In Silico Methods of Assessing the Therapeutic Potential of Natural Substances

Dear Colleagues,

The exploration of naturally occurring substances for therapeutic applications has entered a new era with the advancement of computational methods. This Special Issue focuses on cutting-edge in silico approaches for evaluating the therapeutic potential of natural compounds, bringing together research that bridges traditional natural product discovery with modern computational techniques. We welcome studies involving molecular docking, machine learning applications, QSAR modeling, molecular dynamics simulations, and other computational methods that advance our understanding of natural substances' biological activities and drug-like properties. The issue particularly emphasizes research combining multiple computational approaches to predict, analyze, and optimize the therapeutic potential of compounds derived from natural sources, including plants. Original research articles, comprehensive reviews, and methodological papers addressing challenges and innovations in computational assessment of natural products are encouraged. Topics of interest include, but are not limited to, virtual screening of natural compound libraries, prediction of ADMET properties, target identification, and structure-activity relationship analyses. This Special Issue aims to showcase how in silico methods can accelerate the discovery and development of natural substance-based therapeutics while reducing the time and resources required for traditional experimental approaches.

Prof. Dr. Radosław Zajdel
Dr. Anna Merecz-Sadowska
Guest Editors

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