Paper Contents
Abstract
Plant-derived compounds, known for their rich chemical diversity and bioactive properties, have played a pivotal role in drug discovery. These natural products provide a vast reservoir of potential therapeutic agents for treating various diseases. Molecular docking, a computational technique used to predict the interaction between small molecules and biological targets, has become an indispensable tool in evaluating the pharmacological potential of these compounds. By simulating ligand-receptor binding, molecular docking aids in understanding the binding affinity, stability, and specific interactions of plant-derived compounds with target proteins. This review explores the significance of molecular docking in identifying and optimizing lead compounds from plants, highlighting key discoveries, challenges in predicting accurate interactions, and the integration of docking studies with experimental validations. While molecular docking accelerates the early phases of drug discovery, challenges such as flexibility in target proteins and accurate scoring functions persist. Future advancements in computational techniques and integration with machine learning could further enhance the precision and reliability of docking studies, paving the way for more effective drug discovery from plant sources.
Copyright
Copyright © 2024 Chaitali Shantaram Dawange1. This is an open access article distributed under the Creative Commons Attribution License.
