DenovoProfiling: a webserver for de novo generated molecule library profiling

Abstract

With the advances of deep learning techniques, various architectures for molecular generation have been proposed for de novo drug design. Successful cases from academia and industrial demonstrated that the deep learning based de novo molecular design could efficiently accelerate the drug discovery process. The flourish of the de novo molecular generation methods and applications created great demand for the visualization and functional profiling for the de novo generated molecules. The rising of publicly available chemogenomic databases lays good foundations and create good opportunities for comprehensive profiling of the de novo library. In this paper, we present DenovoProfiling, a web server dedicated for de novo library visualization and functional profiling. Currently, DenovoProfiling contains six modules: (1) identification & visualization, (2) chemical space, (3) scaffold analysis, (4) molecular alignment, (5) target & pathways, and (6) drugs mapping. DenovoProfiling could provide structural identification, chemical space exploration, drugs mapping, and targets & pathways. The comprehensive annotated information could give user a clear picture of their de novo library and could provide guidance in the further selection of candidates for synthesis and biological confirmation. DenovoProfiling is freely available at http://denovoprofiling.xielab.net.