Computer-Aided Drug Design (CADD): An approach for Drug Discovery in Bioinformatics

CADD is a new computer tool for identifying and developing a possible lead in drug development. Computational chemistry, molecular modelling, molecular design, and rational drug design are examples of computer-aided drug design. CADD is being utilized to improve the quality of leads that have been identified. CADD approaches are gaining favour and acceptance in both academic circles and the pharmaceutical industry. The CADD method saves time, is quick, and is cost-effective. The CADD method can be applied in four stages: (1) identify hits/leads by screening a small molecule library against the target using a virtual screening (VS) protocol, (2) Using molecular docking in the active site of additional known targets, assess the specificity of the selected VS hits, (3) predict ADMET properties of the selected hit using in silico techniques, and promising hits are referred to as leads, and (4) assists in the optimization of the leads by designing better molecules for synthesis and testing. CADD approaches are classified into two forms based on the availability of the target protein’s 3D structure: structure-based and ligand-based drug design (SBDD and LBDD).

The 3D structure of the pharmacological target is required for SBDD. There are two approaches to obtain the target structure: (1) if the protein structure has been solved by crystallography, download it from the protein databank (PDB); and (2) if the protein structure has not been solved, predict the structure using molecular modelling (a bioinformatics tool). For soluble proteins that can be crystallized, structure-based CADD is preferable. In contrast, ligand-based CADD is better suited for compounds with high binding affinity to the target, no off-target effects, and can be designed with minimal free energy, favourable drug metabolism, and pharmacokinetic/ADMET properties. In general, CADD is better suited to situations when structural knowledge is limited. When it comes to membrane protein targets, this is frequently the case.

Reference

  1. Fernando D. Prieto-Martinez Edgar Lopez-LopezK. Euridice Juarez-MercadoJose L. Medina-Franco, Computational Drug Design Methods—Current and Future Perspectives in In Silico Drug Design, 2019.