Computational Medicinal Chemistry for Drug Design and Discovery

Computational chemistry methods are using physicochemical-based algorithms andcomputers to simulate chemical events for computing chemical properties of atoms andmolecules. In drug design and discovery, diverse computational chemistry approaches are usedto calculate and predict events, such as the new medications based on the knowledge of abiological target. The drug is most commonly an organic small molecule that activates or inhibitsthe function of a biomolecule such as a protein, DNA and RNA, which in turn results in atherapeutic benefit to the patient. Computer-aided drug design (CADD) approaches have playeda major role in improving and developing of therapeutically important small ligands for threedecades. The methods of CADD are broadly classified as either structure-based drug design(SBDD), when structural data of the target protein are available, and ligand-based drug design(LBDD), when structural information of the target is missing or not fully reliable. Overall, thesemethods facilitate the identification of promising chemical scaffolds that interfere favorably withthe target’s function, producing a positive pharmacological effect. The widely usedcomputational methods and role of computational medicinal chemistry for the ligand-basedpharmacophores, molecular descriptors, and quantitative structure-activity relationships arediscussed with successful examples from literature and/or our findings.

Computational Medicinal Chemistry for Drug Design and Discovery Keywords:

Drug Design , DFT , Docking , MD