CADD is a cutting-edge computational method used to locate and develop a promising lead in the drug discovery process. Molecular modelling, molecular design, computational chemistry, and rational drug design are all components of computer-aided drug design. To maximise discovered leads, CADD is being employed. Both in academic communities and the pharmaceutical companies, CADD approaches are becoming more well-liked and respected. Time is saved, and the CADD technique is quick and economical. The four steps of the CADD method are as follows: (1) use a virtual screening (VS) protocol to screen a small molecule library against the target to find hits or leads, (2) examine the specificity of the selected hits from VS using molecular docking in the active site of other recognized targets, and (3) predict ADMET properties of the selected hit using in silico techniques and the most promising hits are referred to as leads and step four assists in optimizing the leads by creating better compounds for synthesis and testing. Structure-based and ligand-based drug design are the two categories into which CADD approaches are divided depending on the availability of the target protein's 3D structure (SBDD and LBDD). The pharmacological target's 3D structure is necessary for SBDD. The target structure can be obtained in one of two ways: (1) by downloading it from the Protein Data Bank (PDB) if the protein structure has been solved by crystallography and (2) employ molecular modeling (a bioinformatics technique) to forecast the structure if the protein structure cannot be determined.
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