A Structure-Based Drug Discovery Paradigm

International Journal of Molecular Sciences

Maria Batool¹  Sangdun Choi¹  Bilal Ahmad¹ 

[1] Department of Molecular Science and Technology, Ajou University, Suwon 16499, Korea;

关键词: deep learning;    artificial intelligence;    neural network;    structure-based drug discovery;    virtual screening;    scoring function;   

DOI  :  10.3390/ijms20112783

来源: DOAJ

【 摘 要 】

Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the “big data” generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.

【 授权许可】

Unknown