Industry and academia have higher and higher demands on the quality of generated molecules. One demand is the novelty of the structure and scaffold, which makes sure the molecule bypasses the protection of patents and explores new chemical space. Another demand is that, for different targets in different disease pathways, molecules need to meet multiplex and variable features to pass clinical trials. Though, computer-aided drug design (CADD) methods have defects in meeting these demands. Virtual-screening-based methods have difficulties in finding novel scaffolds, and generation models are always fixed on particular missions which makes them not suitable when changing targets or other features that are demanded.<br/>To that end, we developed CUE (Chemical Universe Explorer), a chemist-friendly platform for de novo generation and molecule optimization. The platform allows users to customize demands and generate novel structures or optimize structures in a very short time, which can accelerate the process of the lead compound or preclinical candidate discovery. CUE uses a plug-in framework to consider major molecular features when doing molecular generation or optimization, such as protein-ligand activity, ADMET features, structural characteristics, synthetic accessibility, etc. Users are free to choose and combine various of these demands, and they can also upload their own models to the platform, making it to consider demands which are not in the presets.

CUE: A user-friendly platform with plug-in methods for <i>de novo</i> drug design and chemical space exploration

Where thousands of chemistry professionals meet to share ideas and advance scientific and technical knowledge. Spring 2023 abstracts, posters, and presentations will launch at the end of March.

ACS Spring 2023

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.

CUE: A user-friendly platform with plug-in methods for de novo drug design and chemical space exploration