Literature DB >> 16426071

Screening drug-like compounds by docking to homology models: a systematic study.

Visvaldas Kairys1, Miguel X Fernandes, Michael K Gilson.   

Abstract

In the absence of an experimentally solved structure, a homology model of a protein target can be used instead for virtual screening of drug candidates by docking and scoring. This approach poses a number of questions regarding the choice of the template to use in constructing the model, the accuracy of the screening results, and the importance of allowing for protein flexibility. The present study addresses such questions with compound screening calculations for multiple homology models of five drug targets. A central result is that docking to homology models frequently yields enrichments of known ligands as good as that obtained by docking to a crystal structure of the actual target protein. Interestingly, however, standard measures of the similarity of the template used to build the homology model to the targeted protein show little correlation with the effectiveness of the screening calculations, and docking to the template itself often is as successful as docking to the corresponding homology model. Treating key side chains as mobile produces a modest improvement in the results. The reasons for these sometimes unexpected results, and their implications for future methodologic development, are discussed.

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Year:  2006        PMID: 16426071     DOI: 10.1021/ci050238c

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


  31 in total

1.  Discovery of novel selective serotonin reuptake inhibitors through development of a protein-based pharmacophore.

Authors:  Sankar Manepalli; Laura M Geffert; Christopher K Surratt; Jeffry D Madura
Journal:  J Chem Inf Model       Date:  2011-09-02       Impact factor: 4.956

2.  Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening?

Authors:  Hao Tang; Xiang Simon Wang; Jui-Hua Hsieh; Alexander Tropsha
Journal:  Proteins       Date:  2012-03-13

3.  Loopholes and missing links in protein modeling.

Authors:  Karen A Rossi; Carolyn A Weigelt; Akbar Nayeem; Stanley R Krystek
Journal:  Protein Sci       Date:  2007-07-27       Impact factor: 6.725

4.  Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results.

Authors:  Robert P Sheridan; Georgia B McGaughey; Wendy D Cornell
Journal:  J Comput Aided Mol Des       Date:  2008-02-14       Impact factor: 3.686

5.  Homology modelling of the human adenosine A2B receptor based on X-ray structures of bovine rhodopsin, the beta2-adrenergic receptor and the human adenosine A2A receptor.

Authors:  Farag F Sherbiny; Anke C Schiedel; Astrid Maass; Christa E Müller
Journal:  J Comput Aided Mol Des       Date:  2009-11       Impact factor: 3.686

Review 6.  Protein modeling: what happened to the "protein structure gap"?

Authors:  Torsten Schwede
Journal:  Structure       Date:  2013-09-03       Impact factor: 5.006

Review 7.  Modelling three-dimensional protein structures for applications in drug design.

Authors:  Tobias Schmidt; Andreas Bergner; Torsten Schwede
Journal:  Drug Discov Today       Date:  2013-11-08       Impact factor: 7.851

8.  Assignment of pterin deaminase activity to an enzyme of unknown function guided by homology modeling and docking.

Authors:  Hao Fan; Daniel S Hitchcock; Ronald D Seidel; Brandan Hillerich; Henry Lin; Steven C Almo; Andrej Sali; Brian K Shoichet; Frank M Raushel
Journal:  J Am Chem Soc       Date:  2013-01-02       Impact factor: 15.419

9.  Structure-based discovery of A2A adenosine receptor ligands.

Authors:  Jens Carlsson; Lena Yoo; Zhan-Guo Gao; John J Irwin; Brian K Shoichet; Kenneth A Jacobson
Journal:  J Med Chem       Date:  2010-05-13       Impact factor: 7.446

10.  PSPP: a protein structure prediction pipeline for computing clusters.

Authors:  Michael S Lee; Rajkumar Bondugula; Valmik Desai; Nela Zavaljevski; In-Chul Yeh; Anders Wallqvist; Jaques Reifman
Journal:  PLoS One       Date:  2009-07-16       Impact factor: 3.240

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