Abstract
Chemical biology and computer-aided drug design (CADD) are crucial for identifying and optimizing lead molecules in drug development. Chemical biology is employed to determine the biological function of the target and the mode of action of a chemical modulator. At the same time, in CADD, promising candidate medications are identified based on the structure of the target or known bioactive ligands. Structure-based and ligand-based drug designs should be used in tandem, and their integration with experimental methods can considerably accelerate drug design. Furthermore, the use of CADD along with conventional experimental approaches increases the efficiency and accuracy of the discovery and optimization of possible drug candidates. CADD provides information on the interactions between pharmaceuticals and their target molecules, with recent advances in CADD methodologies—such as artificial intelligence and machine learning—revolutionizing the field. Thus, CADD is expected to notably accelerate the development of novel, efficient treatments for a range of illnesses.
Recommended Citation
Chandramouli, Manasa and Surendra, Madhusudhan Heggadadevanakote
(2025)
"Pharmaceutical Innovation Through Computational Drug Design: A Comprehensive Exploration,"
Makara Journal of Science: Vol. 29:
Iss.
2, Article 6.
DOI: 10.7454/mss.v29i2.2629
Available at:
https://scholarhub.ui.ac.id/science/vol29/iss2/6