Showing papers by "Vincent Zoete published in 2007"

EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

Abstract: In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein-protein association using MM-GBSA: application to the TCR-p-MHC complex.

Abstract: Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by Class I major histocompatibility complexes (MHC) is the key event in the immune response against virus-infected cells or tumor cells. A study of the 2C TCR/SIYR/H-2Kb system using a computational alanine scanning and a much faster binding free energy decomposition based on the Molecular Mechanics—Generalized Born Surface Area (MM-GBSA) method is presented. The results show that the TCR-p-MHC binding free energy decomposition using this approach and including entropic terms provides a detailed and reliable description of the interactions between the molecules at an atomistic level. Comparison of the decomposition results with experimentally determined activity differences for alanine mutants yields a correlation of 0.67 when the entropy is neglected and 0.72 when the entropy is taken into account. Similarly, comparison of experimental activities with variations in binding free energies determined by computational alanine scanning yields correlations of 0.72 and 0.74 when the entropy is neglected or taken into account, respectively. Some key interactions for the TCR-p-MHC binding are analyzed and some possible side chains replacements are proposed in the context of TCR protein engineering. In addition, a comparison of the two theoretical approaches for estimating the role of each side chain in the complexation is given, and a new ad hoc approach to decompose the vibrational entropy term into atomic contributions, the linear decomposition of the vibrational entropy (LDVE), is introduced. The latter allows the rapid calculation of the entropic contribution of interesting side chains to the binding. This new method is based on the idea that the most important contributions to the vibrational entropy of a molecule originate from residues that contribute most to the vibrational amplitude of the normal modes. The LDVE approach is shown to provide results very similar to those of the exact but highly computationally demanding method. Proteins 2007. © 2007 Wiley-Liss, Inc.

Model structure of human APOBEC3G.

Abstract: BACKGROUND: APOBEC3G (apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like 3G) has antiretroviral activity associated with the hypermutation of viral DNA through cytosine deamination. APOBEC3G has two cytosine deaminase (CDA) domains; the catalytically inactive amino-terminal domain of APOBEC3G (N-CDA) carries the Vif interaction domain. There is no 3-D structure of APOBEC3G solved by X-ray or nuclear magnetic resonance. METHODOLOGY/PRINCIPAL FINDINGS: We predicted the structure of human APOBEC3G based on the crystal structure of APOBEC2. To assess the model structure, we evaluated 48 mutants of APOBEC3G N-CDA that identify novel variants altering DeltaVif HIV-1 infectivity and packaging of APOBEC3G. Results indicated that the key residue D128 is exposed at the surface of the model, with a negative local electrostatic potential. Mutation D128K changes the sign of that local potential. In addition, two novel functionally relevant residues that result in defective APOBEC3G encapsidation, R122 and W127, cluster at the surface. CONCLUSIONS/SIGNIFICANCE: The structure model identifies a cluster of residues important for packaging of APOBEC3G into virions, and may serve to guide functional analysis of APOBEC3G.

A Novel Population of Human Melanoma-Specific CD8 T Cells Recognizes Melan-AMART-1 Immunodominant Nonapeptide but Not the Corresponding Decapeptide

Abstract: HLA-A2-restricted cytolytic T cells specific for the immunodominant human tumor Ag Melan-A MART-1 can kill most HLA-matched melanoma cells, through recognition of two naturally occurring antigenic variants, i.e., Melan-A nonamer AAGIGILTV and decamer EAAGIGILTV peptides. Several previous studies have suggested a high degree of TCR cross-reactivity to the two peptides. In this study, we describe for the first time that some T cell clones are exclusively nonamer specific, because they are not labeled by A2/decamer-tetramers and do not recognize the decamer when presented endogenously. Functional assays with peptides gave misleading results, possibly because decamers were cleaved by exopeptidases. Interestingly, nonapeptide-specific T cell clones were rarely Vα2.1 positive (only 1 of 19 clones), in contrast to the known strong bias for Vα2.1-positive TCRs found in decamer-specific clones (59 of 69 clones). Molecular modeling revealed that nonapeptide-specific TCRs formed unfavorable interactions with the decapeptide, whereas decapeptide-specific TCRs productively created a hydrogen bond between CDR1α and glutamic acid (E) of the decapeptide. Ex vivo analysis of T cells from melanoma metastases demonstrated that both nonamer and decamer-specific T cells were enriched to substantial frequencies in vivo, and representative clones showed efficient tumor cell recognition and killing. We conclude that the two peptides should be regarded as distinct epitopes when analyzing tumor immunity and developing immunotherapy against melanoma.