Showing papers by "Vincent Zoete published in 2011"

SwissParam: a fast force field generation tool for small organic molecules.

Abstract: The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

SwissDock, a protein-small molecule docking web service based on EADock DSS

Abstract: Most life science processes involve, at the atomic scale, recognition between two molecules. The prediction of such interactions at the molecular level, by so-called docking software, is a non-trivial task. Docking programs have a wide range of applications ranging from protein engineering to drug design. This article presents SwissDock, a web server dedicated to the docking of small molecules on target proteins. It is based on the EADock DSS engine, combined with setup scripts for curating common problems and for preparing both the target protein and the ligand input files. An efficient Ajax/HTML interface was designed and implemented so that scientists can easily submit dockings and retrieve the predicted complexes. For automated docking tasks, a programmatic SOAP interface has been set up and template programs can be downloaded in Perl, Python and PHP. The web site also provides an access to a database of manually curated complexes, based on the Ligand Protein Database. A wiki and a forum are available to the community to promote interactions between users. The SwissDock web site is available online at http://www.swissdock.ch. We believe it constitutes a step toward generalizing the use of docking tools beyond the traditional molecular modeling community.

Fast docking using the CHARMM force field with EADock DSS.

Abstract: The prediction of binding modes (BMs) occurring between a small molecule and a target protein of biological interest has become of great importance for drug development. The overwhelming diversity of needs leaves room for docking approaches addressing specific problems. Nowadays, the universe of docking software ranges from fast and user friendly programs to algorithmically flexible and accurate approaches. EADock2 is an example of the latter. Its multiobjective scoring function was designed around the CHARMM22 force field and the FACTS solvation model. However, the major drawback of such a software design lies in its computational cost. EADock dihedral space sampling (DSS) is built on the most efficient features of EADock2, namely its hybrid sampling engine and multiobjective scoring function. Its performance is equivalent to that of EADock2 for drug-like ligands, while the CPU time required has been reduced by several orders of magnitude. This huge improvement was achieved through a combination of several innovative features including an automatic bias of the sampling toward putative binding sites, and a very efficient tree-based DSS algorithm. When the top-scoring prediction is considered, 57% of BMs of a test set of 251 complexes were reproduced within 2 A RMSD to the crystal structure. Up to 70% were reproduced when considering the five top scoring predictions. The success rate is lower in cross-docking assays but remains comparable with that of the latest version of AutoDock that accounts for the protein flexibility.

Structure-Function Analyses Point to a Polynucleotide-Accommodating Groove Essential for APOBEC3A Restriction Activities

Abstract: Members of the human APOBEC3 family of editing enzymes can inhibit various mobile genetic elements. APOBEC3A (A3A) can block the retrotransposon LINE-1 and the parvovirus adeno-associated virus type 2 (AAV-2) but does not inhibit retroviruses. In contrast, APOBEC3G (A3G) can block retroviruses but has only limited effects on AAV-2 or LINE-1. What dictates this differential target specificity remains largely undefined. Here, we modeled the structure of A3A based on its homology with the C-terminal domain of A3G and further compared the sequence of human A3A to those of 11 nonhuman primate orthologues. We then used these data to perform a mutational analysis of A3A, examining its ability to restrict LINE-1, AAV-2, and foreign plasmid DNA and to edit a single-stranded DNA substrate. The results revealed an essential functional role for the predicted single-stranded DNA-docking groove located around the A3A catalytic site. Within this region, amino acid differences between A3A and A3G are predicted to affect the shape of the polynucleotide-binding groove. Correspondingly, transferring some of these A3A residues to A3G endows the latter protein with the ability to block LINE-1 and AAV-2. These results suggest that the target specificity of APOBEC3 family members is partly defined by structural features influencing their interaction with polynucleotide substrates.

How T cell receptors interact with peptide-MHCs: a multiple steered molecular dynamics study.

Abstract: The T-cell receptor (TCR) interaction with antigenic peptides (p) presented by the major histocompatibility complex (MHC) molecule is a key determinant of immune response. In addition, TCR-pMHC interactions offer examples of features more generally pertaining to protein-protein recognition: subtle specificity and cross-reactivity. Despite their importance, molecular details determining the TCR-pMHC binding remain unsolved. However, molecular simulation provides the opportunity to investigate some of these aspects. In this study, we perform extensive equilibrium and steered molecular dynamics simulations to study the unbinding of three TCR-pMHC complexes. As a function of the dissociation reaction coordinate, we are able to obtain converged H-bond counts and energy decompositions at different levels of detail, ranging from the full proteins, to separate residues and water molecules, down to single atoms at the interface. Many observed features do not support a previously proposed two-step model for TCR recognition. Our results also provide keys to interpret experimental point-mutation results. We highlight the role of water both in terms of interface resolvation and of water molecules trapped in the bound complex. Importantly, we illustrate how two TCRs with similar reactivity and structures can have essentially different binding strategies.

Unique Spectrum of Activity of Prosimian TRIM5α against Exogenous and Endogenous Retroviruses

Abstract: Lentiviruses, the genus of retrovirus that includes HIV-1, rarely endogenize. Some lemurs uniquely possess an endogenous lentivirus called PSIV (“prosimian immunodeficiency virus”). Thus, lemurs provide the opportunity to study the activity of host defense factors, such as TRIM5α, in the setting of germ line invasion. We characterized the activities of TRIM5α proteins from two distant lemurs against exogenous retroviruses and a chimeric PSIV. TRIM5α from gray mouse lemur, which carries PSIV in its genome, exhibited the narrowest restriction activity. One allelic variant of gray mouse lemur TRIM5α restricted only N-tropic murine leukemia virus (N-MLV), while a second variant restricted N-MLV and, uniquely, B-tropic MLV (B-MLV); both variants poorly blocked PSIV. In contrast, TRIM5α from ring-tailed lemur, which does not contain PSIV in its genome, revealed one of the broadest antiviral activities reported to date against lentiviruses, including PSIV. Investigation into the antiviral specificity of ring-tailed lemur TRIM5α demonstrated a major contribution of a 32-amino-acid expansion in variable region 2 (v2) of the B30.2/SPRY domain to the breadth of restriction. Data on lemur TRIM5α and the prediction of ancestral simian sequences hint at an evolutionary scenario where antiretroviral specificity is prominently defined by the lineage-specific expansion of the variable loops of B30.2/SPRY.

Identification of human IKK-2 inhibitors of natural origin (part I): modeling of the IKK-2 kinase domain, virtual screening and activity assays.

Abstract: Background Their large scaffold diversity and properties, such as structural complexity and drug similarity, form the basis of claims that natural products are ideal starting points for drug design and development. Consequently, there has been great interest in determining whether such molecules show biological activity toward protein targets of pharmacological relevance. One target of particular interest is hIKK-2, a serine-threonine protein kinase belonging to the IKK complex that is the primary component responsible for activating NF-κB in response to various inflammatory stimuli. Indeed, this has led to the development of synthetic ATP-competitive inhibitors for hIKK-2. Therefore, the main goals of this study were (a) to use virtual screening to identify potential hIKK-2 inhibitors of natural origin that compete with ATP and (b) to evaluate the reliability of our virtual-screening protocol by experimentally testing the in vitro activity of selected natural-product hits. Methodology/Principal Findings We thus predicted that 1,061 out of the 89,425 natural products present in the studied database would inhibit hIKK-2 with good ADMET properties. Notably, when these 1,061 molecules were merged with the 98 synthetic hIKK-2 inhibitors used in this study and the resulting set was classified into ten clusters according to chemical similarity, there were three clusters that contained only natural products. Five molecules from these three clusters (for which no anti-inflammatory activity has been previously described) were then selected for in vitro activity testing, in which three out of the five molecules were shown to inhibit hIKK-2. Conclusions/Significance We demonstrated that our virtual-screening protocol was successful in identifying lead compounds for developing new inhibitors for hIKK-2, a target of great interest in medicinal chemistry. Additionally, all the tools developed during the current study (i.e., the homology model for the hIKK-2 kinase domain and the pharmacophore) will be made available to interested readers upon request.

TCRep 3D: An Automated In Silico Approach to Study the Structural Properties of TCR Repertoires

Abstract: TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

Genotype-phenotype correlations of TGFBI p.Leu509Pro, p.Leu509Arg, p.Val613Gly, and the allelic association of p.Met502Val-p.Arg555Gln mutations

Abstract: PURPOSE Investigate the genotype-phenotype correlations for five TGFBI (transforming growth factor, beta-induced) mutations including one novel pathogenic variant and one complex allele affecting the fourth FAS1 domain of keratoepithelin, and their potential effects on the protein's structure. METHODS Three unrelated families were clinically diagnosed with lattice corneal dystrophy (CD) and one with an unclassified CD of Bowman's layer. Mutations in the TGFBI gene were detected by direct sequencing, and the functional impact of each variant was predicted using in silico algorithms. Corneal phenotypes, including histological examinations, were compared with the literature data. Furthermore, molecular modeling studies of these mutations were performed. RESULTS Two distinct missense mutations affecting the same residue at position 509 of keratoepithelin: p.Leu509Pro (c.1526T>C) and p.Leu509Arg (c.1526T>G) were found to be associated with a lattice-type CD. The novel p.Val613Gly (c.1828T>G) TGFBI mutation was found in a sporadic case of an Algerian individual affected by lattice CD. Finally, the Bowman's layer CD was linked to the association in cis of the p.Met502Val and p.Arg555Gln variants, leading to the reclassification of this CD as atypical Thiel-Behnke CD. Structural modeling of these TGFBI mutations argues in favor of these mutations being responsible for instability and/or incorrect folding of keratoepithelin, predictions that are compatible with the clinical diagnoses. CONCLUSIONS Description of a novel TGFBI mutation and a complex TGFBI allele further extends the mutational spectrum of TGFBI. Moreover, we show convincing evidence that TGFBI mutations affecting Leu509 are linked to the lattice phenotype in two unrelated French families, contrasting with findings previously reported. The p.Leu509Pro was reported to be associated with both amyloid and non-amyloid aggregates, whereas p.Leu509Arg has been described as being responsible for Epithelial Basement Membrane Dystrophy (EBMD).