In collaboration with Gisbert Schneider’s research team of ETH Zurich, Department of Chemistry and Applied Biosciences,Professor Shengyong Yang’s research team of State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University has published online a review “Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery” inChemical Reviews,which is an authoritative journal in the field of chemistry. The first author of this research paper is Dr. Xin Yang of State Key Laboratory of Biotherapy and Cancer Center, West China Hospital. Professor Shengyong Yang and Professor Gisbert Schneider are the corresponding authors. The State Key Laboratory of Biotherapy and Cancer Center, West China Hospital is the first work unit.
In recent years, artificial intelligence (AI) technology, represented by deep learning, has achieved rapid development. It is considered an important driving force for the new round of scientific and technological revolution and industrial change. It also brings new hope for accelerating innovative drug research and development. AI-assisted drug discovery promotes the transition of drug research and development from traditional mode which has target and structural information as the core to a new one with data and algorithm as the core. At present, deep learning has been successfully applied to image recognition, automatic driving, human intelligence games and other fields, and great success has been achieved. Nevertheless, due to the particularity of innovative drug research and development, such as molecular characterization, small samples, and the lack of common deep learning methods, the application of deep learning in innovative drug research and development is limited.
“This review provides a comprehensive portrayal of these machine learning techniques and of their applications in medicinal chemistry. After introducing the basic principles, alongside some application notes, of the various machine learning algorithms, the current state-of-the art of AI-assisted pharmaceutical discovery is discussed, including applications in structure- and ligand-based virtual screening, de novo drug design, physicochemical and pharmacokinetic property prediction, drug repurposing, and related aspects.” ( Abstract )
In the end, the authors have summarized several challenges and limitations of the current methods, with a view to potential future directions for AI-assisted drug discovery and design.
Professor Shengyong Yang serves as deputy editor of Signal Transduction and Targeted Therapy journals and editorial board member of several international journals. He won the second prize of National Natural Science, the first prize of Natural Science of the Ministry of Education, and the Life Chemistry Scholar Prize of WuXi Apptec Co., Ltd. The team is mainly engaged in computer-assisted drug molecular design and applications, as well as small molecule targeted drug research for major diseases. Up to now, they have published more than 200 SCI papers in top journals in this field. What’s more, the team has applied for more than 80 patents and over 30 patents have been authorized, including 12 international patents. Six new drug candidates have been transferred to pharmaceutical companies, two of which have entered clinical trials.
Article link:https://pubs.acs.org/doi/10.1021/acs.chemrev.8b00728
