K
Kaushik Raha
Researcher at GlaxoSmithKline
Publications - 22
Citations - 1610
Kaushik Raha is an academic researcher from GlaxoSmithKline. The author has contributed to research in topics: Protein ligand & Ligand (biochemistry). The author has an hindex of 17, co-authored 22 publications receiving 1450 citations. Previous affiliations of Kaushik Raha include University of Florida & University of California, San Francisco.
Papers
More filters
Journal ArticleDOI
Discovery of GSK2126458, a Highly Potent Inhibitor of PI3K and the Mammalian Target of Rapamycin
Steven D. Knight,Nicholas D. Adams,Joelle Lorraine Burgess,Amita M. Chaudhari,Michael G. Darcy,Carla A. Donatelli,Juan I. Luengo,Ken A. Newlander,Cynthia A. Parrish,Lance Ridgers,Martha A. Sarpong,Schmidt Stanley J,Glenn S. Van Aller,Jeffrey D. Carson,Melody Diamond,Patricia A. Elkins,Christine M. Gardiner,Eric Garver,Seth A. Gilbert,Richard R. Gontarek,Jeffrey R. Jackson,Kevin L. Kershner,Lusong Luo,Kaushik Raha,Christian S. Sherk,Chiu-Mei Sung,David Sutton,Peter J. Tummino,Ronald Wegrzyn,Kurt R. Auger,Dashyant Dhanak +30 more
TL;DR: 2,4-Difluoro-N-{2-(methyloxy)-5-[4-(4-pyridazinyl)-6-quinolinyl]-3- pyridinyl}benzenesulfonamide (GSK2126458, 1) has been identified as a highly potent, orally bioavailable inhibitor of PI3Kα and mTOR with in vivo activity in both pharmacodynamic and tumor growth efficacy models.
Journal ArticleDOI
The role of quantum mechanics in structure-based drug design.
Kaushik Raha,Martin Peters,Bing Wang,Ning Yu,Andrew M. Wollacott,Lance M. Westerhoff,Kenneth M. Merz +6 more
TL;DR: Objectively validating the improved applicability and performance of QM over classical-based models in DD will be the focus of research in the coming years along with research on the conformational sampling problem as it relates to protein-ligand complexes.
Journal ArticleDOI
Large-scale validation of a quantum mechanics based scoring function: predicting the binding affinity and the binding mode of a diverse set of protein-ligand complexes.
Kaushik Raha,Kenneth M. Merz +1 more
TL;DR: This study uses semiempirical quantum mechanics to design a scoring function that can calculate the electrostatic interactions and solvation free energy expected during complexation and shows the predictive power and ability of this scoring function within protein targets and its ability to score ligand poses docked to a protein target.
Journal ArticleDOI
A Quantum Mechanics-Based Scoring Function: Study of Zinc Ion-Mediated Ligand Binding
Kaushik Raha,Kenneth M. Merz +1 more
TL;DR: A novel quantum mechanics-based scoring function is developed to predict free energy of ligand binding in the zinc metalloenzymes carbonic anhydrase (CA) and carboxypeptidase A (CPA).
Journal ArticleDOI
Prediction of amino acid sequence from structure.
TL;DR: Overall, the analysis suggests that statistical profile scores of designed sequences are a novel and valuable figure of merit for assessing and improving protein design algorithms.