High-Throughput Virtual Screening (HTVS) of Natural Compounds and Exploration of Their Biomolecular Mechanisms: An In Silico Approach

Abstract

High-throughput virtual screening (HTVS) methods have played a cardinal role in the development of therapeutically important natural compounds. HTVS allows scientists to rapidly perform millions of chemical, biological, pharmacological, or toxicological tests on natural compounds. These screening procedures enable the researchers to rapidly identify active natural compounds that can modulate a particular biomolecular mechanism or pathway. The screening results help to study the interaction/role of a bioactive compound in a particular biochemical process at cellular level and provide preliminary ideas for drug design development. These methods are generally classified as either ligand based or structure based. Structure-based methods are in principle analogous to high-throughput screening where the information of both biomolecular target and ligand structure is essential. Structure-based approaches include docking, simulations, dynamics, and ligand design methods. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. Here, we discuss the widely used techniques, tools, and databases for virtual screening of natural compounds. Finally, computational methods for absorption, distribution, metabolism, excretion - and toxicity (ADMET) prediction are discussed.