PharmaIndustrial India Magazine September-October 2023

Fujitsu and RIKEN Develop AI Drug Discovery Technology to Predict Structural Changes in Proteins Fujitsu Limited and the HPC- and AI-driven Drug Development Platform Division of the RIKEN Center for Computational Sci- ence have developed an AI drug discovery technology that can predict structural changes of proteins from electron micro- scope images as a 3D density map in wide range by utilizing generative AI. The two parties presented a paper on this tech- nology at MICCAI 2023. As part of a joint research project, Fujitsu and RIKEN devel- oped a generative AI technology that accurately estimates the various forms of a target protein’s conformation and their possible proportions from a large number of projection imag- es taken by electron microscopy, as well as a technology that predicts conformational changes in the target protein from the estimated proportions. Based on these two technologies, the two parties developed an AI drug discovery technology that can predict structural changes of a protein in a wide range, with the aim of devel- oping next-generation IT drug discovery technology that sig- nificantly reduces the development time and cost of drug dis - covery. The technology enables the accurate acquisition of protein conformations and changes based on experimental data in more than ten times less time than conventional procedures, thereby enabling innovation in the design process of drugs that bind to target proteins such as bacteria and viruses. Moving forward, Fujitsu and RIKEN will use the newly devel- oped generative AI technology as one of the core technologies for realizing next-generation IT drug discovery technology that can analyze the complex relationships between target proteins and antibodies, and predict global structural changes of mole- cules with high accuracy and speed. Background Proteins that are closely involved in the lifecycles and disease mechanisms of living organisms are naturally very flexible and interact with other molecules in vivo by changing their structure conformation. For example, to develop drugs that suppress in- fection by viruses such as COVID-19 that stimulate its infec- tion with conformational changes on their surface proteins, it is necessary to ascertain the various conformational states of the proteins and how they change between conformations. However, conventional structural analysis methods require a high level of expertise and trial and error, demanding consid- erable time and expenditure to obtain accurate conformational changes. To solve this problem, Fujitsu and RIKEN have devel- oped the following two new drug discovery technologies using generative AI. Two drug discovery technologies Fujitsu and RIKEN developed two new drug discovery tech- nologies by utilizing the know-how cultivated through the de- velopment of Fujitsu’s deep learning technology and applying the knowledge of RIKEN’s drug discovery molecular simulation utilizing supercomputer Fugaku. The combination of the two technologies reduced the time for prediction of conformational changes in a target protein from one day to two hours, thereby TNEECWHSTALK PHARMA INDUSTRIALINDIA · SEP-OCT 23 22