Dataset Information

MTiOpenScreen: a web server for structure-based virtual screening.

ABSTRACT: Open screening endeavors play and will play a key role to facilitate the identification of new bioactive compounds in order to foster innovation and to improve the effectiveness of chemical biology and drug discovery processes. In this line, we developed the new web server MTiOpenScreen dedicated to small molecule docking and virtual screening. It includes two services, MTiAutoDock and MTiOpenScreen, allowing performing docking into a user-defined binding site or blind docking using AutoDock 4.2 and automated virtual screening with AutoDock Vina. MTiOpenScreen provides valuable starting collections for screening, two in-house prepared drug-like chemical libraries containing 150 000 PubChem compounds: the Diverse-lib containing diverse molecules and the iPPI-lib enriched in molecules likely to inhibit protein-protein interactions. In addition, MTiOpenScreen offers users the possibility to screen up to 5000 small molecules selected outside our two libraries. The predicted binding poses and energies of up to 1000 top ranked ligands can be downloaded. In this way, MTiOpenScreen enables researchers to apply virtual screening using different chemical libraries on traditional or more challenging protein targets such as protein-protein interactions. The MTiOpenScreen web server is free and open to all users at http://bioserv.rpbs.univ-paris-diderot.fr/services/MTiOpenScreen/.

SUBMITTER: Labbe CM

PROVIDER: S-EPMC4489289 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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MTiOpenScreen: a web server for structure-based virtual screening.

Labbé Céline M CM Rey Julien J Lagorce David D Vavruša Marek M Becot Jérome J Sperandio Olivier O Villoutreix Bruno O BO Tufféry Pierre P Miteva Maria A MA

Nucleic acids research 20150408 W1

Open screening endeavors play and will play a key role to facilitate the identification of new bioactive compounds in order to foster innovation and to improve the effectiveness of chemical biology and drug discovery processes. In this line, we developed the new web server MTiOpenScreen dedicated to small molecule docking and virtual screening. It includes two services, MTiAutoDock and MTiOpenScreen, allowing performing docking into a user-defined binding site or blind docking using AutoDock 4.2 ...[more]

PMID: 25855812

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Project description:Medicinal plants containing complex mixtures of several compounds with various potential beneficial biological effects are attractive treatment interventions for a complex multi-faceted disease like diabetes. In this study, compounds identified from African medicinal plants were evaluated for their potential anti-diabetic activity. A total of 867 compounds identified from over 300 medicinal plants were screened in silico with the DIA-DB web server (http://bio-hpc.eu/software/dia-db/) against 17 known anti-diabetic drug targets. Four hundred and thirty compounds were identified as potential inhibitors, with 184 plants being identified as the sources of these compounds. The plants Argemone ochroleuca, Clivia miniata, Crinum bulbispermum, Danais fragans, Dioscorea dregeana, Dodonaea angustifolia, Eucomis autumnalis, Gnidia kraussiana, Melianthus comosus, Mondia whitei, Pelargonium sidoides, Typha capensis, Vinca minor, Voacanga Africana, and Xysmalobium undulatum were identified as new sources rich in compounds with a potential anti-diabetic activity. The major targets identified for the natural compounds were aldose reductase, hydroxysteroid 11-beta dehydrogenase 1, dipeptidyl peptidase 4, and peroxisome proliferator-activated receptor delta. More than 30% of the compounds had five or more potential targets. A hierarchical clustering analysis coupled with a maximum common substructure analysis revealed the importance of the flavonoid backbone for predicting potential activity against aldose reductase and hydroxysteroid 11-beta dehydrogenase 1. Filtering with physiochemical and the absorption, distribution, metabolism, excretion and toxicity (ADMET) descriptors identified 28 compounds with favorable ADMET properties. The six compounds-crotofoline A, erythraline, henningsiine, nauclefidine, vinburnine, and voaphylline-were identified as novel potential multi-targeted anti-diabetic compounds, with favorable ADMET properties for further drug development.

Dataset Information

MTiOpenScreen: a web server for structure-based virtual screening.

Publications

MTiOpenScreen: a web server for structure-based virtual screening.

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