Prediction of specificity-determining residues for small-molecule kinase inhibitors
<p>Abstract</p> <p>Background</p> <p>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 th...
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doaj-eecd87b0a40041dd91e5e4791dc88eba2020-11-24T21:53:02ZengBMCBMC Bioinformatics1471-21052008-11-019149110.1186/1471-2105-9-491Prediction of specificity-determining residues for small-molecule kinase inhibitorsLunney Elizabeth ACaffrey Daniel RMoshinsky Deborah J<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p> http://www.biomedcentral.com/1471-2105/9/491 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lunney Elizabeth A Caffrey Daniel R Moshinsky Deborah J |
spellingShingle |
Lunney Elizabeth A Caffrey Daniel R Moshinsky Deborah J Prediction of specificity-determining residues for small-molecule kinase inhibitors BMC Bioinformatics |
author_facet |
Lunney Elizabeth A Caffrey Daniel R Moshinsky Deborah J |
author_sort |
Lunney Elizabeth A |
title |
Prediction of specificity-determining residues for small-molecule kinase inhibitors |
title_short |
Prediction of specificity-determining residues for small-molecule kinase inhibitors |
title_full |
Prediction of specificity-determining residues for small-molecule kinase inhibitors |
title_fullStr |
Prediction of specificity-determining residues for small-molecule kinase inhibitors |
title_full_unstemmed |
Prediction of specificity-determining residues for small-molecule kinase inhibitors |
title_sort |
prediction of specificity-determining residues for small-molecule kinase inhibitors |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2008-11-01 |
description |
<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p> |
url |
http://www.biomedcentral.com/1471-2105/9/491 |
work_keys_str_mv |
AT lunneyelizabetha predictionofspecificitydeterminingresiduesforsmallmoleculekinaseinhibitors AT caffreydanielr predictionofspecificitydeterminingresiduesforsmallmoleculekinaseinhibitors AT moshinskydeborahj predictionofspecificitydeterminingresiduesforsmallmoleculekinaseinhibitors |
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