Xaiohua Zhang , Jianhui Li

Institute of Life Sciences, Jiyang Colloge of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
Computational Molecular Biology, 2024, Vol. 14, No. 3   doi: 10.5376/cmb.2024.14.0014
Received: 09 Apr., 2024    Accepted: 24 May, 2024    Published: 13 Jun., 2024

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Zhang X.H., and Li J.H., 2024, Exploration of the role of computational chemistry in modern drug discovery, Computational Molecular Biology, 14(3): 115-124 (doi: 10.5376/cmb.2024.14.0014)

This study explores the fundamental principles of computational chemistry, such as quantum mechanics and molecular modeling, and investigates their applications in drug design, including structure based and ligand based methods. Emphasis was placed on the integration of advanced technologies such as machine learning and high-throughput virtual screening, highlighting their role in improving prediction accuracy and accelerating drug development. However, challenges such as prediction reliability, computational cost, and integration of computational data with experimental results still exist. The case study demonstrated the effectiveness of the computational method and compared it with traditional methods in developing successful candidate drugs. Looking to the future, the potential of combining computational chemistry and omics data and their role in advancing personalized medicine. Future drug discovery is likely to rely on collaborative platforms and open-source tools to push the boundaries of computational innovation.

Computational chemistry; Drug discovery; Molecular modeling; Machine learning; Structure-based design