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    Rho-associated, coiled-coil-containing protein kinase (ROCK1) regulates cell contraction, morphology, and motility by phosphorylating its downstream targets. ROCK1 is a proven target for many pathological conditions like cancer, atherosclerosis, glaucoma, neuro-degeneration, etc. Though many kinase inhibitors are available, there is a dearth of studies on repurposing approved drugs and novel peptide inhibitors that could potentially target ROCK1. Hence, in this study, an extensive integration of open-source pipelines was employed to probe the potential inhibitors (ligand/peptide) for targeting ROCK1. To start with, a systematic enrichment analysis was performed to delineate the most optimal ROCK1 crystal structure that can be harnessed for drug design. A comparative analysis of conformational flexibility between monomeric and dimeric forms was also performed to prioritize the optimal assembly for structural studies. Subsequently, Virtual screening of FDA-approved drugs in Drugbank was performed using POAP pipeline. Further, the top hits were probed for binding affinity, crucial interaction fingerprints, and complex stability during MD simulation. In parallel, a combinatorial tetrapeptide library was also virtually screened against ROCK1 using the PepVis pipeline. Following which, all these shortlisted inhibitors (compounds/peptides) were subjected to Kinomerun analysis to infer other potential kinase targets. Finally, Polydatin and conivaptan were prioritized as the most potential repurposable inhibitors, and WWWF, WWVW as potential inhibitory peptides for targeting ROCK1. The prioritized inhibitors are highly promising for use in therapeutics, as these are resultants of the multilevel stringent filtration process. The computational strategies implemented in this study could potentially serve as a scaffold towards selective inhibitor design for other kinases.Communicated by Ramaswamy H. Sarma.


    Samdani Ansar, Umashankar Vetrivel. Structure-based design of small molecule and peptide inhibitors for selective targeting of ROCK1: an integrative computational approach. Journal of biomolecular structure & dynamics. 2021 Mar 10:1-19

    PMID: 33715594

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