Evolutionary design of molecules based on deep learning and a genetic algorithm.

ABSTRACT: Evolutionary design has gained significant attention as a useful tool to accelerate the design process by automatically modifying molecular structures to obtain molecules with the target properties. However, its methodology presents a practical challenge-devising a way in which to rapidly evolve molecules while maintaining their chemical validity. In this study, we address this limitation by developing an evolutionary design method. The method employs deep learning models to extract the inherent knowledge from a database of materials and is used to effectively guide the evolutionary design. In the proposed method, the Morgan fingerprint vectors of seed molecules are evolved using the techniques of mutation and crossover within the genetic algorithm. Then, a recurrent neural network is used

SUBMITTER: Kwon Y 

PROVIDER: S-EPMC8397714 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature