Literature DB >> 26360643

Protein Flexibility in Docking-Based Virtual Screening: Discovery of Novel Lymphoid-Specific Tyrosine Phosphatase Inhibitors Using Multiple Crystal Structures.

Xuben Hou1, Kangshuai Li1, Xiao Yu1, Jin-peng Sun1, Hao Fang1.   

Abstract

Incorporating protein flexibility is a major challenge for docking-based virtual screening. With an increasing number of available crystal structures, ensemble docking with multiple protein structures is an efficient approach to deal with protein flexibility. Herein, we report the successful application of a docking-based virtual screen using multiple crystal structures to discover novel inhibitors of lymphoid-specific tyrosine phosphatase (LYP), a potential drug target for autoimmune diseases. The appropriate use of multiple protein structures allowed a better enrichment than a single structure in the recovery of known inhibitors. Subsequently, an optimal ensemble of LYP structures was selected and used in docking-based virtual screening. Eight novel LYP inhibitors (IC50 ranging from 7.95 to 56.6 μM) were identified among 23 hit compounds. Further studies demonstrated that the most active compound B15 possessed some selectivity over other protein phosphatases and could effectively up-regulate TCR (T cell receptor)-mediated signaling in Jurkat T cells. These novel hits not only provided good starting points for the development of therapeutic agents useful in autoimmune diseases but also demonstrated the advantages of choosing an appropriate ensemble of protein structures in docking-based virtual screening over using a single protein conformation.

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Year:  2015        PMID: 26360643     DOI: 10.1021/acs.jcim.5b00344

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  11 in total

Review 1.  Docking Screens for Novel Ligands Conferring New Biology.

Authors:  John J Irwin; Brian K Shoichet
Journal:  J Med Chem       Date:  2016-03-15       Impact factor: 7.446

2.  Binding mode similarity measures for ranking of docking poses: a case study on the adenosine A2A receptor.

Authors:  Andrew Anighoro; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2016-06-22       Impact factor: 3.686

Review 3.  Open-source chemogenomic data-driven algorithms for predicting drug-target interactions.

Authors:  Ming Hao; Stephen H Bryant; Yanli Wang
Journal:  Brief Bioinform       Date:  2019-07-19       Impact factor: 11.622

4.  Efficiency of Stratification for Ensemble Docking Using Reduced Ensembles.

Authors:  Bing Xie; John D Clark; David D L Minh
Journal:  J Chem Inf Model       Date:  2018-08-29       Impact factor: 4.956

5.  The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

Authors:  Jie Xia; Jui-Hua Hsieh; Huabin Hu; Song Wu; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2017-06-01       Impact factor: 4.956

6.  Computational Strategy for Bound State Structure Prediction in Structure-Based Virtual Screening: A Case Study of Protein Tyrosine Phosphatase Receptor Type O Inhibitors.

Authors:  Xuben Hou; David Rooklin; Duxiao Yang; Xiao Liang; Kangshuai Li; Jianing Lu; Cheng Wang; Peng Xiao; Yingkai Zhang; Jin-Peng Sun; Hao Fang
Journal:  J Chem Inf Model       Date:  2018-10-19       Impact factor: 4.956

Review 7.  Modern approaches to accelerate discovery of new antischistosomal drugs.

Authors:  Bruno Junior Neves; Eugene Muratov; Renato Beilner Machado; Carolina Horta Andrade; Pedro Vitor Lemos Cravo
Journal:  Expert Opin Drug Discov       Date:  2016-05-03       Impact factor: 6.098

Review 8.  Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

Authors:  Rohan Gupta; Devesh Srivastava; Mehar Sahu; Swati Tiwari; Rashmi K Ambasta; Pravir Kumar
Journal:  Mol Divers       Date:  2021-04-12       Impact factor: 3.364

9.  Systematic exploration of multiple drug binding sites.

Authors:  Mónika Bálint; Norbert Jeszenői; István Horváth; David van der Spoel; Csaba Hetényi
Journal:  J Cheminform       Date:  2017-12-28       Impact factor: 5.514

Review 10.  Chalcone Derivatives: Promising Starting Points for Drug Design.

Authors:  Marcelo N Gomes; Eugene N Muratov; Maristela Pereira; Josana C Peixoto; Lucimar P Rosseto; Pedro V L Cravo; Carolina H Andrade; Bruno J Neves
Journal:  Molecules       Date:  2017-07-25       Impact factor: 4.411

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