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

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 communit

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

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

SwissTargetPrediction: a web server for target prediction of bioactive small molecules

Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-molecular targets to modulate their activity, which in turn results in the observed phenotypic effects. For this reason, mapping the targets of bioactive small molecules is a key step toward unraveling the molecular mechanisms underlying their bioactivity and predicting potential side effects or cross-reactivity. Recently, large datasets of protein-small molecule interactions have become available, providing a unique source of information for the development of knowledge-based approaches to computationally identify new targets for uncharacterized molecules or secondary targets for known molecules. Here, we introduce SwissTargetPrediction, a web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. Predictions can be carried out in five different organisms, and mapping predictions by homology within and between different species is enabled for close paralogs and orthologs. SwissTargetPrediction is accessible free of charge and without login requirement at http://www.swisstargetprediction.c

ExPASy: SIB bioinformatics resource portal

ExPASy (http://www.expasy.org) has worldwide reputation as one of the main bioinformatics resources for proteomics. It has now evolved, becoming an extensible and integrative portal accessing many scientific resources, databases and software tools in different areas of life sciences. Scientists can henceforth access seamlessly a wide range of resources in many different domains, such as proteomics, genomics, phylogeny/evolution, systems biology, population genetics, transcriptomics, etc. The individual resources (databases, web-based and downloadable software tools) are hosted in a ‘decentralized' way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions. Specifically, a single web portal provides a common entry point to a wide range of resources developed and operated by different SIB groups and external institutions. The portal features a search function across ‘selected' resources. Additionally, the availability and usage of resources are monitored. The portal is aimed for both expert users and people who are not familiar with a specific domain in life sciences. The new web interface provides, in particular, visual guidance for newcomers to ExPAS

Local Alignment Refinement Using Structural Assessment

Homology modeling is the most commonly used technique to build a three-dimensional model for a protein sequence. It heavily relies on the quality of the sequence alignment between the protein to model and related proteins with a known three dimensional structure. Alignment quality can be assessed according to the physico-chemical properties of the three dimensional models it produces

Identification of Human IKK-2 Inhibitors of Natural Origin (Part I): Modeling of the IKK-2 Kinase Domain, Virtual Screening and Activity Assays

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

Conception d'un logiciel de docking et applications dans la recherche de nouvelles molécules actives

Les récentes difficultés de l'industrie pharmaceutique semblent ne pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus de techniques dites haut-débit , dont des approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules. Toutes deux reposent sur la capacité à prédire l'interaction moléculaire entre un principe actif potentiel et une protéine cible ayant un intérêt thérapeutique. Cette thèse présente un nouveau logiciel réalisant cette prédiction: EADock. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections et repose sur CHARMM. Son efficacité a été mise en évidence sur 37 complexes protéine-ligand cristallisés. Il a également permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5b1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis.The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques, including computational approaches such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both rely on the prediction of the molecular interaction occurring between drug-like molecules and a therapeutically relevant target. A new docking software is introduced in this thesis : EADock. This hybrid evolutionary algorithm uses two fitness functions, and rely on CHARMM. Its docking efficiency was shown on 37 crystallized protein-ligand complexes. It has been used in a fragment-based rational drug design approach, leading to the successful design of new peptidic ligands for the a integrin and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well established ligands.GRENOBLE1-BU Médecine pharm. (385162101) / SudocSudocFranceF

Influence of energy minimization for six different predictors CDIE/All (A), RDIE/All (B), GBMV2/All (C), ProsaII/All (D), ANOLEA/All (E) and ANOLEA/SSE (F) applied to the test case 1flp helix1.

<p>The six corresponding profiles and their standard deviation are shown for minimized and non minimized models, with plain and dotted lines, respectively.</p

Mean backbone (bb) RMSD per residue for 100 models of 1flp h1 testcase for Δseq = 0.

<p>Secondary structure elements limits are indicated by horizontal bars on the upper x axis. Regions of high variability correspond to loops.</p