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Identification of type I and type II inhibitors of c-Yes kinase using in silico and experimental techniques
Authors:Chandrasekaran Ramakrishnan  Anthony Mary Thangakani  Devadasan Velmurugan  Dhanabalan Anantha Krishnan  Masakazu Sekijima  Yutaka Akiyama
Affiliation:1. Department of Biotechnology, Bhupat Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT) Madras, Chennai 600036, Tamilnadu, India;2. Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai 600025, Tamilnadu, India;3. Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, 4259 Nagatsutacho, Midori-ku, Yokohama 226-8501, Japan;4. Advanced Computational Drug Discovery Unit (ACDD), Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsutacho, Midori-ku, Yokohama 226-8501, Japan;5. Department of Computer Science, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8550, Japan
Abstract:c-Yes kinase is considered as one of the attractive targets for anti-cancer drug design. The DFG (Asp-Phe-Gly) motif present in most of the kinases will adopt active and inactive conformations, known as DFG-in and DFG-out and their inhibitors are classified into type I and type II, respectively. In the present study, two screening protocols were followed for identification of c-Yes kinase inhibitors. (i) Structure-based virtual screening (SBVS) and (ii) Structure-based (SB) and Pharmacophore-based (PB) tandem screening. In SBVS, the c-Yes kinase structure was obtained from homology modeling and seven ensembles with different active site scaffolds through molecular dynamics (MD) simulations. For SB-PB tandem screening, we modeled ligand bound active and inactive conformations. Physicochemical properties of inhibitors of Src kinase family and c-Yes kinase were used to prepare target focused libraries for screenings. Our screening procedure along with docking showed 520 probable hits in SBVS and tandem screening (120 and 400, respectively). Out of 5000 compounds identified from different computational methods, 2410 were examined using kinase inhibition assays. It includes 266 compounds (5.32%) identified from our method. We observed that 14 compounds (12%) are identified by the present method out of 168 that showed > 30% inhibition. Among them, three compounds are novel, unique, and showed good inhibition. Further, we have studied the binding of these compounds at the DFG-in and DFG-out conformations and reported the probable class (type I or type II). Hence, we suggest that these compounds could be novel drug leads for regulation of colorectal cancer.
Keywords:colorectal cancer  c-Yes kinase  structure-based virtual screening  SBVS  Pharmacophore-based virtual screening  PBVS  type I and type II inhibitors
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