Development of lead optimization method using novel profile data analysis method

2020 Fiscal Year Final Research Report

• Project/Area Number: 19K22485
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 47:Pharmaceutical sciences and related fields
• Research Institution: The University of Tokyo
• Principal Investigator: Kusuhara Hiroyuki 東京大学, 大学院薬学系研究科(薬学部), 教授 (00302612)
• Co-Investigator(Kenkyū-buntansha): 水野 忠快 東京大学, 大学院薬学系研究科(薬学部), 助教 (90736050)
• Project Period (FY): 2019-06-28 – 2021-03-31
• Keywords: プロファイル解析 / OLSA / リード化合物最適化 / 構造類似体 / 潜在的作用

Outline of Final Research Achievements

Our novel profile data analysis method, orthogonal linear separation analysis (OLSA), can visualize even off-target-derived drug action. We aimed to establish a lead compound optimization support system using this analysis method. According to the analysis of 293 compounds, we focused on resinnamine (RES) and syrosingopine, which are quite similar in structure. As suggested, we confirmed their HDAC inhibitory action and mTORC inhibitory action in vitro. Notably, SREBP activating action, which presumed to be higher in RES, could be also reproduced in vitro. It was clarified that the similarities and differences in the actions of structurally similar compounds can be estimated by decomposing their actions using our analysis method. Since the effects of RES and syrosingopine detected in this study have not been reported yet, the approach developed in this study is useful to uncover unrecognized effects of compounds, and hence, contribute to derivatization strategies in lead optimization.

Free Research Field

薬物動態学

Academic Significance and Societal Importance of the Research Achievements

オフターゲット効果は薬物のリポジショニングや有害事象発現に関連しており、その検出方法の開発は、医薬品開発において重要な課題である。本研究で提唱した低分子医薬品の作用を分離して理解するというアプローチが、化合物の潜在的な作用の検出を通じて、目的に掲げたリード化合物最適化に資するものであることを強く支持するものであり、医薬品開発に大きく貢献するものと考える。