Construction of conformation database for QSAR

Abstract

To advance the research on quantitative structure activity correlation (QSAR) and quantitative physical property correlation (QSPR) using deep neural networks (DNNs), it is necessary to prepare a large number of conformation information as the learning dataset, Although most of the available public molecular databases currently provide 2D molecular information and/or with a single 3D structure data. Therefore, we have developed a laboratory localized database C3DB (Computational Chemistry Conformation DataBase) system which records numerous conformers obtained by conformational search and three-dimensional structure information optimized by quantum chemical calculation. The C3DB system consists of an API server that provides WUI, and a DB server that provides the functions for converting molecular structure information into XML format and storing it into the database (DB). An XML format used in the DB server is uniquely extended from the genuine CML format. In addition, C3DB provides functions for submitting jobs for conformational search and geometry optimization to pre-registered computing servers and retrieving and storing their results. Currently, about 12,000 molecular information is stored.