02340nas a2200289   4500008004100000022001400041245008700055210006900142260000900211300001400220490000800234520143200242653002101674653001101695653001801706653003301724653001501757100002201772700002001794700002501814700001801839700001801857700002101875700002301896700001701919856011401936       2021                        eng d  a0011-389100aAntiviral drugs prioritization for COVID-19 management based on rational selection0 aAntiviral drugs prioritization for COVID19 management based on r  cMAY   a1464-14700 v1203 a<p>The SARS-CoV-2 infection has resulted in COVID-19 pandemic worldwide. It has infected around 0.1 billion individuals and caused 2 million fatalities across the globe till mid-January 2021. Drug repurposing has been utilized as the most preferred therapeutic intervention for COVID-19 mitigation due to its necessity and feasibility. To prioritize therapeutic regime against COVID-19, we used 61 antiviral drugs and their combinations. Selected molecules were subjected to virtual screening against: (i) human angiotensin-converting enzyme 2 receptor binding domain (hACE-2) which serves as an anchor for virus attachment and entry, (ii) SARS-CoV-2 RNA dependent RNA polymerase (RdRp) responsible for viral RNA replication, and (iii) SARS-CoV-2 main protease (M-Pro) needed for viral polyprotein slab proteolytic processing. Based on docking score, pharmacodynamic and pharmacokinetic parameters, combinations of Daclatasvir, Elbasvir, Indinavir, Ledipasvir, Paritaprevir and Rilpivirine were analysed further. Our analysis suggested Sofosbuvir in combination with Ledipasvir and Daclatasvir as potential therapeutic agents for SARS-CoV-2. The combined score suggests that these combinations have superior anti-SARS-CoV-2 potential than Remdesivir and other investigational drugs. The present work provides a rationale-based approach to select drugs with possible anti-SARS-CoV-2 activity for further clinical evaluation.</p>10aDrug repurposing10ahACE-210amain protease10aRNA dependent RNA polymerase10aSARS-CoV-21 aJoshi, Rakesh, S.1 aGiri, Ashok, P.1 aKulkarni, Mahesh, J.1 aGupta, Mahesh1 aVerma, Savita1 aChaudhry, Dhruva1 aDeshmukh, Narendra1 aChugh, Anita  uhttp://library.ncl.res.in/content/antiviral-drugs-prioritization-covid-19-management-based-rational-selection02767nas a2200265   4500008004100000022001400041245013800055210006900193260000900262300001400271490000700285520182600292653002702118653002102145653002202166653003002188653004202218653002202260100002002282700002002302700000502322700003302327700001502360856012602375       2023                        eng d  a0739-110200aComprehensive molecular docking and dynamic simulations for drug repurposing of clinical drugs against multiple cancer kinase targets0 aComprehensive molecular docking and dynamic simulations for drug  cNOV   a7735-77430 v413 a<p>
	Drug repurposing is a method to identify novel therapeutic agents from the existing drugs and clinical compounds. In the present comprehensive work, molecular docking, virtual screening and dynamics simulations were carried out for ten cancer types viz breast, colon, central nervous system, leukaemia, melanoma, ovarian, prostate, renal and lung (non-small and small cell) against validated eighteen kinase targets. The study aims to understand the action of chemotherapy drugs mechanism through binding interactions against selected targets via comparative docking simulations with the state-art molecular modelling suits such as MOE, Cresset-Flare, AutoDock Vina, GOLD and GLIDE. Chemotherapeutic drugs (n = 112) were shortlisted from standard drug databases with appropriate chemoinformatic filters. Based on docking studies it was revealed that leucovorin, nilotinib, ellence, thalomid and carfilzomib drugs possessed potential against other cancer targets. A library was built to enumerate novel molecules based on the scaffold and functional groups extracted from known drugs and clinical compounds. Twenty novel molecules were prioritised further based on drug-like attributes. These were cross docked against 1MQ4 Aurora-A Protein Kinase for prostate cancer and 4UYA Mitogen-activated protein kinase for renal cancer. All docking programs yielded similar results but interestingly AutoDock Vina yielded the lowest RMSD with the native ligand. To further validate the final docking results at atomistic level, molecular dynamics simulations were performed to ascertain the stability of the protein-ligand complex. The study enables repurposing of drugs and lead identification by employing a host of structure and ligand based virtual screening tools and techniques. Communicated by Ramaswamy H. Sarma</p>
10achemotherapeutic drugs10aDrug repurposing10aMolecular docking10amolecular simulation (MD)10astructure-based drug designing (SBDD)10avirtual screening1 aShaikh, Nilofer1 aLinthoi, R., K.1 a1 aKarthikeyan, Muthukumarasamy1 aVyas, Renu  uhttp://library.ncl.res.in/content/comprehensive-molecular-docking-and-dynamic-simulations-drug-repurposing-clinical-drugs