Recurrent neural network (RNN) model accelerates the development of antibacterial metronidazole derivatives.

ABSTRACT: Metronidazole is a specific drug against trichomonas and anaerobic bacteria, and is widely used in the clinic. However, extensive clinical application is often accompanied by extensive side effects, so it is still of great significance to develop metronidazole derivatives with a new skeleton. Compared with other traditional receptor-based drug design methods, the computational model based on a neural network has higher accuracy and reliability. In this work, a Recurrent Neural Network (RNN) model is applied to the discovery of metronidazole drugs with a new skeleton. Firstly, the generation model based on a Gated Recurrent Unit (GRU) is trained to generate an effective Simplified Molecular-Input Line-Entry System (SMILES) string library with high precision. Then, transfer learning is intro

SUBMITTER: Chen N 

PROVIDER: S-EPMC9377161 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature