Screening of Some Ayurvedic Phytochemicals to Identify Potential Inhibitors against SARS-CoV-2 Mpro by In Silico Computational Approach

Veerachamy Alagarsamy; Subramanian Nivedhitha; Manavalan Gopinath; Kavitha Kunchu; Rupeshkumar Mani; Vemulapalli Ravikumar; Alagarsamy Aishwarya; Viswas Solomon; Mohaideen Sulthana; Bandi Narendhar; Potabathula Shyamsundar; Periyasamy Parthiban

doi:10.2174/0122113525255835240107162255

Screening of Some Ayurvedic Phytochemicals to Identify Potential Inhibitors against SARS-CoV-2 Mpro by In Silico Computational Approach

作者: Alagarsamy V.¹, Nivedhitha S.², Gopinath M.², Kunchu K.³, Mani R.⁴, Ravikumar V.¹, Aishwarya A.¹, Solomon V.¹, Sulthana M.¹, Narendhar B.¹, Shyamsundar P.¹, Parthiban P.⁵
隶属关系:
1. Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy, 502 294, India
2. Swathi College of Pharmacy, SPSR Nellore, 524 320, Andhra Pradesh, India
3. Department of Pharmacy, NITTE College of Pharmaceutical Sciences, Bangalore, 560 064, India
4. Department of Pharmacology, Sri Adichunchanagiri College of Pharmacy, B.G. Nagara, 571 448, India
5. Vellalar College of Pharmacy, Thindal Post, Erode, 638012, Tamilnadu, India
期: 卷 22, 编号 5 (2024)
栏目: Medicine
URL: https://rjmseer.com/2211-3525/article/view/642329
DOI: https://doi.org/10.2174/0122113525255835240107162255
ID: 642329

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Background:The classical drug discovery approach demands more than a decade of strenuous exploration and substantial monetary or economic support, which is difficult in pandemic conditions, such as COVID-19.

Methods:The main purpose of this work was to ascertain the best inhibitors to combat the SARS-CoV-2 Mpro (PDB ID: 6LU7) target. To achieve this, we conducted a molecular docking screening of 35 phytochemicals from eight different medicinal plants. Using a structure-based drug design of molecular docking, we studied the binding affinities and found 35 molecules that showed greater or identical affinity towards the target than the N3 inhibitor. Additionally, we conducted MD simula-tions for the 6LU7-schaftoside complex.

Results:The docking analysis has identified several promising phytochemicals with great binding attraction towards the key target. The phytoconstituent, schaftoside (-8.7 kcal/mol), demonstrated the most binding attraction with the target via 6 conventional hydrogen bonds. Additionally, 2'-O-methyl cajanone (-8.3 kcal/mol), isoschaftoside (-8.0 kcal/mol), cajaflavonone (-8.0 kcal/mol), and co-crystal N3 inhibitor (-7.8 kcal/mol) also displayed significant binding affinity. Interestingly, schaftoside and 2-O-methyl cajanone showed the most promising activities with their low binding energies.

Conclusion:After thorough analysis, some compounds were found on elite docking sites that re-sembled drugs and had a harmless ADMET profile. Based on the study, it can be concluded that the compounds mentioned earlier possess the ability to be reused as potent inhibitors against the COVID-19 pandemic.

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COVID-19, SARS-CoV-2, molecular docking, MD simulation, medicinal plants, ADMET.

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Screening of Some Ayurvedic Phytochemicals to Identify Potential Inhibitors against SARS-CoV-2 Mpro by In Silico Computational Approach

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