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Computational protein–ligand docking is well-known to be prone to inaccuracies in input receptor structures, and it is challenging to obtain good docking results with computationally predicted receptor structures (e.g. through homology modeling). Here we introduce a fragment-based docking method and test if it reduces requirements on the accuracy of an input receptor structures relative to non-fragment docking approaches. In this method, small rigid fragments are docked first using AutoDock Vina to generate a large number of favorably docked poses spanning the receptor binding pocket. Then a graph theory maximum clique algorithm is applied to find combined sets of docked poses of different fragment types onto which the complete ligand can be properly aligned. On the basis of these alignments, possible binding poses of complete ligand are determined. This docking method is first tested for bound docking on a series of Cytochrome P450 (CYP450) enzyme–substrate complexes, in which experimentally determined receptor structures are used. For all complexes tested, ligand poses of less than 1 Å root mean square deviations (RMSD) from the actual binding positions can be recovered. Then the method is tested for unbound docking with modeled receptor structures for a number of protein–ligand complexes from different families including the very recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protease. For all complexes, poses with RMSD less than 3 Å from actual binding positions can be recovered. Our results suggest that for docking with approximately modeled receptor structures, fragment-based methods can be more effective than common complete ligand docking approaches. [ABSTRACT FROM AUTHOR]

G protein-coupled receptors (GPCR) comprise the largest family of membrane proteins and are of considerable interest as targets for drug development. However, many GPCR structures remain unsolved. To address the structural ambiguity of these receptors, computational tools such as homology modeling and loop modeling are often employed to generate predictive receptor structures. Here we combined both methods to benchmark a protocol incorporating homology modeling based on a locally selected template and extracellular loop modeling that additionally evaluates the presence of template ligands during these modeling steps. Ligands were also docked using three docking methods and two pose selection methods to elucidate an optimal ligand pose selection method. Results suggest that local template-based homology models followed by loop modeling produce more accurate and predictive receptor models than models produced without loop modeling, with decreases in average receptor and ligand RMSD of 0.54 Å and 2.91 Å, respectively. Ligand docking results showcased the ability of MOE induced fit docking to produce ligand poses with atom root-mean-square deviation (RMSD) values at least 0.20 Å lower (on average) than the other two methods benchmarked in this study. In addition, pose selection methods (software-based scoring, ligand complementation) selected lower RMSD poses with MOE induced fit docking than either of the other methods (averaging at least 1.57 Å lower), indicating that MOE induced fit docking is most suited for docking into GPCR homology models in our hands. In addition, target receptor models produced with a template ligand present throughout the modeling process most often produced target ligand poses with RMSD values ≤ 4.5 Å and Tanimoto coefficients > 0.6 after selection based on ligand complementation than target receptor models produced in the absence of template ligands. Overall, the findings produced by this study support the use of local template homology modeling in combination with de novo ECL2 modeling in the presence of a ligand from the template crystal structure to generate GPCR models intended to study ligand binding interactions. [ABSTRACT FROM AUTHOR]

Among still comparatively few G protein-coupled receptors, the adenosine A2A receptor has been co-crystallized with several ligands, agonists as well as antagonists. It can thus serve as a template with a well-described orthosteric ligand binding region for adenosine receptors. As not all subtypes have been crystallized yet, and in order to investigate the usability of homology models in this context, multiple adenosine A1 receptor (A1AR) homology models had been previously obtained and a library of lead-like compounds had been docked. As a result, a number of potent and one selective ligand toward the intended target have been identified. However, in in vitro experimental verification studies, many ligands also bound to the A2AAR and the A3AR subtypes. In this work we asked the question whether a classification of the ligands according to their selectivity was possible based on docking scores. Therefore, we built an A3AR homology model and docked all previously found ligands to all three receptor subtypes. As a metric, we employed an in vitro/in silico selectivity ranking system based on taxicab geometry and obtained a classification model with reasonable separation. In the next step, the method was validated with an external library of, selective ligands with similarly good performance. This classification system might also be useful in further screens. [ABSTRACT FROM AUTHOR]

We investigated the Gi-coupled A3 adenosine receptor (A3AR) activation mechanism by running 7.2 µs of molecular dynamics (MD) simulations. Based on homology to G protein-coupled receptor (GPCR) structures, three constitutively active mutant (CAM) and the wild-type (WT) A3ARs in the apo form were modeled. Conformational signatures associated with three different receptor states (inactive R, active R*, and bound to Gi protein mimic) were predicted by analyzing and comparing the CAMs with WT receptor and by considering site-directed mutagenesis data. Detected signatures that were correlated with receptor state included: Persistent salt-bridges involving key charged residues for activation (including a novel, putative ionic lock), rotameric state of conserved W6.48, and Na+ ions and water molecules present. Active-coupled state signatures similar to the X-ray structures of β2 adrenergic receptor-Gs protein and A2AAR-mini-Gs and the recently solved cryo-EM A1AR–Gi complexes were found. Our MD analysis suggests that constitutive activation might arise from the D1073.49–R1083.50 ionic lock destabilization in R and the D1073.49–R1113.53 ionic lock stabilization in R* that presumably lowers the energy barrier associated with an R to R* transition. This study provides new opportunities to understand the underlying interactions of different receptor states of other Gi protein-coupled GPCRs. [ABSTRACT FROM AUTHOR]

G protein-coupled receptors (GPCR) are important drug discovery targets. Despite progress, many GPCR structures have not yet been solved. For these targets, comparative modeling is used in virtual ligand screening to prioritize experimental efforts. However, the structure of extracellular loop 2 (ECL2) is often poorly predicted. This is significant due to involvement of ECL2 in ligand binding for many Class A GPCR. Here we examine the performance of loop modeling protocols available in the Rosetta (cyclic coordinate descent [CCD], KIC with fragments [KICF] and next generation KIC [NGK]) and Molecular Operating Environment (MOE) software suites (de novo search). ECL2 from GPCR crystal structures served as the structure prediction targets and were divided into four sets depending on loop length. Results suggest that KICF and NGK sampled and scored more loop models with sub-angstrom and near-atomic accuracy than CCD or de novo search for loops of 24 or fewer residues. None of the methods were able to sample loop conformations with near-atomic accuracy for the longest targets ranging from 25 to 32 residues based on 1000 models generated. For these long loop targets, increased conformational sampling is necessary. The strongly conserved disulfide bond between Cys3.25 and Cys45.50 in ECL2 proved an effective filter. Setting an upper limit of 5.1 Å on the S–S distance improved the lowest RMSD model included in the top 10 scored structures in Groups 1–4 on average between 0.33 and 1.27 Å. Disulfide bond formation and geometry optimization of ECL2 provided an additional incremental benefit in structure quality. [ABSTRACT FROM AUTHOR]

ERG-associated protein with the SET domain (ESET/SET domain bifurcated 1/SETDB1/KMT1E) is a histone lysine methyltransferase (HKMT) and it preferentially tri-methylates lysine 9 of histone H3 (H3K9me3). SETDB1/ESET leads to heterochromatin condensation and epigenetic gene silencing. These functional changes are reported to correlate with Huntington's disease (HD) progression and mood-related disorders which make SETDB1/ESET a viable drug target. In this context, the present investigation was performed to identify novel peptide-competitive small molecule inhibitors of the SETDB1/ESET by a combined in silico-in vitro approach. A ligand-based pharmacophore model was built and employed for the virtual screening of ChemDiv and Asinex database. Also, a human SETDB1/ESET homology model was constructed to supplement the data further. Biological evaluation of the selected 21 candidates singled out 5 compounds exhibiting a notable reduction of the H3K9me3 level via inhibitory potential of SETDB1/ESET activity in SETDB1/ESET-inducible cell line and HD striatal cells. Later on, we identified two compounds as final hits that appear to have neuronal effects without cytotoxicity based on the result from MTT assay. These compounds hold the calibre to become the future lead compounds and can provide structural insights into more SETDB1/ESET-focused drug discovery research. Moreover, these SETDB1/ESET inhibitors may be applicable for the preclinical study to ameliorate neurodegenerative disorders via epigenetic regulation. Graphical Abstract: [ABSTRACT FROM AUTHOR]

We have previously demonstrated that the secreted prolyl oligopeptidase of Trypanosoma cruzi (POPTc80) is involved in the infection process by facilitating parasite migration through the extracellular matrix. We have built a 3D structural model where POPTc80 is formed by a catalytic α/β-hydrolase domain and a β-propeller domain, and in which the substrate docks at the inter-domain interface, suggesting a 'jaw opening' gating access mechanism. This preliminary model was refined by molecular dynamics simulations and next used for a virtual screening campaign, whose predictions were tested by standard binding assays. This strategy was successful as all 13 tested molecules suggested from the in silico calculations were found out to be active POPTc80 inhibitors in the micromolar range (lowest K at 667 nM). This work paves the way for future development of innovative drugs against Chagas disease. [ABSTRACT FROM AUTHOR]

Permeation of ions through open channels and their accessibility to pore-targeting drugs depend on the pore cross-sectional dimensions, which are known only for static X-ray and cryo-EM structures. Here, we have built homology models of the closed, open and desensitized αβγ GABA receptor (GABAR). The models are based, respectively, on the X-ray structure of α glycine receptor (α GlyR), cryo-EM structure of α GlyR and X-ray structure of β GABAR. We employed Monte Carlo energy minimizations to explore how the pore lumen may increase due to repulsions of flexible side chains from a variable-diameter electroneutral atom (an expanding sphere) pulled through the pore. The expanding sphere computations predicted that the pore diameter averaged along the permeation pathway is larger by approximately 3 Å than that computed for the models with fixed sidechains. Our models predict three major pore constrictions located at the levels of −2′, 9′ and 20′ residues. Residues around the −2′ and 9′ rings are known to form the desensitization and activation gates of GABAR. Our computations predict that the 20′ ring may also serve as GABAR gate whose physiological role is unclear. The side chain flexibility of residues −2′, 9′ and 20′ and hence the dimensions of the constrictions depend on the GABAR functional state. [ABSTRACT FROM AUTHOR]

Snake venom metalloproteinases are important toxins that play fundamental roles during envenomation. They share a structurally similar catalytic domain, but with diverse hemorrhagic capabilities. To understand the structural basis for this difference, we build and compare two dynamical models, one for the hemorrhagic atroxlysin-I from Bothrops atrox and the other for the non-hemorraghic leucurolysin-a from Bothrops leucurus. The analysis of the extended molecular dynamics simulations shows some changes in the local structure, flexibility and surface determinants that can contribute to explain the different hemorrhagic activity of the two enzymes. In agreement with previous results, the long Ω-loop (from residue 149 to 177) has a larger mobility in the hemorrhagic protein. In addition, we find some potentially-relevant differences at the base of the S′ pocket, what may be interesting for the structure-based design of new anti-venom agents. However, the sharpest differences in the computational models of atroxlysin-I and leucurolysin-a are observed in the surface electrostatic potential around the active site region, suggesting thus that the hemorrhagic versus non-hemorrhagic activity is probably determined by protein surface determinants. [ABSTRACT FROM AUTHOR]

Calcium-activated chloride channels (CaCCs) play vital roles in a variety of physiological processes. Transmembrane protein 16A (TMEM16A) has been confirmed as the molecular counterpart of CaCCs which greatly pushes the molecular insights of CaCCs forward. However, the detailed mechanism of Ca binding and activating the channel is still obscure. Here, we utilized a combination of computational and electrophysiological approaches to discern the molecular mechanism by which Ca regulates the gating of TMEM16A channels. The simulation results show that the first intracellular loop serves as a Ca binding site including D439, E444 and E447. The experimental results indicate that a novel residue, E447, plays key role in Ca binding. Compared with WT TMEM16A, E447Y produces a 30-fold increase in EC of Ca activation and leads to a 100-fold increase in Ca concentrations that is needed to fully activate the channel. The following steered molecular dynamic (SMD) simulation data suggests that the mutations at 447 reduce the Ca dissociation energy. Our results indicated that both the electrical property and the size of the side-chain at residue 447 have significant effects on Ca dependent gating of TMEM16A. [ABSTRACT FROM AUTHOR]

Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane proteins including the GPCRs, based on templates of low sequence identity, remains an eminent challenge. Current approaches addressing this challenge adopt the philosophy of 'modeling first, refinement next'. In the present work, we developed an alternative modeling approach through the novel application of available multiple templates. First, conserved inter-residue interactions are derived from each additional template through conservation analysis of each template-target pairwise alignment. Then, these interactions are converted into distance restraints and incorporated in the homology modeling process. This approach was applied to modeling of the human β adrenergic receptor using the bovin rhodopsin and the human protease-activated receptor 1 as templates and improved model quality was demonstrated compared to the homology model generated by standard single-template and multiple-template methods. This method of 'refined restraints first, modeling next', provides a fast and complementary way to the current modeling approaches. It allows rational identification and implementation of additional conserved distance restraints extracted from multiple templates and/or experimental data, and has the potential to be applicable to modeling of all helical transmembrane proteins. [ABSTRACT FROM AUTHOR]

Proteins from halophilic archaea, which live in extreme saline conditions, have evolved to remain folded, active and stable at very high ionic strengths. Understanding the mechanism of haloadaptation is the first step toward engineering of halostable biomolecules. Amylases are one of the main enzymes used in industry. Yet, no three-dimensional structure has been experimentally resolved for α-amylases from halophilic archaea. In this study, homology structure modeling of α-amylases from the halophilic archaea Haloarcula marismortui, Haloarcula hispanica, and Halalkalicoccus jeotgali were performed. The resulting models were subjected to energy minimization, evaluation, and structural analysis. Calculations of the amino acid composition, salt bridges and hydrophobic interactions were also performed and compared to a set of non-halophilic counterparts. It clearly appeared that haloarchaeal α-amylases exhibited lower propensities for helix formation and higher propensities for coil-forming regions. Furthermore, they could maintain a folded and stable conformation in high salt concentration through highly negative charged surface with over representation of acidic residues, especially Asp, and low hydrophobicity with increase of salt bridges and decrease in hydrophobic interactions on the protein surface. This study sheds some light on the stability of α-amylases from halophilic archaea and provides strong basis not only to understand haloadaptation mechanisms of proteins in microorganisms from hypersalines environments but also for biotechnological applications. [ABSTRACT FROM AUTHOR]

Isoflavone reductase-like proteins (IRLs) are enzymes with key roles in the metabolism of diverse flavonoids. Last identified olive pollen allergen (Ole e 12) is an IRL relevant for allergy amelioration, since it exhibits high prevalence among atopic patients. The goals of this study are the characterization of (A) the structural-functionality of Ole e 12 with a focus in its catalytic mechanism, and (B) its molecular allergenicity by extensive analysis using different molecular computer-aided approaches covering (1) physicochemical properties and functional-regulatory motifs, (2) sequence analysis, 2-D and 3D structural homology modeling comparative study and molecular docking, (3) conservational and evolutionary analysis, (4) catalytic mechanism modeling, and (5) sequence, structure-docking based B-cell epitopes prediction, while T-cell epitopes were predicted by inhibitory concentration and binding score methods. Structural-based detailed features, phylogenetic and sequences analysis have identified Ole e 12 as phenylcoumaran benzylic ether reductase. A catalytic mechanism has been proposed for Ole e 12 which display Lys133 as one of the conserved residues of the IRLs catalytic tetrad (Asn-Ser-Tyr-Lys). Structure characterization revealed a conserved protein folding among plants IRLs. However, sequence polymorphism significantly affected residues involved in the catalytic pocket structure and environment (cofactor and substrate interaction-recognition). It might also be responsible for IRLs isoforms functionality and regulation, since micro-heterogeneities affected physicochemical and posttranslational motifs. This polymorphism might have large implications for molecular differences in B- and T-cells epitopes of Ole e 12, and its identification may help designing strategies to improve the component-resolving diagnosis and immunotherapy of pollen and food allergy through development of molecular tools. [ABSTRACT FROM AUTHOR]

Twelve homology models of the human M muscarinic receptor using different sets of templates have been designed using the Prime program or the modeller program and compared to crystallographic structure (PDB:3UON). The best models were obtained using single template of the closest published structure, the M muscarinic receptor (PDB:4DAJ). Adding more (structurally distant) templates led to worse models. Data document a key role of the template in homology modeling. The models differ substantially. The quality checks built into the programs do not correlate with the RMSDs to the crystallographic structure and cannot be used to select the best model. Re-docking of the antagonists present in crystallographic structure and relative binding energy estimation by calculating MM/GBSA in Prime and the binding energy function in YASARA suggested it could be possible to evaluate the quality of the orthosteric binding site based on the prediction of relative binding energies. Although estimation of relative binding energies distinguishes between relatively good and bad models it does not indicate the best one. On the other hand, visual inspection of the models for known features and knowledge-based analysis of the intramolecular interactions allows an experimenter to select overall best models manually. [ABSTRACT FROM AUTHOR]

The lymphoid tyrosine phosphatase (LYP), encoded by the PTPN22 gene, has recently been identified as a promising drug target for human autoimmunity diseases. Like the majority of protein-tyrosine phosphatases LYP can adopt two functionally distinct forms determined by the conformation of the WPD-loop. The WPD-loop plays an important role in the catalytic dephosphorylation by protein-tyrosine phosphatases. Here we investigate the binding modes of two chemotypes of small molecule LYP inhibitors with respect to both protein conformations using computational modeling. To evaluate binding in the active form, we built a LYP protein structure model of high quality. Our results suggest that the two different compound classes investigated, bind to different conformations of the LYP phosphatase domain. Binding to the closed form is facilitated by an interaction with Asp195 in the WPD-loop, presumably stabilizing the active conformation. The analysis presented here is relevant for the design of inhibitors that specifically target either the closed or the open conformation of LYP in order to achieve better selectivity over phosphatases with similar binding sites. [ABSTRACT FROM AUTHOR]

The transient receptor potential vanilloid subtype 1 (TRPV1) is a non-selective cation channel composed of four monomers with six transmembrane helices (TM1-TM6). TRPV1 is found in the central and peripheral nervous system, and it is an important therapeutic target for pain relief. We describe here the construction of a tetrameric homology model of rat TRPV1 (rTRPV1). We experimentally evaluated by mutational analysis the contribution of residues of rTRPV1 contributing to ligand binding by the prototypical TRPV1 agonists, capsaicin and resiniferatoxin (RTX). We then performed docking analysis using our homology model. The docking results with capsaicin and RTX showed that our homology model was reliable, affording good agreement with our mutation data. Additionally, the binding mode of a simplified RTX (sRTX) ligand as predicted by the modeling agreed well with those of capsaicin and RTX, accounting for the high binding affinity of the sRTX ligand for TRPV1. Through the homology modeling, docking and mutational studies, we obtained important insights into the ligand-receptor interactions at the molecular level which should prove of value in the design of novel TRPV1 ligands. [ABSTRACT FROM AUTHOR]

The P2Y receptor (P2YR) is an ADP-activated G protein-coupled receptor (GPCR) that is an important target for antithrombotic drugs. Three homology models of P2YR were compared, based on different GPCR structural templates: bovine rhodopsin (bRHO), human A adenosine receptor (AAR), and human C-X-C chemokine receptor type 4 (CXCR4). By criteria of sequence analysis (25.6% identity in transmembrane region), deviation from helicity in the second transmembrane helix (TM2), docked poses of ligands highlighting the role of key residues, accessibility of a conserved disulfide bridge that is reactive toward irreversibly-binding antagonists, and the presence of a shared disulfide bridge between the third extracellular loop (EL3) and the N-terminus, the CXCR4-based model appeared to be the most consistent with known characteristics of P2YR. The docked poses of agonist 2MeSADP and charged anthraquinone antagonist PSB-0739 in the binding pocket of P2YR-CXC agree with previously published site-directed mutagenesis studies of Arg256 and Lys280. A sulfonate at position 2 of the anthraquinone core created a strong interaction with the Lys174(EL2) side chain. The docking poses of the irreversibly-binding, active metabolite (existing as two diastereoisomers in vivo) of the clinically utilized antagonist Clopidogrel were compared. The free thiol group of the 4S diastereoisomer, but not the 4R isomer, was found in close proximity (~4.7 Å) to the sulfur atom of a disulfide bridge involving Cys175, suggesting greater activity in covalent binding. Therefore, ligand docking to the CXCR4-based model of the P2YR predicted poses of both reversibly and irreversibly-binding small molecules, consistent with observed pharmacology and mutagenesis studies. [ABSTRACT FROM AUTHOR]

n in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters. [ABSTRACT FROM AUTHOR]

Folding correctors of F508del-CFTR were discovered by in silico structure-based screening utilizing homology models of CFTR. The intracellular segment of CFTR was modeled and three cavities were identified at inter-domain interfaces: (1) Interface between the two Nucleotide Binding Domains (NBDs); (2) Interface between NBD1 and Intracellular Loop (ICL) 4, in the region of the F508 deletion; (3) multi-domain interface between NBD1:2:ICL1:2:4. We hypothesized that compounds binding at these interfaces may improve the stability of the protein, potentially affecting the folding yield or surface stability. In silico structure-based screening was performed at the putative binding-sites and a total of 496 candidate compounds from all three sites were tested in functional assays. A total of 15 compounds, representing diverse chemotypes, were identified as F508del folding correctors. This corresponds to a 3% hit rate, ~tenfold higher than hit rates obtained in corresponding high-throughput screening campaigns. The same binding sites also yielded potentiators and, most notably, compounds with a dual corrector-potentiator activity (dual-acting). Compounds harboring both activity types may prove to be better leads for the development of CF therapeutics than either pure correctors or pure potentiators. To the best of our knowledge this is the first report of structure-based discovery of CFTR modulators. [ABSTRACT FROM AUTHOR]

CXCR4 is a G-protein coupled receptor for CXCL12 that plays an important role in human immunodeficiency virus infection, cancer growth and metastasization, immune cell trafficking and WHIM syndrome. In the absence of an X-ray crystal structure, theoretical modeling of the CXCR4 receptor remains an important tool for structure-function analysis and to guide the discovery of new antagonists with potential clinical use. In this study, the combination of experimental data and molecular modeling approaches allowed the development of optimized ligand-receptor models useful for elucidation of the molecular determinants of small molecule binding and functional antagonism. The ligand-guided homology modeling approach used in this study explicitly re-shaped the CXCR4 binding pocket in order to improve discrimination between known CXCR4 antagonists and random decoys. Refinement based on multiple test-sets with small compounds from single chemotypes provided the best early enrichment performance. These results provide an important tool for structure-based drug design and virtual ligand screening of new CXCR4 antagonists. [ABSTRACT FROM AUTHOR]

The Small Heterodimer Partner (SHP) is an orphan nuclear receptor and an atypical member of the nuclear receptor superfamily Since its discovery, a growing body of evidences have pointed out a pivotal role for SHP in the transcriptional regulation of a variety of target genes involved in diverse metabolic pathways. While we have previously developed a homology model of the structure of SHP that was instrumental to identify a putative ligand binding pocket and suggest the possibility of the development of synthetic modulators, others reported that some atypical retinoids may represent the first synthetic ligands for this receptor. In this work, we report a combined computational approach aimed at shedding further lights on the binding mode and mechanism of action of some atypical retinoids as ligands of SHP. The results have been instrumental to design mutagenesis experiments whose preliminary data suggest the presence of a functional site in SHP as defined by residues Phe96, Arg138 and Arg238. While further experimental studies are ongoing, these findings constitute the basis for the design and identification of novel synthetic modulators of SHP functions. [ABSTRACT FROM AUTHOR]

CYP2D6 is an important enzyme that is involved in first pass metabolism and is responsible for metabolizing ~25% of currently marketed drugs. A homology model of CYP2D6 was built using X-ray structures of ligand-bound CYP2C5 complexes as templates. This homology model was used in docking studies to rationalize and predict the site of metabolism of known CYP2D6 substrates. While the homology model was generally found to be in good agreement with the recently solved apo (ligand-free) X-ray structure of CYP2D6, significant differences between the structures were observed in the B′ and F–G helical region. These structural differences are similar to those observed between ligand-free and ligand-bound structures of other CYPs and suggest that these conformational changes result from induced-fit adaptations upon ligand binding. By docking to the homology model using Glide, it was possible to identify the correct site of metabolism for a set of 16 CYP2D6 substrates 85% of the time when the 5 top scoring poses were examined. On the other hand, docking to the apo CYP2D6 X-ray structure led to a loss in accuracy in predicting the sites of metabolism for many of the CYP2D6 substrates considered in this study. These results demonstrate the importance of describing substrate-induced conformational changes that occur upon binding. The best results were obtained using Glide SP with van der Waals scaling set to 0.8 for both the receptor and ligand atoms. A discussion of putative binding modes that explain the distribution of metabolic sites for substrates, as well as a relationship between the number of metabolic sites and substrate size, are also presented. In addition, analysis of these binding modes enabled us to rationalize the typical hydroxylation and O-demethylation reactions catalyzed by CYP2D6 as well as the less common N-dealkylation. [ABSTRACT FROM AUTHOR]

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor–ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered. [ABSTRACT FROM AUTHOR]

The success of structure-based drug design relies on accurate protein modeling where one of the key issues is the modeling and refinement of loops. This study takes a critical look at modeled loops, determining the effect of re-sampling side-chains after the loop conformation has been generated. The results are evaluated in terms of backbone and side-chain conformations with respect to the native loop. While models can contain loops with high quality backbone conformations, the side-chain orientations could be poor, and therefore unsuitable for ligand docking and structure-based design. In this study, we report on the ability to model loop side-chains accurately using a variety of commercially available algorithms that include rotamer libraries, systematic torsion scans and knowledge-based methods. [ABSTRACT FROM AUTHOR]

Inducible, microsomal prostaglandin E synthase 1 (mPGES-1), the terminal enzyme in the prostaglandin (PG) biosynthetic pathway, constitutes a promising therapeutic target for the development of new anti-inflammatory drugs. To elucidate structure–function relationships and to enable structure-based design, an mPGES-1 homology model was developed using the three-dimensional structure of the closest homologue of the MAPEG family (Membrane Associated Proteins in Eicosanoid and Glutathione metabolism), mGST-1. The ensuing model of mPGES-1 is a homo-trimer, with each monomer consisting of four membrane-spanning segments. Extensive structure refinement revealed an inter-monomer salt bridge (K26-E77) as well as inter-helical interactions within each monomer, including polar hydrogen bonds (e.g. T78-R110-T129) and hydrophobic π-stacking (F82-F103-F106), all contributing to the overall stability of the homo-trimer of mPGES-1. Catalytic co-factor glutathione (GSH) was docked into the mPGES-1 model by flexible optimization of both the ligand and the protein conformations, starting from the initial location ascertained from the mGST-1 structure. Possible binding site for the substrate, prostaglandin H2 (PGH2), was identified by systematically probing the refined molecular structure of mPGES-1. A binding model was generated by induced fit docking of PGH2 in the presence of GSH. The homology model prescribes three potential inhibitor binding sites per mPGES-1 trimer. This was further confirmed experimentally by equilibrium dialysis study which generated a binding stoichiometric ratio of approximately three inhibitor molecules to three mPGES-1 monomers. The structural model that we have derived could serve as a useful tool for structure-guided design of inhibitors for this emergently important therapeutic target. [ABSTRACT FROM AUTHOR]

Pyruvate phosphate dikinase (PPDK) is the key enzyme essential for the glycolytic pathway in most common and perilous parasite Entamoeba histolytica. Inhibiting the function of this enzyme could control the wide spread of intestinal infections caused by Entamoeba histolytica in humans. With this objective, we modeled the three dimensional structure of the PPDK protein. We used templates with 51% identity and 67% similarity to employ homology-modeling approach. Stereo chemical quality of protein structure was validated by protein structure validation program PROCHECK and VERIFY3D. Experimental proof available in literature along with the in silico studies indicated Lys21, Arg91, Asp323, Glu325 and Gln337 to be the probable active sites in the target protein. Virtual screening was carried out using the genetic docking algorithm GOLD and a consensus scoring function X-Score to substantiate the prediction. The small molecule libraries (ChemDivision database, Diversity dataset, Kinase inhibitor database) were used for screening process. Along with the high scoring results, the interaction studies provided promising ligands for future experimental screening to inhibit the function of PPDK in Entamoeba histolytica. Further, the phylogeny study was carried out to assess the possibility of using the proposed ligands as inhibitors in related pathogens. [ABSTRACT FROM AUTHOR]

Lipoxygenases (LOXs) are a group of enzymes involved in the oxygenation of polyunsaturated fatty acids. Among these 5-lipoxygenase (5-LOX) is the key enzyme leading to the formation of pharmacologically important leukotrienes and lipoxins, the mediators of inflammatory and allergic disorders. In view of close functional similarity to mammalian lipoxygenase, potato 5-LOX is used extensively. In this study, the homology modeling technique has been used to construct the structure of potato 5-LOX. The amino acid sequence identity between the target protein and sequence of template protein 1NO3 (soybean LOX-3) searched from NCBI protein BLAST was 63%. Based on the template structure, the protein model was constructed by using the Homology program in InsightII. The protein model was briefly refined by energy minimization steps and validated using Profile-3D, ERRAT and PROCHECK. The results showed that 99.3% of the amino acids were in allowed regions of Ramachandran plot, suggesting that the model is accurate and its stereochemical quality good. Like all LOXs, 5-LOX also has a two-domain structure, the small N-terminal β-barrel domain and a larger catalytic domain containing a single atom of non-heme iron coordinating with His525, His530, His716 and Ile864. Asn720 is present in the fifth coordination position of iron. The sixth coordination position faces the open cavity occupied here by the ligands which are docked. Our model of the enzyme is further validated by examining the interactions of earlier reported inhibitors and by energy minimization studies which were carried out using molecular mechanics calculations. Four ligands, nordihydroguaiaretic acid (NDGA) having IC50 of 1.5 μM and analogs of benzyl propargyl ethers having IC50 values of 760 μM, 45 μM, and no inhibition respectively were selected for our docking and energy minimization studies. Our results correlated well with the experimental data reported earlier, which proved the quality of the model. This model generated can be further used for the design and development of more potent 5-LOX inhibitors. [ABSTRACT FROM AUTHOR]

Essential for viral replication and highly conserved among poxviridae, the vaccinia virus I7L ubiquitin-like proteinase (ULP) is an attractive target for development of smallpox antiviral drugs. At the same time, the I7L proteinase exemplifies several interesting challenges from the rational drug design perspective. In the absence of a published I7L X-ray structure, we have built a detailed 3D model of the I7L ligand binding site (S2–S2′ pocket) based on exceptionally high structural conservation of this site in proteases of the ULP family. The accuracy and limitations of this model were assessed through comparative analysis of available X-ray structures of ULPs, as well as energy based conformational modeling. The 3D model of the I7L ligand binding site was used to perform covalent docking and VLS of a comprehensive library of about 230,000 available ketone and aldehyde compounds. Out of 456 predicted ligands, 97 inhibitors of I7L proteinase activity were confirmed in biochemical assays (∼20% overall hit rate). These experimental results both validate our I7L ligand binding model and provide initial leads for rational optimization of poxvirus I7L proteinase inhibitors. Thus, fragments predicted to bind in the prime portion of the active site can be combined with fragments on non-prime side to yield compounds with improved activity and specificity. [ABSTRACT FROM AUTHOR]

Mycobacterium tuberculosis 1-deoxy- d-xylulose-5-phosphate reductoisomerase ( MtDXR) is a potential target for antitubercular chemotherapy. In the absence of its crystallographic structure, our aim was to develop a structural model of MtDXR. This will allow us to gain early insight into the structure and function of the enzyme and its likely binding to ligands and cofactors and thus, facilitate structure-based inhibitor design. To achieve this goal, initial models of MtDXR were generated using MODELER. The best quality model was refined using a series of minimizations and molecular dynamics simulations. A protein–ligand complex was also developed from the initial homology model of the target protein by including information about the known ligand as spatial restraints and optimizing the mutual interactions between the ligand and the binding site. The final model was evaluated on the basis of its ability to explain several site-directed mutagenesis data. Furthermore, a comparison of the homology model with the X-ray structure published in the final stages of the project shows excellent agreement and validates the approach. The knowledge gained from the current study should prove useful in the design and development of inhibitors as potential novel therapeutic agents against tuberculosis by either de novo drug design or virtual screening of large chemical databases. [ABSTRACT FROM AUTHOR]

Aldosterone is synthesised by aldosterone synthase (CYP11B2). CYP11B2 has a highly homologous isoform, steroid 11β-hydroxylase (CYP11B1), which is responsible for the biosynthesis of aldosterone precursors and glucocorticoids. To investigate aldosterone biosynthesis and facilitate the search for selective CYP11B2 inhibitors, we constructed three-dimensional models for CYP11B1 and CYP11B2 for both human and rat. The models were constructed based on the crystal structure of Pseudomonas Putida CYP101 and Oryctolagus Cuniculus CYP2C5. Small steric active site differences between the isoforms were found to be the most important determinants for the regioselective steroid synthesis. A possible explanation for these steric differences for the selective synthesis of aldosterone by CYP11B2 is presented. The activities of the known CYP11B inhibitors metyrapone, R-etomidate, R-fadrazole and S-fadrazole were determined using assays of V79MZ cells that express human CYP11B1 and CYP11B2, respectively. By investigating the inhibitors in the human CYP11B models using molecular docking and molecular dynamics simulations we were able to predict a similar trend in potency for the inhibitors as found in the in vitro assays. Importantly, based on the docking and dynamics simulations it is possible to understand the enantioselectivity of the human enzymes for the inhibitor fadrazole, the R-enantiomer being selective for CYP11B2 and the S-enantiomer being selective for CYP11B1. [ABSTRACT FROM AUTHOR]

Ongoing efforts to model P2Y receptors for extracellular nucleotides, i.e., endogenous ADP, ATP, UDP, UTP, and UDP-glucose, were summarized and correlated for the eight known subtypes. The rhodopsin-based homology modeling of the P2Y receptors is supported by a growing body of site-directed mutagenesis data, mainly for P2Y1 receptors. By comparing molecular models of the P2Y receptors, it was concluded that nucleotide binding could occur in the upper part of the helical bundle, with the ribose moiety accommodated between transmembrane domain (TM) 3 and TM7. The nucleobase was oriented towards TM1, TM2, and TM7, in the direction of the extracellular side of the receptor. The phosphate chain was oriented towards TM6, in the direction of the extracellular loops (ELs), and was coordinated by three critical cationic residues. In particular, in the P2Y1, P2Y2, P2Y4, and P2Y6 receptors the nucleotide ligands had very similar positions. ADP in the P2Y12 receptor was located deeper inside the receptor in comparison to other subtypes, and the uridine moiety of UDP-glucose in the P2Y14 receptor was located even deeper and shifted toward TM7. In general, these findings are in agreement with the proposed binding site of small molecules to other class A GPCRs. [ABSTRACT FROM AUTHOR]

Human 11β-hydroxysteroid dehydrogenase type 1 (11βHSD1) catalyzes the interconversion of cortisone into active cortisol. 11βHSD1 inhibition is a tempting target for the treatment of a host of human disorders that might benefit from blockade of glucocorticoid action, such as obesity, metabolic syndrome, and diabetes type 2. Here, we report an in silico screening study aimed at identifying new selective inhibitors of human 11βHSD1 enzyme. In the first step, homology modeling was employed to build the 3D structure of 11βHSD1. Further, molecular docking was used to validate the predicted model by showing that it was able to discriminate between known 11βHSD1 inhibitors or substrates and non-inhibitors. The homology model was found to reproduce closely the crystal structure that became publicly available in the final stages of this work. Finally, we carried out structure-based virtual screening experiments on both the homology model and the crystallographic structure with a database of 114’000 natural molecules. Among these, 15 molecules were consistently selected as inhibitors based on both the model and crystal structures of the enzyme, implying a good quality for the homology model. Among these putative 11βHSD1 inhibitors, two were flavonone derivatives that have already been shown to be potent inhibitors of the enzyme. [ABSTRACT FROM AUTHOR]

For AIDS therapy, there are currently a number of compounds available for multiple targets already approved by the FDA and in clinic, e.g. protease inhibitors, reverse transcriptase inhibitors (NRTI, NNRTI), fusion inhibitors, CCR4, CCR5 among others. Some pharmaceuticals act against the virus before the entrance of HIV into the host cells. One of these targets is the glucosidase protein. This novel fusion target has been recently explored because the synthesis of viral glycoproteins depends on the activity of enzymes, such as glucosidase and transferase, for the elaboration of the polysaccharides. In this work we have built an homology model of Saccharomyces cerevisiae glucosidase and superimposed all relevant glucosidase-like enzymes in complex with carbohydrates, and calculated as well molecular interaction fields in our S. cerevisiae active site model. Our results suggest that there are two saccharide binding sites which are the most important for the binding of inhibitors with this family of enzymes which supports the possibility of inhibitors containing only two sugar units. Based on these results, we have proposed a novel pseudo-dissacharide which is a potential pharmaceutical for AIDS treatment. [ABSTRACT FROM AUTHOR]

As an effort to develop therapeutics for cancer treatments, a number of effective histone deacetylase inhibitors with structural diversity have been discovered. To gain insight into optimizing the activity of an identified lead compound, a computational protocol sequentially involving homology modeling, docking experiments, molecular dynamics simulation, and free energy perturbation calculations was applied for rationalizing the relative activities of known histone deacetylase inhibitors. With the newly developed force field parameters for the coordination environment of the catalytic zinc ion in hand, the computational strategy proved to be successful in predicting the rank orders for 12 derivatives of three hydroxamate-based inhibitor scaffolds with indole amide, pyrrole, and sulfonamide moieties. The results showed that the free energy of an inhibitor in aqueous solution should be an important factor in determining the binding free energy. Hence, in order to enhance the inhibitory activity by adding or substituting a chemical group, the increased stabilization in solution due to the structural changes must be overcome by a stronger enzyme-inhibitor interaction. It was also found that to optimize inhibitor potency, the hydrophobic head of an inhibitor should be elongated or enlarged so that it can interact with Pro29 and His28 that are components of the flexible loop at the top of the active site. [ABSTRACT FROM AUTHOR]

Adenosine is a naturally occurring purine nucleoside that has a wide variety of well-documented regulatory functions and physiological roles. Selective activation of the adenosine A1 receptor has drawn attention in drug discovery for the therapeutic effects on neural and cardiovascular disorders. We have developed a model of the human A1 adenosine receptor using bovine rhodopsin as a template. A flexible docking approach has been subsequently carried out for evaluating the molecular interactions of twenty-one selective A1 agonists with the receptor model. The results of these studies are consistent with mutational and biochemical data. In particular, they highlight a wide hydrogen-bonding network between the nucleoside portion of the ligands and the A1 receptor as well as key amino acids for hydrophobic interactions with the different N6-groups of the agonists. The models presented here provide a detailed molecular map for the selective stimulation of the adenosine A1 receptor subtype and a steady basis for the rational design of new A1 selective ligands. [ABSTRACT FROM AUTHOR]

A new method is described for generating all-atom protein structures from Cα-atom information. The method, which combines both local structural trace alignments and comparative side chain modeling with ab initio side chain modeling, makes use of both the virtual-bond and the dipole-path methods. Provided that 3D structures of structurally and functionally related proteins exist, the method presented here is highly suitable for generating all-atom coordinates of partly solved, low-resolution crystal structures. Particularly the active site region can be modeled accurately with this procedure, which enables investigation of the binding modes of different classes of ligands with molecular dynamics simulations. The method is applied to the trace of Streptococcus pneumoniae, in order to construct an all-atom structure of the transpeptidase domain. Since after generation of full coordinates of the transpeptidase domain the structure had been solved to 2.4 Å resolution, new X-ray coordinates for the worst modeled loop (residues T370 to M386; 17 out of a total number of 351 residues constituting the transpeptidase domain) were incorporated, as kindly provided by Dr. Dideberg. The structure was relaxed with molecular dynamics simulations and simulated annealing methods. The RMS deviation between the 144 aligned Cα-atoms and the corresponding ones in the originally solved 3.5 Å resolution crystal structure was 0.98. The 351 Cα-atoms of the whole transpeptidase domain of the final model showed an RMS deviation of 1.58. The Ramachandran plot showed that 79.3% of the residues are in the most favored regions, with only 1.0% occurring in disallowed regions. The model presented here can be used to investigate the three-dimensional influences of mutations around the active site of PBP2 x. [ABSTRACT FROM AUTHOR]

The recombinant antibody, pSAN13.4.1, has a unique T cell like specificity; it binds an Influenza Hemagglutinin octapeptide (Ha255−262) in an MHC (H-2Kk)-restricted manner, and a detailed comparison of the fine specificity of pSAN13.4.1 with the fine specificity of two Ha255−262-specific, H-2Kk-restricted T cell hybridomas has supported this contention. A three-dimensional model of pSAN13.4.1 has been derived by homology modeling techniques. Subsequently, the structure of the pSAN13.4.1 antibody in complex with the antigenic Ha-Kk ligand was derived after a flexible and automated docking of the MHC-peptide pair into the Fab combining site. Interestingly, the most energetically favored binding mode shows numerous analogies to the recently determined recognition of class I MHC-peptide complexes by αβ T cell receptors (TCRs). The pSAN13.4.1 also binds diagonally across the MHC binding groove but is more deeply anchored to the peptide-MHC (pep/MHC) ligand than TCRs, notably through numerous interactions of its heavy chain. The present model accounts well for the experimentally determined binding affinity of a set of 144 single amino acid substituted Ha analogues and the observed shared specificity between the pSAN antibody and two different T cell receptors for the Ha-Kk antigenic ligand. Analogies and differences between Fab and TCR recognition are explained by dissecting the binding role of each chain of the immune receptors as well as the contribution of all peptide amino acids. [ABSTRACT FROM AUTHOR]

A three-dimensional model of the complex between an Influenza Hemagglutinin peptide, Ha255−262, and its restricting element, the mouse major histocompatibility complex (MHC) class I molecule, Kk, was built by homology modeling and subsequently refined by simulated annealing and restrained molecular dynamics. Next, three-dimensional models of two different T cell receptors (TCRs) both specific for the Ha255−262/Kk complex were generated based on previously published TCR X-ray structures. Finally, guided by the recently published X-ray structures of ternary TCR/peptide/MHC-I complexes, the TCR models were successfully docked into the Ha255−262/Kk model. We have previously used a systematic and exhaustive panel of 144 single amino acid substituted analogs to analyze both MHC binding and T cell recognition of the parental viral peptide. This large body of experimental data was used to evaluate the models. They were found to account well for the experimentally obtained data, lending considerable support to the proposed models and suggesting a universal docking mode for αβ TCRs to MHC-peptide complexes. Such models may also be useful in guiding future rational experimentation. [ABSTRACT FROM AUTHOR]