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Prediction of specificity-determining residues for small-molecule kinase inhibitors.

Caffrey DR, Lunney EA, Moshinsky DJ - BMC Bioinformatics (2008)

Bottom Line: 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.The method identifies potential specificity determinants that are not readily apparent, and provokes further investigation at the structural level.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pfizer Research Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. daniel.caffrey@gmail.com

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.

Show MeSH
S-Filter results for SB-203580. S-Filter is available through the PFAAT application. Percent inhibition values are displayed to the right of the kinase name. S-Filter analysis was restricted to alignment columns that correspond to residues that make contact with SB-203580. All residues that do not make contact with SB-203580 are hidden so that all contact resides appear as a contiguous sequence. S-Filter has applied filters to the tenth and eleventh columns as indicated by the filter boxes above the respective columns. Leucine and threonine are predicted as selectivity determinants, and all uninhibited kinases that do not have these residues are hidden by the respective filters.
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Figure 3: S-Filter results for SB-203580. S-Filter is available through the PFAAT application. Percent inhibition values are displayed to the right of the kinase name. S-Filter analysis was restricted to alignment columns that correspond to residues that make contact with SB-203580. All residues that do not make contact with SB-203580 are hidden so that all contact resides appear as a contiguous sequence. S-Filter has applied filters to the tenth and eleventh columns as indicated by the filter boxes above the respective columns. Leucine and threonine are predicted as selectivity determinants, and all uninhibited kinases that do not have these residues are hidden by the respective filters.

Mentions: SB-203580 selectively inhibits EGFR and p38 in the kinase panel (Figure 2). These two kinases are on distinct branches of the kinome tree [1] and share relatively low sequence identity in the binding site. S-Filter predicts that Leu 104 and Thr 106 are specificity determinants for SB-203580 (Figure 3). SB-203580 is a well-characterized compound, and the structural basis for its selectivity at the gatekeeper position is well known [11,31]. The relatively small threonine provides access to the so-called selectivity pocket. For example, ERK2 is not inhibited by SB-203580 as it has a bulkier glutamine at this position. However, mutation of glutamine 105 to a threonine makes ERK2 susceptible to inhibition by SB-203580 [31]. These experimental observations support the prediction of Thr 106 as a specificity determinant and we designate the prediction as a true positive in Table 1.


Prediction of specificity-determining residues for small-molecule kinase inhibitors.

Caffrey DR, Lunney EA, Moshinsky DJ - BMC Bioinformatics (2008)

S-Filter results for SB-203580. S-Filter is available through the PFAAT application. Percent inhibition values are displayed to the right of the kinase name. S-Filter analysis was restricted to alignment columns that correspond to residues that make contact with SB-203580. All residues that do not make contact with SB-203580 are hidden so that all contact resides appear as a contiguous sequence. S-Filter has applied filters to the tenth and eleventh columns as indicated by the filter boxes above the respective columns. Leucine and threonine are predicted as selectivity determinants, and all uninhibited kinases that do not have these residues are hidden by the respective filters.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2655090&req=5

Figure 3: S-Filter results for SB-203580. S-Filter is available through the PFAAT application. Percent inhibition values are displayed to the right of the kinase name. S-Filter analysis was restricted to alignment columns that correspond to residues that make contact with SB-203580. All residues that do not make contact with SB-203580 are hidden so that all contact resides appear as a contiguous sequence. S-Filter has applied filters to the tenth and eleventh columns as indicated by the filter boxes above the respective columns. Leucine and threonine are predicted as selectivity determinants, and all uninhibited kinases that do not have these residues are hidden by the respective filters.
Mentions: SB-203580 selectively inhibits EGFR and p38 in the kinase panel (Figure 2). These two kinases are on distinct branches of the kinome tree [1] and share relatively low sequence identity in the binding site. S-Filter predicts that Leu 104 and Thr 106 are specificity determinants for SB-203580 (Figure 3). SB-203580 is a well-characterized compound, and the structural basis for its selectivity at the gatekeeper position is well known [11,31]. The relatively small threonine provides access to the so-called selectivity pocket. For example, ERK2 is not inhibited by SB-203580 as it has a bulkier glutamine at this position. However, mutation of glutamine 105 to a threonine makes ERK2 susceptible to inhibition by SB-203580 [31]. These experimental observations support the prediction of Thr 106 as a specificity determinant and we designate the prediction as a true positive in Table 1.

Bottom Line: 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.The method identifies potential specificity determinants that are not readily apparent, and provokes further investigation at the structural level.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pfizer Research Technology Center, 620 Memorial Drive, Cambridge, MA 02139, USA. daniel.caffrey@gmail.com

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.

Show MeSH