Literature DB >> 16729730

Improved lead-finding for kinase targets using high-throughput docking.

Campbell McInnes1.   

Abstract

Protein kinases represent a major class of drug targets for the pharmaceutical industry, and the identification of kinase inhibitors with novel and diverse chemotypes is therefore a high priority. Virtual screening methods are a primary source for the discovery of lead molecules for drug development, with high-throughput docking algorithms being among the most extensively used of these methods. A number of developments in virtual screening technologies have resulted in more effective computer-based compound screening of potential kinase inhibitors. These developments include the following: (i) conformational search methods for pose generation; (ii) improvements in the prediction of protein-ligand binding energy through the use of scoring functions; (iii) the use of interaction filters for identifying ligand poses with known binding determinants; and (iv) the impact of binding site flexibility upon high-throughput docking success. This review discusses the application of these methods in the context of the discovery of kinase adenosine triphosphate antagonists.

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Year:  2006        PMID: 16729730

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  2 in total

1.  Biased retrieval of chemical series in receptor-based virtual screening.

Authors:  Natasja Brooijmans; Jason B Cross; Christine Humblet
Journal:  J Comput Aided Mol Des       Date:  2010-10-30       Impact factor: 3.686

2.  Nilotinib based pharmacophore models for BCRABL.

Authors:  Kesavan Sabitha
Journal:  Bioinformation       Date:  2012-07-21
  2 in total

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