Abstract:
BACKGROUND:Designing 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. RESULTS:Here 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. CONCLUSION:S-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.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Caffrey DR,Lunney EA,Moshinsky DJdoi
10.1186/1471-2105-9-491subject
Has Abstractpub_date
2008-11-25 00:00:00pages
491issn
1471-2105pii
1471-2105-9-491journal_volume
9pub_type
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