Literature DB >> 22515569

Generation of receptor structural ensembles for virtual screening using binding site shape analysis and clustering.

David J Osguthorpe1, Woody Sherman, Arnold T Hagler.   

Abstract

Accounting for protein flexibility is an essential yet challenging component of structure-based virtual screening. Whereas an ideal approach would account for full protein and ligand flexibility during the virtual screening process, this is currently intractable using available computational resources. An alternative is ensemble docking, where calculations are performed on a set of individual rigid receptor conformations and the results combined. The primary challenge associated with this approach is the choice of receptor structures to use for the docking calculations. In this work, we show that selection of a small set of structures based on clustering on binding site volume overlaps provides an efficient and effective way to account for protein flexibility in virtual screening. We first apply the method to crystal structures of cyclin-dependent kinase 2 and HIV protease and show that virtual screening for ensembles of four cluster representative structures yields consistently high enrichments and diverse actives. We then apply the method to a structural ensemble of the androgen receptor generated with molecular dynamics and obtain results that are in agreement with those from the crystal structures of cyclin-dependent kinase 2 and HIV protease. This work provides a step forward in the incorporation of protein flexibility into structure-based virtual screening.
© 2012 John Wiley & Sons A/S.

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Year:  2012        PMID: 22515569     DOI: 10.1111/j.1747-0285.2012.01396.x

Source DB:  PubMed          Journal:  Chem Biol Drug Des        ISSN: 1747-0277            Impact factor:   2.817


  29 in total

1.  Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors.

Authors:  Xian-qiang Sun; Lei Chen; Yao-zong Li; Wei-hua Li; Gui-xia Liu; Yao-quan Tu; Yun Tang
Journal:  Acta Pharmacol Sin       Date:  2013-12-16       Impact factor: 6.150

2.  Ensemble-based virtual screening: identification of a potential allosteric inhibitor of Bcr-Abl.

Authors:  Vivek Kumar Singh; Mohane Selvaraj Coumar
Journal:  J Mol Model       Date:  2017-07-01       Impact factor: 1.810

3.  Exploring protein flexibility: incorporating structural ensembles from crystal structures and simulation into virtual screening protocols.

Authors:  David J Osguthorpe; Woody Sherman; Arnold T Hagler
Journal:  J Phys Chem B       Date:  2012-04-23       Impact factor: 2.991

4.  Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors.

Authors:  Ori Kalid; Dora Toledo Warshaviak; Sharon Shechter; Woody Sherman; Sharon Shacham
Journal:  J Comput Aided Mol Des       Date:  2012-09-30       Impact factor: 3.686

5.  Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments.

Authors:  G Madhavi Sastry; Matvey Adzhigirey; Tyler Day; Ramakrishna Annabhimoju; Woody Sherman
Journal:  J Comput Aided Mol Des       Date:  2013-04-12       Impact factor: 3.686

6.  Molecular dynamics, dynamic site mapping, and highthroughput virtual screening on leptin and the Ob receptor as anti-obesity target.

Authors:  Marco Tutone; Licia Pantano; Antonino Lauria; Anna Maria Almerico
Journal:  J Mol Model       Date:  2014-05-06       Impact factor: 1.810

7.  Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures.

Authors:  Hugo Guterres; Sang-Jun Park; Wei Jiang; Wonpil Im
Journal:  J Chem Inf Model       Date:  2020-12-18       Impact factor: 4.956

8.  In Vitro Evaluation of Antileishmanial Activity of Computationally Screened Compounds against Ascorbate Peroxidase To Combat Amphotericin B Drug Resistance.

Authors:  Rani Mansuri; Ashish Kumar; Sindhuprava Rana; Bhavana Panthi; M Yousuf Ansari; Sushmita Das; Manas Ranjan Dikhit; Ganesh Chandra Sahoo; Pradeep Das
Journal:  Antimicrob Agents Chemother       Date:  2017-06-27       Impact factor: 5.191

9.  Enhancing Virtual Screening Performance of Protein Kinases with Molecular Dynamics Simulations.

Authors:  Tavina L Offutt; Robert V Swift; Rommie E Amaro
Journal:  J Chem Inf Model       Date:  2016-10-03       Impact factor: 4.956

10.  Improving Protein-Ligand Docking Results with High-Throughput Molecular Dynamics Simulations.

Authors:  Hugo Guterres; Wonpil Im
Journal:  J Chem Inf Model       Date:  2020-04-10       Impact factor: 4.956

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