and thus must be the off-state, (b) a highly localized binding site exists at a pivot point where the two halves of the receptor meet, (c) small molecules can be created that have high potency for this site that will be competitive with EPO and thus can displace the protein-protein interaction, (d) small symmetric molecules will stabilize the symmetric off-state of the receptor, and (e) a key asymmetry in the small molecule will stabilize a mirror image asymmetry in the receptor resulting in the stabilization of the on-state and proliferation of the stem cells into red blood cells. Researchers at Amgen published a co-crystal structure of EPO bound to the EPO receptor, which has a beautiful twofold symmetry-it was argued that this is the active state of the receptor. Activating the EPO receptor with EPO induces an almost instantaneous shutdown mechanism to sharply curtail any proliferative signal transduction, and thus, my hypotheses lead to the conclusion that the Amgen co-crystal is actually the state after receptor downregulation and thus an off-state. To put these hypotheses to the test, my computational method of Simulated Annealing of Chemical Potential was run using the co-crystal created at RWJ, which is the receptor trapped in a partial agonist state. The simulations predicted a previously unknown high affinity binding site at the pivot point where the two halves of the dimeric receptor meet, and detailed analysis of the fragment patterns led to the prediction of a molecule less than 300 MW that is basically twofold symmetric with a chiral center on one side and not the other. Thus, to the degree that computer simulations can be taken seriously, these results support my hypotheses on small molecule receptor activation. When this small molecule was synthesized and tested it indeed induced human hematopoietic stems cells to become red blood cells. When the predicted chiral center of this molecule was removed eliminating its one asymmetric feature, the resulting molecule was an antagonist-it could potently displace hot EPO but could no longer induce stem cell proliferation and differentiation. These results provided strong support for my theories on how to create potent small molecule EPO agonists and were used to launch the new company Locus Pharmaceuticals. These molecules, however, required significant chemical changes in order to make them stable in other in vitro assays and to be in vivo active, but these alterations had to be done in a way that maintained the symmetry-asymmetry considerations that led to the creation of an in vitro active molecule. The combination of changing functional groups to enable good pharmacokinetics, while not changing the key intrinsic symmetry properties were never seriously pursued at Locus and the program died. Investigations into how red blood cells are created have occupied many prominent researchers for the entire twentieth century. In the second half of the century EPO was discovered and by the end of the century it became a blockbuster commercial product that launched the biotech revolution.

Assessment of gene promoter G­quadruplex binding and modulation by a naphthalene diimide derivative in tumor cells.

Naphthalene diimide (NDI) derivatives have shown high affinity for telomeric guanine (G)­quadruplexes and good antiproliferative activity in different human tumor experimental models. A trisubstituted compound (H­NDI­NMe2) has been reported to stabilize the telomeric G­quadruplex and to cause telomere dysfunction and downregulation of telomerase expression. We further investigated its mechanism of action by analyzing the capability of the molecule to interfere with the expression levels of oncogenes, such as MYC, telome-rase reverse transcriptase (TERT), KIT and BCL2, known to bear G­quadruplex­forming sequences within their promoters, in human tumor cell lines of different histological origin. Exposure to H­NDI­NMe2 resulted in a cell type­dependent perturbation of the expression levels of the four selected genes. Biophysical and molecular analyses revealed that H­NDI­NMe2 bound with high affinity and effectively stabilized mainly MYC and BCL2, which share long sequences and the possibility of multiple G­quadruplex folding. The mRNA levels of both genes, but not protein amounts were affected by NDI treatment. Global gene expression analysis showed modulation of genes implicated in telomere function and mechanisms of cancer; however, G­quadruplex­mediated regulation of gene expression by H­NDI­NMe2 was largely dependent on the cell context. These data indicate that a deeper knowledge on the molecular mechanisms and biological effects of G­quadruplex structures is still needed to help developing new effective anticancer agents.

Monte Carlo loop refinement and virtual screening of the thyroid-stimulating hormone receptor transmembrane domain.

Metropolis Monte Carlo (MMC) loop refinement has been performed on the three extracellular loops (ECLs) of rhodopsin and opsin-based homology models of the thyroid-stimulating hormone receptor transmembrane domain, a class A type G protein-coupled receptor. The Monte Carlo sampling technique, employing torsion angles of amino acid side chains and local moves for the six consecutive backbone torsion angles, has previously reproduced the conformation of several loops with known crystal structures with accuracy consistently less than 2 Å. A grid-based potential map, which includes van der Waals, electrostatics, hydrophobic as well as hydrogen-bond potentials for bulk protein environment and the solvation effect, has been used to significantly reduce the computational cost of energy evaluation. A modified sigmoidal distance-dependent dielectric function has been implemented in conjunction with the desolvation and hydrogen-bonding terms. A long high-temperature simulation with 2 kcal/mol repulsion potential resulted in extensive sampling of the conformational space. The slow annealing leading to the low-energy structures predicted secondary structure by the MMC technique. Molecular docking with the reported agonist reproduced the binding site within 1.5 Å. Virtual screening performed on the three lowest structures showed that the ligand-binding mode in the inter-helical region is dependent on the ECL conformations.