Abstract

BackgroundDesigning small-molecule kinase inhibitors with desirable selectivity profiles is a major challenge in drug discovery. A high-throughput screen for inhibitors of a given kinase will typically yield many compounds that inhibit more than one kinase. A series of chemical modifications are usually required before a compound exhibits an acceptable selectivity profile. Rationalizing the selectivity profile for a small-molecule inhibitor in terms of the specificity-determining kinase residues for that molecule can be an important step toward the goal of developing selective kinase inhibitors.ResultsHere we describe S-Filter, a method that combines sequence and structural information to predict specificity-determining residues for a small molecule and its kinase selectivity profile. Analysis was performed on seven selective kinase inhibitors where a structural basis for selectivity is known. S-Filter correctly predicts specificity determinants that were described by independent groups. S-Filter also predicts a number of novel specificity determinants that can often be justified by further structural comparison.ConclusionS-Filter is a valuable tool for analyzing kinase selectivity profiles. The method identifies potential specificity determinants that are not readily apparent, and provokes further investigation at the structural level.

Highlights

  • Designing small-molecule kinase inhibitors with desirable selectivity profiles is a major challenge in drug discovery

  • Designing selective kinase inhibitors is a major challenge in drug discovery and development

  • The selectivity issues associated with small molecules that bind to the ATP catalytic binding site are challenging as most kinases have the same active-site chemistry

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Summary

Methodology article

Prediction of specificity-determining residues for small-molecule kinase inhibitors. Address: 1Pfizer Research Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA and 2Pfizer Global Research and Development, 10777 Science Center Drive, San Diego, CA 92121, USA. Published: 25 November 2008 BMC Bioinformatics 2008, 9:491 doi:10.1186/1471-2105-9-491

Results
Background
Discussion and Conclusion
Cohen P
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