Interaction profiles of protein kinase-inhibitor complexes and their application to virtual screening
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作者:
Chuaqui, C
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Biogen Idec Inc, Dept Res Informat, Computat Drug Design Grp, Cambridge Ctr 14, Cambridge, MA 02142 USABiogen Idec Inc, Dept Res Informat, Computat Drug Design Grp, Cambridge Ctr 14, Cambridge, MA 02142 USA
Chuaqui, C
[1
]
Deng, Z
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Biogen Idec Inc, Dept Res Informat, Computat Drug Design Grp, Cambridge Ctr 14, Cambridge, MA 02142 USABiogen Idec Inc, Dept Res Informat, Computat Drug Design Grp, Cambridge Ctr 14, Cambridge, MA 02142 USA
Deng, Z
[1
]
Singh, J
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Biogen Idec Inc, Dept Res Informat, Computat Drug Design Grp, Cambridge Ctr 14, Cambridge, MA 02142 USABiogen Idec Inc, Dept Res Informat, Computat Drug Design Grp, Cambridge Ctr 14, Cambridge, MA 02142 USA
Singh, J
[1
]
机构:
[1] Biogen Idec Inc, Dept Res Informat, Computat Drug Design Grp, Cambridge Ctr 14, Cambridge, MA 02142 USA
A major challenge facing structure-based drug discovery efforts is how to leverage the massive amount of experimental (X-ray and NMR) and virtual structural information generated from drug discovery projects. Many important drug targets have large numbers of protein-inhibitor complexes, necessitating tools to compare and contrast their similarities and differences. ThiS information would be valuable for understanding potency and selectivity of inhibitors and could be used to define target constraints to assist virtual screening. We describe a profile-based approach that enables us to capture the conservation of interactions between a set, of protein ligand receptor complexes. The use of profiles provides a sensitive means to compare multiple inhibitors binding to a drug target. We demonstrate the utility of profile-based analysis of small molecule complexes from the protein-kinase family to identify, similarities and differences in binding of ATP, p38, and CDK2 compounds to kinases and how these profiles can be applied to differentiate the selectivity of these inhibitors. Importantly.. our virtual screening results demonstrate superior enrichment of kinase inhibitors using profile-based methods relative to traditional scoring functions. Interaction-based analysis should provide a valuable tool for understanding inhibitor binding to other important drug targets.