DenovoProfiling

DenovoProfiling: a webserver for de novo generated molecule library profiling.

Introduction

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 a 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 creates good opportunities for comprehensive profiling of the de novo library. In this paper, we present DenovoProfiling, a webserver dedicated to de novo library visualization and functional profiling. Currently, DenovoProfiling contains six modules: (1) identification & visualization, (2) chemical space, (3) ADMET prediction, (4) molecular alignment, (5) drugs mapping, and (6) target & pathway. DenovoProfiling could provide structural identification, chemical space exploration, drug mapping, and target & pathway information. The comprehensive annotated information could give users a clear picture of their de novo library and could guide the further selection of candidates for synthesis and biological confirmation.

Web site

http://denovoprofiling.xielab.net

Install and Run

1. Download and install golang following the official instructions(https://go.dev/doc/install).
2. Clone the DenovoProfiling repository.
   git clone https://github.com/nanomolar/DenovoProfiling.git
3. Build the source code.
   go build main.go
4. edit the configure file in conf/app.conf.
5. run server.
   nohup ./main &