Aeri Lee1, Dongsup Kim1. 1. Department of Bio and Brain Engineering, KAIST, Daejeon 34141, Republic of Korea.
Abstract
MOTIVATION: Identification of putative drug targets is a critical step for explaining the mechanism of drug action against multiple targets, finding new therapeutic indications for existing drugs and unveiling the adverse drug reactions. One important approach is to use the molecular docking. However, its widespread utilization has been hindered by the lack of easy-to-use public servers. Therefore, it is vital to develop a streamlined computational tool for target prediction by molecular docking on a large scale. RESULTS: We present a fully automated web tool named Consensus Reverse Docking System (CRDS), which predicts potential interaction sites for a given drug. To improve hit rates, we developed a strategy of consensus scoring. CRDS carries out reverse docking against 5254 candidate protein structures using three different scoring functions (GoldScore, Vina and LeDock from GOLD version 5.7.1, AutoDock Vina version 1.1.2 and LeDock version 1.0, respectively), and those scores are combined into a single score named Consensus Docking Score (CDS). The web server provides the list of top 50 predicted interaction sites, docking conformations, 10 most significant pathways and the distribution of consensus scores. AVAILABILITY AND IMPLEMENTATION: The web server is available at http://pbil.kaist.ac.kr/CRDS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Identification of putative drug targets is a critical step for explaining the mechanism of drug action against multiple targets, finding new therapeutic indications for existing drugs and unveiling the adverse drug reactions. One important approach is to use the molecular docking. However, its widespread utilization has been hindered by the lack of easy-to-use public servers. Therefore, it is vital to develop a streamlined computational tool for target prediction by molecular docking on a large scale. RESULTS: We present a fully automated web tool named Consensus Reverse Docking System (CRDS), which predicts potential interaction sites for a given drug. To improve hit rates, we developed a strategy of consensus scoring. CRDS carries out reverse docking against 5254 candidate protein structures using three different scoring functions (GoldScore, Vina and LeDock from GOLD version 5.7.1, AutoDock Vina version 1.1.2 and LeDock version 1.0, respectively), and those scores are combined into a single score named Consensus Docking Score (CDS). The web server provides the list of top 50 predicted interaction sites, docking conformations, 10 most significant pathways and the distribution of consensus scores. AVAILABILITY AND IMPLEMENTATION: The web server is available at http://pbil.kaist.ac.kr/CRDS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Bruna Costa Zorzanelli; Gabriel Ouverney; Fernanda P Pauli; Anna Carolina Carvalho da Fonseca; Elan Cardozo Paes de Almeida; Danielle Gonçalves de Carvalho; Patricia Abrão Possik; Vitor Won-Held Rabelo; Paula Alvarez Abreu; Bruno Pontes; Vitor Francisco Ferreira; Luana da Silva Magalhães Forezi; Fernando de Carvalho da Silva; Bruno Kaufmann Robbs Journal: Molecules Date: 2022-08-12 Impact factor: 4.927
Authors: Yash Gupta; Neha Sharma; Snigdha Singh; Jesus G Romero; Vinoth Rajendran; Reagan M Mogire; Mohammad Kashif; Jordan Beach; Walter Jeske; Bernhards R Ogutu; Stefan M Kanzok; Hoseah M Akala; Jennifer Legac; Philip J Rosenthal; David J Rademacher; Ravi Durvasula; Agam P Singh; Brijesh Rathi; Prakasha Kempaiah Journal: Pharmaceutics Date: 2022-06-28 Impact factor: 6.525