Recent Advancements in the Application of Artificial Intelligence in Drug Molecular Generation and Synthesis Planning - Buyong Ma; Yiguo Wang; Xingzi Li; Chang Shen; Hao Lin; Chenxi Du; Shanlin Yang; Ruoqing Zeng; Xuyang Tang; Jinglei Hu; Yukun Yang; Jingwen Wang; et al. (Pharmaceutical Fronts)
The design and synthesis of drug molecules is a pivotal stage in drug development that traditionally requires significant investment in time and finances. However, the integration of artificial intelligence (AI) in drug design accelerates the identification of potential drug candidates, optimizes the drug development process, and contributes to more informed decision-making. The application of AI in molecular generation is changing the way researchers explore the chemical space and design novel compounds. It accelerates the process of drug discovery and materials science, enabling rapid exploration of the vast chemical landscapes for the identification of promising candidates for further experimental validation. The application of AI in predicting reaction products accelerates the synthesis planning process, contributes to the automation of synthetic chemistry tasks, and supports chemists in making informed decisions during drug discovery. This paper reviewed the recent advances in two interrelated areas: the application of AI in molecular generation and synthesis routes. It will provide insights into the innovative ways in which AI is transforming traditional approaches in drug development and predict its future progress in these key fields.