Data of the molecular dynamics simulations of mutations in the human connexin46 docking interface

The structure of hCx26 derived from the X-ray analysis was used to generate a homology model for hCx46. Interacting connexin molecules were used as starting model for the molecular dynamics (MD) simulation using NAMD and allowed us to predict the dynamic behavior of hCx46wt and the cataract related mutant hCx46N188T as well as two artificial mutants hCx46N188Q and hCx46N188D. Within the 50 ns simulation time the docked complex composed of the mutants dissociate while hCx46wt remains stable. The data indicates that one hCx46 molecule forms 5-7 hydrogen bonds (HBs) with the counterpart connexin of the opposing connexon. These HBs appear essential for a stable docking of the connexons as shown by the simulation of an entire gap junction channel and were lost for all the tested mutants. The data described here are related to the research article entitled "The cataract related mutation N188T in human connexin46 (hCx46) revealed a critical role for residue N188 in the docking process of gap junction channels" (Schadzek et al., 2015) [1].

Low molecular weight compounds from mushrooms as potential Bcl-2 inhibitors: docking and virtual screening studies

Mushrooms have the ability to promote apoptosis in tumor cell lines, but the mechanism of action is not quite well understood. Inhibition of the interaction between Bcl-2 and pro-apoptotic proteins could be an important step that leads to apoptosis. Therefore, the discovery of compounds with the ability to inhibit Bcl-2 is an ongoing research topic in drug discovery. In this study, we started by analyzing Bcl-2 experimental structures that are currently available in Protein Data Bank database. After analysis of the more relevant Bcl-2 structures, 4 were finally selected. An analysis of the best docking methodology was then performed using a cross-docking and re-docking approach while testing 2 docking softwares: AutoDock 4 and AutoDock Vina. Autodock4 provided the best docking results and was selected to perform a virtual screening study applied to a dataset of 40 Low Molecular Weight (LMW) compounds present in mushrooms, using the selected Bcl-2 structures as target. Results suggest that steroid are the more promising family, among the analyzed compounds, and may have the ability to interact with Bcl-2 and this way promoting tumor apoptosis. The steroids that presented lowest estimated binding energy (ΔG) were: Ganodermanondiol, Cerevisterol, Ganoderic Acid X and Lucidenic Lactone; with estimated ΔG values between -8,45 and -8,23 Kcal/mol. A detailed analysis of the docked conformation of these 4 top ranked LMW compounds was also performed and illustrates a plausible interaction between the 4 top raked steroids and Bcl-2, thus substantiating the accuracy of the predicted docked poses. Therefore, tumoral apoptosis promoted by mushroom might be related to Bcl-2 inhibition mediated by steroid family of compounds.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

Molecular modeling of Bt Cry1Ac (DI–DII)–ASAL (Allium sativum lectin)–fusion protein and its interaction with aminopeptidase N (APN) receptor of Manduca sexta

Genetic engineering of Bacillus thuringiensis (Bt) Cry proteins has resulted in the synthesis of various novel toxin proteins with enhanced insecticidal activity and specificity towards different insect pests. In this study, a fusion protein consisting of the DI–DII domains of Cry1Ac and garlic lectin (ASAL) has been designed in silico by replacing the DIII domain of Cry1Ac with ASAL. The binding interface between the DI–DII domains of Cry1Ac and lectin has been identified using protein–protein docking studies. Free energy of binding calculations and interaction profiles between the Cry1Ac and lectin domains confirmed the stability of fusion protein. A total of 18 hydrogen bonds was observed in the DI–DII–lectin fusion protein compared to 11 hydrogen bonds in the Cry1Ac (DI–DII–DIII) protein. Molecular mechanics/Poisson–Boltzmann (generalized-Born) surface area [MM/PB (GB) SA] methods were used for predicting free energy of interactions of the fusion proteins. Protein–protein docking studies based on the number of hydrogen bonds, hydrophobic interactions, aromatic–aromatic, aromatic–sulphur, cation–pi interactions and binding energy of Cry1Ac/fusion proteins with the aminopeptidase N (APN) of Manduca sexta rationalised the higher binding affinity of the fusion protein with the APN receptor compared to that of the Cry1Ac–APN complex, as predicted by ZDOCK, Rosetta and ClusPro analysis. The molecular binding interface between the fusion protein and the APN receptor is well packed, analogously to that of the Cry1Ac–APN complex. These findings offer scope for the design and development of customized fusion molecules for improved pest management in crop plants.

Design, Development, Synthesis, and Docking Analysis of 2-substituted Triclosan Analogs as Inhibitors for Plasmodium falciparum Enoyl-ACP Reductase

A structure-based approach has been adopted to develop 2'substituted analogs of triclosan. The Cl at position 2' in ring B of triclosan was chemically substituted with other functional groups like NH2, NO2 and their inhibitory potencies against PfENR were determined. The binding energies of the 2' substituted analogs of triclosan for enoyl-acyl carrier protein reductase (ENR) of Plasmodium falciparum were determined using Autodock. Based on the autodock results, we synthesized the potential compounds. The IC50 and inhibition constant (K-i) of 2' substituted analogs of triclosan were determined against purified PfENR. Among them, two compounds,2-(2'-Amino-4'-chloro-phenoxy)-5-chloro-phenol (compound 4) and 5-chloro-2-(4'-chloro-2'-nitro-phenoxy)-phenol) (compound 5) exhibited good potencies. Compound 4 followed uncompetitive inhibition kinetics with crotonoyl CoA and competitive with NADH. It was shown to have an IC50 of 110 nM; inhibition constant was 104 nM with the substrate and 61 nM with the cofactor. IC50 Of compound 5 was determined to be 229 nM. Compounds 4 and 5 showed significant inhibition of the parasite growth in P. falciparum culture. (C) 2009 IUBMB IUBMB Life, 61(11):1083-1091, 2009.

Functional interaction of diphenols with polyphenol oxidase - Molecular determinants of substrate/inhibitor specificity SO FEBS JOURNAL

Polyphenol oxidase (PPO) catalyzes the oxidation of o-diphenols to their respective quinones. The quinones autopolymerize to form dark pigments, an undesired effect. PPO is therefore the target for the development of antibrowning and antimelanization agents. A series of phenolic compounds experimentally evaluated for their binding affinity and inhibition constants were computationally docked to the active site of catechol oxidase. Docking studies suggested two distinct modes of binding, dividing the docked ligands into two groups. Remarkably, the first group corresponds to ligands determined to be substrates and the second group corresponds to reversible inhibitors. Analyses of the complexes provide structural explanations for correlating subtle changes in the position and nature of the substitutions on o-diphenols to their functional properties as substrates and inhibitors. Higher reaction rates and binding are reckoned by additional interactions of the substrates with key residues that line the hydrophobic cavity. The docking results suggest that inhibition of oxidation stems from an interaction between the aromatic carboxylic acid group and the apical His 109 of the four coordinates of the trigonal pyramidal coordination polyhedron of CuA. The spatial orientation of the hydroxyl in relation to the carboxylic group either allows a perfect fit in the substrate cavity, leading to inhibition, or because of a steric clash flips the molecule vertically, facilitating oxidation. This is the first study to explain, at the molecular level, the determinants Of substrate and inhibitor specificity of a catechol oxidase, thereby providing a platform for the design of selective inhibitors useful to both the food and pharmaceutical industries.

Using Correlated Parameters for Improved Ranking of Protein-Protein Docking Decoys

A successful protein-protein docking study culminates in identification of decoys at top ranks with near-native quaternary structures. However, this task remains enigmatic because no generalized scoring functions exist that effectively infer decoys according to the similarity to near-native quaternary structures. Difficulties arise because of the highly irregular nature of the protein surface and the significant variation of the nonbonding and solvation energies based on the chemical composition of the protein-protein interface. In this work, we describe a novel method combining an interface-size filter, a regression model for geometric compatibility (based on two correlated surface and packing parameters), and normalized interaction energy (calculated from correlated nonbonded and solvation energies), to effectively rank decoys from a set of 10,000 decoys. Tests on 30 unbound binary protein-protein complexes show that in 16 cases we can identify at least one decoy in top three ranks having <= 10 angstrom backbone root mean square deviation from true binding geometry. Comparisons with other state-of-art methods confirm the improved ranking power of our method without the use of any experiment-guided restraints, evolutionary information, statistical propensities, or modified interaction energy equations. Tests on 118 less-difficult bound binary protein-protein complexes with <= 35% sequence redundancy at the interface showed that in 77% cases, at least 1 in 10,000 decoys were identified with <= 5 angstrom backbone root mean square deviation from true geometry at first rank. The work will promote the use of new concepts where correlations among parameters provide more robust scoring models. It will facilitate studies involving molecular interactions, including modeling of large macromolecular assemblies and protein structure prediction. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 32: 787-796, 2011.

DockYard-a repository to assist modeling of protein-protein docking

In the absence of interlogs, building docking models is a time intensive task, involving generation of a large pool of docking decoys followed by refinement and screening to identify near native docking solutions. This limits the researcher interested in building docking methods with the choice of benchmarking only a limited number of protein complexes. We have created a repository called dockYard (http://pallab.serc.iisc.ernet.in/dockYard), that allows modelers interested in protein-protein interaction to access large volume of information on protein dimers and their interlogs, and also download decoys for their work if they are interested in building modeling methods. dockYard currently offers four categories of docking decoys derived from: Bound (native dimer co-crystallized), Unbound (individual subunits are crystallized, as well as the target dimer), Variants (match the previous two categories in at least one subunit with 100% sequence identity), and Interlogs (match the previous categories in at least one subunit with >= 90% or >= 50% sequence identity). The web service offers options for full or selective download based on search parameters. Our portal also serves as a repository to modelers who may want to share their decoy sets with the community.

Docking and free energy simulations to predict conformational domains involved in hCG-LH receptor interactions using recombinant antibodies

Single chain fragment variables (ScFvs) have been extensively employed in studying the protein-protein interactions. ScFvs derived from phage display libraries have an additional advantage of being generated against a native antigen, circumventing loss of information on conformational epitopes. In the present study, an attempt has been made to elucidate human chorionic gonadotropin (hCG)-luteinizing hormone (LH) receptor interactions by using a neutral and two inhibitory ScFvs against hCG. The objective was to dock a computationally derived model of these ScFvs onto the crystal structure of hCG and understand the differential roles of the mapped epitopes in hCG-LH receptor interactions. An anti-hCG ScFv, whose epitope was mapped previously using biochemical tools, served as the positive control for assessing the quality of docking analysis. To evaluate the role of specific side chains at the hCG-ScFv interface, binding free energy as well as residue interaction energies of complexes in solution were calculated using molecular mechanics Poisson-Boltzmann/surface area method after performing the molecular dynamic simulations on the selected hCG-ScFv models and validated using biochemical and SPR analysis. The robustness of these calculations was demonstrated by comparing the theoretically determined binding energies with the experimentally obtained kinetic parameters for hCG-ScFv complexes. Superimposition of hCG-ScFv model onto a model of hCG complexed with the 51-266 residues of LH receptor revealed importance of the residues previously thought to be unimportant for hormone binding and response. This analysis provides an alternate tool for understanding the structure-function analysis of ligand-receptor interactions. Proteins 2011;79:3108-3122. (C) 2011 Wiley-Liss, Inc.

Binding of BIS like and other ligands with the GSK-3 beta kinase: a combined docking and MM-PBSA study

Binding of several bisindolylmaleimide (BIS) like (BIS-3, BIS-8 and UCN1) and other ligands (H89, SB203580 and Y27632) with the glycogen synthase kinase-3 (GSK-3 beta) has been studied using combined docking, molecular dynamics and Poisson-Boltzmann surface area analysis approaches. The study generated novel binding modes of these ligands that can rationalize why some ligands inhibit GSK-3 beta while others do not. The relative binding free energies associated with these binding modes are in agreement with the corresponding measured specificities. This study further provides useful insight regarding possible existence of multiple conformations of some ligands like H89 and BIS-8. It is also found that binding modes of BIS-3, BIS-8 and UCN1 with GSK-3 beta and PDK1 kinases are similar. These new insights are expected to be useful for future rational design of novel, more potent GSK-3 beta-specific inhibitors as promising therapeutics.

Functional characterization, homology modeling and docking studies of beta-glucosidase responsible for bioactivation of cyanogenic hydroxynitrile glucosides from Leucaena leucocephala (subabul)

Glycosyl hydrolase family 1 beta-glucosidases are important enzymes that serve many diverse functions in plants including defense, whereby hydrolyzing the defensive compounds such as hydroxynitrile glucosides. A hydroxynitrile glucoside cleaving beta-glucosidase gene (Llbglu1) was isolated from Leucaena leucocephala, cloned into pET-28a (+) and expressed in E. coli BL21 (DE3) cells. The recombinant enzyme was purified by Ni-NTA affinity chromatography. The optimal temperature and pH for this beta-glucosidase were found to be 45 A degrees C and 4.8, respectively. The purified Llbglu1 enzyme hydrolyzed the synthetic glycosides, pNPGlucoside (pNPGlc) and pNPGalactoside (pNPGal). Also, the enzyme hydrolyzed amygdalin, a hydroxynitrile glycoside and a few of the tested flavonoid and isoflavonoid glucosides. The kinetic parameters K (m) and V (max) were found to be 38.59 mu M and 0.8237 mu M/mg/min for pNPGlc, whereas for pNPGal the values were observed as 1845 mu M and 0.1037 mu M/mg/min. In the present study, a three dimensional (3D) model of the Llbglu1 was built by MODELLER software to find out the substrate binding sites and the quality of the model was examined using the program PROCHEK. Docking studies indicated that conserved active site residues are Glu 199, Glu 413, His 153, Asn 198, Val 270, Asn 340, and Trp 462. Docking of rhodiocyanoside A with the modeled Llbglu1 resulted in a binding with free energy change (Delta G) of -5.52 kcal/mol on which basis rhodiocyanoside A could be considered as a potential substrate.

Crystal structures and binding studies of atovaquone and its derivatives with cytochrome bc(1): a molecular basis for drug design

Crystal structure of trans-atovaquone (antimalarial drug), its polymorph and its stereoisomer (cis) along with five other derivatives with different functional groups have been analyzed. Based on the conformational features of these compounds and the characteristics of the nature of intermolecular interactions, valuable insights into the atomistic details of protein-inhibitor interactions have been derived by docking studies. Atovaquone and its derivatives pack in the crystal lattice using intermolecular O-H center dot center dot center dot O hydrogen bond dimer motifs supported by surrogate weak interactions including C-H center dot center dot center dot O and C-H center dot center dot center dot Cl hydrogen bonds. The docking results of these molecules with cytochrome bc(1) show preferences to form N-H center dot center dot center dot O, O-H center dot center dot center dot O and O-H center dot center dot center dot Cl hydrogen bonds. The involvement of halogen atoms in the binding pocket appears to be significant and is contrary to the theoretically predicted mechanism of protein-ligand docking reported earlier based on mimicking experimental binding results of stigmatellin with cytochrome bc(1). The significance of subtle energy factors controlled by weak intermolecular interactions appears to play a major role in drug binding.

Structural and functional characterization of the human CCR5 receptor in complex with HIV gp120 envelope glycoprotein and CD4 receptor by molecular modeling studies

The entry of human immunodeficiency virus (HIV) into cells depends on a sequential interaction of the gp120 envelope glycoprotein with the cellular receptors CD4 and members of the chemokine receptor family. The CC chemokine receptor CCR5 is such a receptor for several chemokines and a major coreceptor for the entry of R5 HIV type-1 (HIV-1) into cells. Although many studies focus on the interaction of CCR5 with HIV-1, the corresponding interaction sites in CCR5 and gp120 have not been matched. Here we used an approach combining protein structure modeling, docking and molecular dynamics simulation to build a series of structural models of the CCR5 in complexes with gp120 and CD4. Interactions such as hydrogen bonds, salt bridges and van der Waals contacts between CCR5 and gp120 were investigated. Three snapshots of CCR5-gp120-CD4 models revealed that the initial interactions of CCR5 with gp120 are involved in the negatively charged N-terminus (Nt) region of CCR5 and positively charged bridging sheet region of gp120. Further interactions occurred between extracellular loop2 (ECL2) of CCR5 and the base of V3 loop regions of gp120. These interactions may induce the conformational changes in gp120 and lead to the final entry of HIV into the cell. These results not only strongly support the two-step gp120-CCR5 binding mechanism, but also rationalize extensive biological data about the role of CCR5 in HIV-1 gp120 binding and entry, and may guide efforts to design novel inhibitors.

Consensus scoring for enriching near-native structures from protein-protein docking decoys

The identification of near native protein-protein complexes among a set of decoys remains highly challenging. A stategy for improving the success rate of near native detection is to enrich near native docking decoys in a small number of top ranked decoys. Recently, we found that a combination of three scoring functions (energy, conservation, and interface propensity) can predict the location of binding interface regions with reasonable accuracy. Here, these three scoring functions are modified and combined into a consensus scoring function called ENDES for enriching near native docking decoys. We found that all individual scores result in enrichment for the majority of 28 targets in ZDOCK2.3 decoy set and the 22 targets in Benchmark 2.0. Among the three scores, the interface propensity score yields the highest enrichment in both sets of protein complexes. When these scores are combined into the ENDES consensus score, a significant increase in enrichment of near-native structures is found. For example, when 2000 dock decoys are reduced to 200 decoys by ENDES, the fraction of near-native structures in docking decoys increases by a factor of about six in average. ENDES was implemented into a computer program that is available for download at http://sparks.informatics.iupui.edu.

Refining near-native protein-protein docking decoys by local resampling and energy minimization

How to refine a near-native structure to make it closer to its native conformation is an unsolved problem in protein-structure and protein-protein complex-structure prediction. In this article, we first test several scoring functions for selecting locally resampled near-native protein-protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance-scaled Ideal-gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein-InteRaction Energy) for optimization and re-ranking. Significant improvement of final top-1 ranked structures over initial near-native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 angstrom or more and only 7% increased by 0.5 angstrom or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed.