Tatsuya Takagi
Osaka University, Japan
Title: SBDD of MDM2 and β-secretase inhibitors using FMO and machine learning
Biography
Biography: Tatsuya Takagi
Abstract
MDM2 (Mouse double minute 2 homolog) is known as a protein which is a significant negative regulator of p53. MDM2 is also considered to be E3 ubiquitin-protein ligase recognizing the N-terminal TAD (Transactivation Domain). Thus, MDM2-p53 interactions are proposed to be a promising therapeutic strategy for tumors. Previously, we reported a part of the FMO (Fragment Molecular Orbital) calculation results of MDM2 and its inhibitors at the 11th China-Japan Joint Symposium on Drug Design and Development. Although we showed a satisfactory result, we also thought the result could be improved using PIEDA (Pair Interaction Energy Decomposition Analysis). In this study, we added some FMO results and tried to obtain a better correlation using data mining methods, such as PLS. First, we selected significant 18 IFIE (Inter Fragment Interaction Energy) values and 45 electrostatic interaction energies as the results of PIEDA from 84 ones. Then we obtained two latent variables as the results of PLS and cross validations. Resulted scatter plot of the two latent variables. In this case, the best-squared correlation coefficient values between observed and calculated pIC50 of MDM2, 0.924, was obtained. FMO calculation results between β-secretase and inhibitors also will be shown.