Brian J. Hare
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Brian J. Hare has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
Paul R. Caron
Vertex Pharmaceuticals Incorporated, 130 Waverly Street, Cambridge, Massachusetts 02139
2 shared publicationsDaniel Chelsky
Caprion Proteomics, Montreal, Quebec, Canada H2X 3Y7
1 shared publicationEric Haseltine
Vertex Pharmaceuticals Incorporated, Boston, MA, USA
1 shared publicationGuy W. Bemis
Vertex Pharmaceuticals, 130 Waverly Street, Cambridge, Massachusetts 02139
1 shared publicationLaura McIntosh
Caprion Proteomics, Montreal, Quebec, Canada H2X 3Y7
1 shared publicationMarc D. Jacobs
Vertex Pharmaceuticals Incorporated, 130 Waverly Street, Cambridge, Massachusetts 02139, USA
1 shared publication
Latest Publications
- Open Access
- 1 June 2015
- Published by Elsevier in Data in Brief
- Vol. 3, 56-61
A signature for immune response correlates with HCV treatment outcome in Caucasian subjects
- 1 June 2015
- Published by Elsevier in Data in Brief
- Vol. 3, 56-61
Open AccessA signature for immune response correlates with HCV treatment outcome in Caucasian subjects
- 1 October 2007
- Published by Wiley in Proteins: Structure, Function, and Bioinformatics
- Vol. 70 (4) , 1451-1460
Classifying protein kinase structures guides use of ligand‐selectivity profiles to predict inactive conformations: Structure of lck/imatinib complex
We report a clustering of public human protein kinase structures based on the conformations of two structural elements, the activation segment and the C‐helix, revealing three discrete clusters. One cluster includes kinases in catalytically active conformations. Each of the other clusters contains a distinct inactive conformation. Typically, kinases adopt at most one of the inactive conformations in available X‐ray structures, implying that one of the conformations is preferred for many kinases. The classification is consistent with selectivity profiles of several well‐characterized kinase inhibitors. We show further that inhibitor selectivity profiles guide kinase classification. For example, selective inhibition of lck among src‐family kinases by imatinib (Gleevec) suggests that the relative stabilities of inactive conformations of lck are different from other src‐family kinases. We report the X‐ray structure of the lck/imatinib complex, confirming that the conformation adopted by lck is distinct from other structurally‐characterized src‐family kinases and instead resembles kinases abl1 and kit in complex with imatinib. Our classification creates new paths for designing small‐molecule inhibitors. Proteins 2008.
- 1 October 2007
- Published by Wiley in Proteins: Structure, Function, and Bioinformatics
- Vol. 70 (4) , 1451-1460
Classifying protein kinase structures guides use of ligand‐selectivity profiles to predict inactive conformations: Structure of lck/imatinib complex
We report a clustering of public human protein kinase structures based on the conformations of two structural elements, the activation segment and the C‐helix, revealing three discrete clusters. One cluster includes kinases in catalytically active conformations. Each of the other clusters contains a distinct inactive conformation. Typically, kinases adopt at most one of the inactive conformations in available X‐ray structures, implying that one of the conformations is preferred for many kinases. The classification is consistent with selectivity profiles of several well‐characterized kinase inhibitors. We show further that inhibitor selectivity profiles guide kinase classification. For example, selective inhibition of lck among src‐family kinases by imatinib (Gleevec) suggests that the relative stabilities of inactive conformations of lck are different from other src‐family kinases. We report the X‐ray structure of the lck/imatinib complex, confirming that the conformation adopted by lck is distinct from other structurally‐characterized src‐family kinases and instead resembles kinases abl1 and kit in complex with imatinib. Our classification creates new paths for designing small‐molecule inhibitors. Proteins 2008.
- 27 July 2004
- Published by American Chemical Society (ACS) in Journal of Medicinal Chemistry
- Vol. 47 (19) , 4731-4740
CORES: An Automated Method for Generating Three-Dimensional Models of Protein/Ligand Complexes
We describe a new, automated method for building 3D models of small-molecule ligands complexed with proteins. Modeling templates are constructed from frameworks (i.e., ring systems and linkers) of ligands extracted from 3D structures of ligands complexed with proteins that are structurally related to the target protein. These templates are typically substructures of the target ligand and are used to build models that constrain the ligand's conformation and binding orientation in the active site of the target protein. The practical utility of the method is shown by demonstrating that most ligands containing related frameworks bind protein kinases in the same orientation. Moreover, models for 15 of 19 cdk2/ligand complexes in the protein data bank built using our method deviate from the X-ray structure by less than 2 Å (rms). Finally, we show that over 70% of small-molecule protein kinase inhibitors published in J. Med. Chem. since 1993 can be modeled using a template extracted from a 3D protein kinase structure in the protein data bank.
- 27 July 2004
- Published by American Chemical Society (ACS) in Journal of Medicinal Chemistry
- Vol. 47 (19) , 4731-4740
CORES: An Automated Method for Generating Three-Dimensional Models of Protein/Ligand Complexes
We describe a new, automated method for building 3D models of small-molecule ligands complexed with proteins. Modeling templates are constructed from frameworks (i.e., ring systems and linkers) of ligands extracted from 3D structures of ligands complexed with proteins that are structurally related to the target protein. These templates are typically substructures of the target ligand and are used to build models that constrain the ligand's conformation and binding orientation in the active site of the target protein. The practical utility of the method is shown by demonstrating that most ligands containing related frameworks bind protein kinases in the same orientation. Moreover, models for 15 of 19 cdk2/ligand complexes in the protein data bank built using our method deviate from the X-ray structure by less than 2 Å (rms). Finally, we show that over 70% of small-molecule protein kinase inhibitors published in J. Med. Chem. since 1993 can be modeled using a template extracted from a 3D protein kinase structure in the protein data bank.