Literature DB >> 17696871

Free resources to assist structure-based virtual ligand screening experiments.

Bruno O Villoutreix1, Nicolas Renault, David Lagorce, Olivier Sperandio, Matthieu Montes, Maria A Miteva.   

Abstract

In today's research environment, a wealth of experimental/theoretical structural data is available and the number of therapeutically relevant macromolecular structures is growing rapidly. This, coupled with the huge number of small non-peptide potential drug candidates easily available (over 7 million compounds), highlight the need of using computer-aided techniques for the efficient identification and optimization of novel hit compounds. Virtual (or in silico) ligand screening based on the three-dimensional structure of macromolecular targets (SB-VLS) is firmly established as an important approach to identify chemical entities that have a high likelihood of binding to a target molecule to elicit desired biological responses. A myriad of free applications and services facilitating the drug discovery process have been posted on the Web. In this review, we cite over 350 URLs that are useful for SB-VLS projects and essentially free for academic groups. We attempt to provide links for in silico ADME/tox prediction tools, compound collections, some ligand-based methods, characterization/simulation of 3D targets and homology modeling tools, druggable pocket predictions, active site comparisons, analysis of macromolecular interfaces, protein docking tools to help identify binding pockets and protein-ligand docking/scoring methods. As such, we aim at providing both, methods pertaining to the field of Structural Bioinformatics (defined here as tools to study macromolecules) and methods pertaining to the field of Chemoinformatics (defined here as tools to make better decisions faster in the arena of drug/lead identification and optimization). We also report several recent success stories using these free computer methods. This review should help readers finding free computer tools useful for their projects. Overall, we are confident that these tools will facilitate rapid and cost-effective identification of new hit compounds. The URLs presented in this review will be updated regularly at www.vls3d.com in the coming months, "Links" section.

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Year:  2007        PMID: 17696871     DOI: 10.2174/138920307781369391

Source DB:  PubMed          Journal:  Curr Protein Pept Sci        ISSN: 1389-2037            Impact factor:   3.272


  21 in total

Review 1.  From laptop to benchtop to bedside: structure-based drug design on protein targets.

Authors:  Lu Chen; John K Morrow; Hoang T Tran; Sharangdhar S Phatak; Lei Du-Cuny; Shuxing Zhang
Journal:  Curr Pharm Des       Date:  2012       Impact factor: 3.116

2.  A computerized protein-protein interaction modeling study of ampicillin antibody specificity in relation to biosensor development.

Authors:  Minghua Wang; Jianping Wang
Journal:  J Mol Model       Date:  2011-02-11       Impact factor: 1.810

3.  Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

Authors:  Jihyun Shim; Alexander D Mackerell
Journal:  Medchemcomm       Date:  2011-05       Impact factor: 3.597

4.  Data Mining and Computational Modeling of High-Throughput Screening Datasets.

Authors:  Sean Ekins; Alex M Clark; Krishna Dole; Kellan Gregory; Andrew M Mcnutt; Anna Coulon Spektor; Charlie Weatherall; Nadia K Litterman; Barry A Bunin
Journal:  Methods Mol Biol       Date:  2018

5.  A versatile approach to transform low-affinity peptides into protein probes with cotranslationally expressed chemical cross-linker.

Authors:  Aiko Umeda; Gabrielle Nina Thibodeaux; Kathryn Moncivais; Faqin Jiang; Zhiwen Jonathan Zhang
Journal:  Anal Biochem       Date:  2010-05-31       Impact factor: 3.365

6.  e-LEA3D: a computational-aided drug design web server.

Authors:  Dominique Douguet
Journal:  Nucleic Acids Res       Date:  2010-05-05       Impact factor: 16.971

7.  Frog2: Efficient 3D conformation ensemble generator for small compounds.

Authors:  Maria A Miteva; Frederic Guyon; Pierre Tufféry
Journal:  Nucleic Acids Res       Date:  2010-05-05       Impact factor: 16.971

8.  Nilotinib based pharmacophore models for BCRABL.

Authors:  Kesavan Sabitha
Journal:  Bioinformation       Date:  2012-07-21

Review 9.  Major prospects for exploring canine vector borne diseases and novel intervention methods using 'omic technologies.

Authors:  Robin B Gasser; Cinzia Cantacessi; Bronwyn E Campbell; Andreas Hofmann; Domenico Otranto
Journal:  Parasit Vectors       Date:  2011-04-13       Impact factor: 3.876

10.  Attacking COVID-19 Progression Using Multi-Drug Therapy for Synergetic Target Engagement.

Authors:  Mathew A Coban; Juliet Morrison; Sushila Maharjan; David Hyram Hernandez Medina; Wanlu Li; Yu Shrike Zhang; William D Freeman; Evette S Radisky; Karine G Le Roch; Carla M Weisend; Hideki Ebihara; Thomas R Caulfield
Journal:  Biomolecules       Date:  2021-05-23
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