Abstract
Chemical space exploration is a major task of the hit-finding process during the pursuit of novel chemical
entities. Compared with other screening technologies, computational de novo design has become a popular
approach to overcome the limitation of current chemical libraries. Here, we reported a de novo design platform
named systemic evolutionary chemical space explorer (SECSE). The platform was conceptually inspired by
fragment-based drug design, that miniaturized a “lego-building” process within the pocket of a certain target.
The key of virtual hits generation was then turned into a computational search problem. To enhance search and
optimization, human intelligence and deep learning were integrated. Application of SECSE against PHGDH,
proved its potential in finding novel and diverse small molecules that are attractive starting points for further
validation. This platform is open-sourced and the code is available at http://github.com/KeenThera/SECSE.