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In Silico Screening of Some Active Phytochemicals to Identify Promising Inhibitors Against SARS-CoV-2 Targets.
Alagarsamy, V; Solomon, V Raja; Murugesan, S; Sundar, P Shyam; Muzaffar-Ur-Rehman, M D; Chandu, Ala; Aishwarya, A Dharshini; Narendhar, B; Sulthana, M T; Ravikumar, V.
Afiliação
  • Alagarsamy V; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India.
  • Solomon VR; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India.
  • Murugesan S; Department of Pharmacy, BITS Pilani, Pilani Campus, Pilani-333031, India.
  • Sundar PS; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India.
  • Muzaffar-Ur-Rehman MD; Department of Pharmacy, BITS Pilani, Pilani Campus, Pilani-333031, India.
  • Chandu A; Department of Pharmacy, BITS Pilani, Pilani Campus, Pilani-333031, India.
  • Aishwarya AD; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India.
  • Narendhar B; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India.
  • Sulthana MT; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India.
  • Ravikumar V; Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India.
Article em En | MEDLINE | ID: mdl-37861016
BACKGROUND: There are very few small-molecule drug candidates developed against SARS-CoV-2 that have been revealed since the epidemic began in November 2019. The typical medicinal chemistry discovery approach requires more than a decade of the year of painstaking research and development and a significant financial guarantee, which is not feasible in the challenge of the current epidemic. OBJECTIVE: This current study proposes to find and identify the most effective and promising phytomolecules against SARS-CoV-2 in six essential proteins (3CL protease, Main protease, Papain- Like protease, N-protein RNA binding domain, RNA-dependent RNA polymerase, and Spike receptor binding domain target through in silico screening of 63 phytomolecules from six different Ayurveda medicinal plants. METHODS: The phytomolecules and SARS-CoV-2 proteins were taken from public domain databases such as PubChem and RCSB Protein Data Bank. For in silico screening, the molecular interactions, binding energy, and ADMET properties were investigated. RESULTS: The structure-based molecular docking reveals some molecules' greater affinity towards the target than the co-crystal ligand. Our results show that tannic acid, cyanidin-3-rutinoside, zeaxanthin, and carbolactone are phytomolecules capable of inhibiting SARS-CoV-2 target proteins in the least energy conformations. Tannic acid had the least binding energy of -8.8 kcal/mol, which is better than the binding energy of its corresponding co-crystal ligand (-7.5 kcal/mol) against 3 CL protease. Also, it has shown the least binding energy of -9.9 kcal/mol with a more significant number of conventional hydrogen bond interactions against the RdRp target. Cyanidin-3-rutinoside showed binding energy values of -8.8 and -7.6 kcal/mol against Main protease and Papain-like protease, respectively. Zeaxanthin was the top candidate in the N protein RBD with a binding score of - 8.4 kcal/mol, which is slightly better when compared to a co-crystal ligand (-8.2 kcal/mol). In the spike, carbolactone was the suitable candidate with the binding energy of -7.2 kcal/mol and formed a conventional hydrogen bond and two hydrophobic interactions. The best binding affinity-scored phytomolecules were selected for the MD simulations studies. CONCLUSION: The present in silico screening study suggested that active phytomolecules from medicinal plants could inhibit SARS-CoV-2 targets. The elite docked compounds with drug-like properties have a harmless ADMET profile, which may help to develop promising COVID-19 inhibitors.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article