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Feature-similarity protein classifier as a ligand engineering tool.


ABSTRACT: Kinases have been often targeted in drug therapy aimed at blocking signaling pathways. However, the conservation of protein structure across homologs often leads to uncontrolled cross-reactivity. On the other hand, sticky packing defects in proteins are typically not conserved across homologs, making them ligand-anchoring sites potentially important to enhance selectivity. Thus, we introduce a hierarchical clustering of PDB-reported kinases according to packing differences. This kinome partitioning is highly correlated with proximity relations arising from the pharmacological profiling of kinases. A variable packing sensitivity is observed for individual drugs, with highly promiscuous ligands being the most insensitive to packing differences. Our classifier enables a strategy to design selective inhibitors.

SUBMITTER: Maddipati S 

PROVIDER: S-EPMC1945244 | biostudies-literature | 2006 Dec

REPOSITORIES: biostudies-literature

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Feature-similarity protein classifier as a ligand engineering tool.

Maddipati Sridhar S   Fernández Ariel A  

Biomolecular engineering 20061010 6


Kinases have been often targeted in drug therapy aimed at blocking signaling pathways. However, the conservation of protein structure across homologs often leads to uncontrolled cross-reactivity. On the other hand, sticky packing defects in proteins are typically not conserved across homologs, making them ligand-anchoring sites potentially important to enhance selectivity. Thus, we introduce a hierarchical clustering of PDB-reported kinases according to packing differences. This kinome partition  ...[more]

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