De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

ABSTRACT: Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine-tuned on recognizing retinoid X and peroxisome proliferator-activated receptor agonists. We synthesized five top-ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low-micromolar receptor modulatory activity in cell-based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge w

SUBMITTER: Merk D 

PROVIDER: S-EPMC5838524 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature