Abstract

One of the most widely used computational approaches for drug discovery and optimization is structure-based virtual screening (SBVS). This technique utilizes three-dimensional structures of the targets for discovering novel lead compounds. SBVS is emerging as an ideal tool in the drug designing and discovery process. It is a computer-based approach that catalyzes the drug discovery process. It is cost effective and saves precious time and resources. SBVS, also popularly known as target-based virtual screening, uses different in silico techniques and software to assess the best possible interactions between two molecules in order to form a stable complex. Virtual screening assesses the affinity of the ligand molecules and identifies its binding groups to the active site of the receptor/enzyme, and predicts the best binding mode of the ligand to the target molecule. SBVS is known for better predictive performance over other in silico techniques, as it ranks compounds on the basis of scoring and free energy functions by the docking process. The process can be performed using a single software or a combination of software as this reduces the chance of correlations/findings. Scoring functions are identified with the success or failure of the virtual screening process. In this chapter different aspects of the SBVS technique and software tools used for the drug designing and discovery process are discussed.

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