Chawla P.A., Singh D., Dua K., Dhanasekaran M., Chawla V. (ed.) Computational Drug Discovery: Molecular Simulation for Medicinal Chemistry

De Gruyter, 2021. — 441 p.Computational methods and understanding computational models are important in modern drug discovery. The book focuses on computational approaches that can improve the development of in silico methodologies. It includes lead hit methods, docking algorithms, computational chiral compounds, structure-based drug design, GROMACS and NAMD, structural genomics, toxicity prediction, enzyme inhibitors, and peptidomimetic therapeutics.Historical development of computer-aided drug design.
Lead-hit-based methods for drug design and ligand identification.
Virtual screening tools in ligand and receptor-based drug design.
State-of-the-art modeling techniques in performing docking algorithms and scoring.
Design of computational chiral compounds for drug discovery and development.
Role of integrated bioinformatics in structure-based drug design.
Molecular recognizable tools in X-ray crystallography in computer-aided drug design.
Design of target hit molecules using molecular dynamic simulations: special key aspects of GROMACS or Role of molecular dynamic simulations in designing a hit molecule for drug discovery.
Computational prediction of drug-limited solubility and CYP450-mediated biotransformation.
Recent advancement in binding free-energy calculation.
Role of structural genomics in drug discovery.
Unlocking therapeutic potential: computational approaches for enzyme inhibition discovery.
Role of spectroscopy in drug discovery.
Computer-aided design of peptidomimetic therapeutics.
Developing safer therapeutic agents through toxicity prediction.
Identifying prominent molecular targets in the fight against drug resistance.