Exploring plant-based antivirals using computer-aided drug design: evidence from the Indo-Gangetic plain
Suvendu Ghosh, Ramkrishna Ghosh, Lakshmi Kanta Das, Partha Sarathi Singha, Debosree GhoshAbstract
Background:
The Indo-Gangetic plain is characterized by rich botanical diversity, including a wide range of medicinal plants that produce bioactive phytocompounds with notable antiviral potential.
Objective:
This review emphasizes the role of computer-aided techniques in the efficient, cost-effective exploration of antiviral phytocompounds derived from these plant resources.
Materials and Methods:
Computer-aided approaches, such as molecular docking, virtual screening, and molecular dynamics simulations, have been used to identify and evaluate phytocompounds with strong binding affinity for key viral targets, including proteases, polymerases, and viral entry proteins. In addition, advanced technologies incorporating artificial intelligence and machine learning are increasingly used to accelerate screening and discovery while reducing costs. Common viral targets investigated in computer-aided drug design (CADD)-based studies include Mpro, RdRp, NS3, and spike proteins.
Results:
This review outlines CADD strategies for discovering, optimizing, and validating antiviral phytocompounds from plants native to the Indo-Gangetic plain. It highlights CADD’s considerable potential to accelerate the identification of novel antiviral agents from India’s extensive botanical resources. CADD has been widely used to identify lead compounds against viruses such as influenza, dengue, severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), human immunodeficiency virus, hepatitis viruses, and human papillomavirus. Thousands of antiviral phytocompounds have already been identified from plant sources, with many more likely to be discovered from nature’s vast reservoir. Notably, the antiviral phytochemical database includes 2537 antiviral phytochemicals derived from 383 plant species, many of which have been identified and validated using CADD approaches. Furthermore, an in-house library of 1163 antiviral phytochemicals from the Natural Product Activity and Species Source database and PubChem databases was screened against SARS-CoV-2 using CADD methods, yielding 140 promising small-molecule candidates (reported in a 2023 study published in the International Journal of Molecular Sciences).
Discussion:
Given the ongoing mutation and evolution of viral pathogens, there is an urgent need to adopt advanced computational strategies to accelerate and enhance the discovery of effective antiviral agents. Plant-derived compounds, often associated with fewer adverse effects, are a valuable and underexplored resource in this context.
Conclusion:
Novel antiviral phytocompounds hold substantial promise for the development of effective therapies against pathogenic and drug-resistant viruses. Integrating modern computer-aided techniques with conventional drug development approaches can significantly improve efficiency, reduce costs, and enhance outcomes in antiviral drug discovery. This review offers a concise overview of recent advances in CADD-assisted identification of antiviral phytocompounds from medicinal plants of the Indo-Gangetic plain. It lays a foundation for future research in this field.