The 70th JSAP Spring Meeting 2023

Presentation information

Poster presentation

12 Organic Molecules and Bioelectronics » 12.6 Nanobiotechnology

[16p-PB02-1~15] 12.6 Nanobiotechnology

Thu. Mar 16, 2023 4:00 PM - 6:00 PM PB02 (Poster)

4:00 PM - 6:00 PM

[16p-PB02-14] Machine learning assisted improvement of evaluation scheme of FMO-DPD

Sota Matsuoka1, Hideo Doi1, Koji Okuwaki1, Ryo Hatada1, Sojiro Minami1, Ryosuke Suhara1, Yuji Mochizuki1,2 (1.Rikkyo Univ., 2.Univ. Tokyo)

Keywords:machine learning, FMO, DPD

The effective interaction (χ) parameters in dissipative particle dynamics (DPD) simulations can be evaluated by using the fragment molecular orbital (FMO) based Chi-parameter Evaluation Workflow System (FCEWS). The total cost of FCEWS usage is completely dominated by FMO calculations, thus its reduction is of special interest. In this study, we have tried to improve the efficiency of evaluations with machine learning technique and developed a workflow system (pre_fcews).