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학술발표회초록보기

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  • 09월 03일 23시 이후 : 초록수정 불가능, 일정확인 및 검색만 가능

제122회 대한화학회 학술발표회, 총회 및 기기전시회 안내 Development and Application of a Comprehensive Artificial Intelligence Program for Predicting Biochemical and Pharmacological Properties of Organic Molecules

등록일
2018년 9월 3일 18시 09분 31초
접수번호
2207
발표코드
PHYS2-1 이곳을 클릭하시면 발표코드에 대한 설명을 보실 수 있습니다.
발표시간
금 09시 : 00분
발표형식
심포지엄
발표분야
Physical Chemistry - Data-Enabled Computational Chemistry
저자 및
공동저자
Hwangseo Park
Department of Bioscience and Biotechnology, Sejong University, Korea

We establish a comprehensive quantitative structure-activity relationship (QSAR) model termed AlphaQ through the artificial intelligence algorithm to associate the fully quantum mechanical molecular descriptors with various biochemical and pharmacological properties. Preliminarily, a novel method for molecular structural alignments was developed in such a way to maximize the quantum mechanical cross correlations among the molecules. Besides the improvement of structural alignments, three-dimensional (3D) distribution of the molecular electrostatic potential was introduced as the unique numerical descriptor for individual molecules. These dual modifications lead to a substantial accuracy enhancement in multifarious 3D-QSAR prediction models of AlphaQ. Most remarkably, AlphaQ proves applicable to structurally diverse molecules to the extent that it outperforms the conventional QSAR methods in estimating the inhibitory activity against thrombin, the water-cyclohexane distribution coefficient, the permeability across the membrane of Caco-2 cell, and the metabolic stability in human liver microsomes. Due to the simplicity in model building and the high predictive capability for varying biochemical and pharmacological properties, AlphaQ is anticipated to serve as a valuable screening tool at both early and late stage of drug discovery.


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