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Prediction of specificity-determining residues for small-molecule kinase inhibitors
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 u...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2655090/ https://www.ncbi.nlm.nih.gov/pubmed/19032760 http://dx.doi.org/10.1186/1471-2105-9-491 |
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author | Caffrey, Daniel R Lunney, Elizabeth A Moshinsky, Deborah J |
author_facet | Caffrey, Daniel R Lunney, Elizabeth A Moshinsky, Deborah J |
author_sort | Caffrey, Daniel R |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2655090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26550902009-03-14 Prediction of specificity-determining residues for small-molecule kinase inhibitors Caffrey, Daniel R Lunney, Elizabeth A Moshinsky, Deborah J BMC Bioinformatics Methodology Article 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. BioMed Central 2008-11-25 /pmc/articles/PMC2655090/ /pubmed/19032760 http://dx.doi.org/10.1186/1471-2105-9-491 Text en Copyright © 2008 Caffrey et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Article Caffrey, Daniel R Lunney, Elizabeth A Moshinsky, Deborah J Prediction of specificity-determining residues for small-molecule kinase inhibitors |
title | 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_short | Prediction of specificity-determining residues for small-molecule kinase inhibitors |
title_sort | prediction of specificity-determining residues for small-molecule kinase inhibitors |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2655090/ https://www.ncbi.nlm.nih.gov/pubmed/19032760 http://dx.doi.org/10.1186/1471-2105-9-491 |
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