Pharmacoinformatics in identifying therapeutically important chemical species from Ayurvedic formulations employed in treating COVID-19 patients

药物信息学在识别用于治疗新冠肺炎患者的阿育吠陀配方中具有治疗意义的化学物质方面的应用

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Abstract

BACKGROUND: Ayurveda provided many innovative solutions during the COVID-19 pandemic. It is important to explore the phytochemical constituents in effective Ayurvedic formulations. OBJECTIVE: The main aim of the work is to identify active phytoconstituents from five Ayurvedic formulations employed in treating COVID-19 patients in an Ayurvedic hospital. MATERIAL AND METHODS: Pharmacoinformatics technologies were employed in this study. The chemoinformatics, 3D molecular structure building, and molecular docking of 967 compounds on eight different macromolecular viral targets associated with SARS-CoV-2 were carried out using GLIDE software. Molecular dynamics simulations were also performed. SwissADME web server was employed to determine the physicochemical, lipophilicity and absorption, distribution, metabolism, and excretion (ADME) parameters. RESULTS: The molecular docking results indicate that quercetin-3-O-arabinoglucoside, quercetin-3,7-O-diglucoside, glycyrrhizin, calceolarioside B, mucic acid-2-gallate, protodioscin and indioside D are the phytochemicals which effectively bind to eight of the proteins of SARS-CoV-2 virus and these may be treated as new lead compounds for multi-target drug discovery for SARS-CoV-2 inhibition. MD simulations helped in identifying five leads out of seven chosen from docking analysis. CONCLUSION: Five Ayurvedic formulations were used to treat respiratory illnesses associated with COVID-19. Five phytoconstituents present in these formulations were identified as leads by employing pharmacoinformatics techniques.

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