Sivaramakrishnan, V. Ilamathi, M. Girish, K.S. Kemparaju, K. Rangappa, K.S. Lakkappa Dhananjaya, Bhadrapura Viper venom hyaluronidase and its potential inhibitor analysis: a multipronged computational investigation <p>Viper venom hyaluronidase (VV-HYA) inhibitors have long been used as therapeutic agents for arresting the local and systemic effects caused during its envenomation. Henceforth, to understand its structural features and also to identify the best potential inhibitor against it the present computational study was undertaken. Structure-based homology modeling of VV-HYA followed by its docking and free energy-based ranking analysis of ligand, the MD simulations of the lead complex was also performed. The sequence analysis and homology modeling of VV-HYA revealed a distorted (β/α)<sub>8</sub> folding as in the case of hydrolases family of proteins. Molecular docking of the resultant 3D structure of VV-HYA with known inhibitors (compounds 1–25) revealed the importance of molecular recognition of hotspot residues (Tyr 75, Arg 288, and Trp 321) other than that of the active site residues. It also revealed that Trp 321 of VV-HYA is highly important for mediating π–π interactions with ligands. In addition, the molecular docking and comparative free energy binding analysis was investigated for the VV-HYA inhibitors (compounds 1–25). Both molecular docking and relative free energy binding analysis clearly confirmed the identification of sodium chromoglycate (compound 1) as the best potential inhibitor against VV-HYA. Molecular dynamics simulations additionally confirmed the stability of their binding interactions. Further, the information obtained from this work is believed to serve as an impetus for future rational designing of new novel VV-HYA inhibitors with improved activity and selectivity.</p> inhibitor;hyaluronidase;sodium chromoglycate;MM-GBSA;molecular docking 2016-07-11
    https://tandf.figshare.com/articles/journal_contribution/Viper_venom_hyaluronidase_and_its_potential_inhibitor_analysis_a_multipronged_computational_investigation/3479651
10.6084/m9.figshare.3479651.v1