Literature DB >> 10761126

New approach to molecular docking and its application to virtual screening of chemical databases

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Abstract

This paper describes the validation of a molecular docking method and its application to virtual database screening. The code flexibly docks ligand molecules into rigid receptor structures using a tabu search methodology driven by an empirically derived function for estimating the binding affinity of a protein-ligand complex. The docking method has been tested on 70 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. The lowest energy geometry produced by the docking protocol is within 2.0 A root mean square of the experimental binding mode for 79% of the complexes. The method has been applied to the problem of virtual database screening to identify known ligands for thrombin, factor Xa, and the estrogen receptor. A database of 10,000 randomly chosen "druglike" molecules has been docked into the three receptor structures. In each case known receptor ligands were included in the study. The results showed good separation between the predicted binding affinities of the known ligand set and the database subset.

Entities:  

Year:  2000        PMID: 10761126     DOI: 10.1021/ci990440d

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  11 in total

1.  Modified AutoDock for accurate docking of protein kinase inhibitors.

Authors:  Oleksandr V Buzko; Anthony C Bishop; Kevan M Shokat
Journal:  J Comput Aided Mol Des       Date:  2002-02       Impact factor: 3.686

Review 2.  A review of protein-small molecule docking methods.

Authors:  R D Taylor; P J Jewsbury; J W Essex
Journal:  J Comput Aided Mol Des       Date:  2002-03       Impact factor: 3.686

3.  Unsupervised guided docking of covalently bound ligands.

Authors:  Xavier Fradera; Jasmit Kaur; Jordi Mestres
Journal:  J Comput Aided Mol Des       Date:  2004-10       Impact factor: 3.686

4.  Synthesis, X-ray Single Crystal Structure, Molecular Docking and DFT Computations on N-[(1E)-1-(2H-1,3-Benzodioxol-5-yl)-3-(1H-imidazol-1-yl)propylidene]-hydroxylamine: A New Potential Antifungal Agent Precursor.

Authors:  Reem I Al-Wabli; Alwah R Al-Ghamdi; Hazem A Ghabbour; Mohamed H Al-Agamy; James Clemy Monicka; Issac Hubert Joe; Mohamed I Attia
Journal:  Molecules       Date:  2017-02-28       Impact factor: 4.411

5.  A Discovery Funnel for Nucleic Acid Binding Drug Candidates.

Authors:  Patrick A Holt; Robert Buscaglia; John O Trent; Jonathan B Chaires
Journal:  Drug Dev Res       Date:  2011-03-01       Impact factor: 4.360

6.  Disease-Ligand Identification Based on Flexible Neural Tree.

Authors:  Bin Yang; Wenzheng Bao; Baitong Chen
Journal:  Front Microbiol       Date:  2022-06-06       Impact factor: 6.064

7.  Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening.

Authors:  Maria I Zavodszky; Paul C Sanschagrin; Rajesh S Korde; Leslie A Kuhn
Journal:  J Comput Aided Mol Des       Date:  2002-12       Impact factor: 3.686

8.  Discovery of novel DNA gyrase inhibitors by high-throughput virtual screening.

Authors:  David A Ostrov; José A Hernández Prada; Patrick E Corsino; Kathryn A Finton; Nhan Le; Thomas C Rowe
Journal:  Antimicrob Agents Chemother       Date:  2007-08-06       Impact factor: 5.191

9.  Scoring functions and enrichment: a case study on Hsp90.

Authors:  Chrysi Konstantinou-Kirtay; John B O Mitchell; James A Lumley
Journal:  BMC Bioinformatics       Date:  2007-01-26       Impact factor: 3.169

10.  Low potency toxins reveal dense interaction networks in metabolism.

Authors:  William Bains
Journal:  BMC Syst Biol       Date:  2016-02-20
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