Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation.

Xiong, Youjin; Wang, Yiqing; Wang, Yisheng; Li, Chenmei; Yusong, Peng; Wu, Junyu; Wang, Yiqing; Gu, Lingyun; Butch, Christopher J

Xiong, Youjin; Wang, Yiqing; Wang, Yisheng; Li, Chenmei; Yusong, Peng; Wu, Junyu; Wang, Yiqing; Gu, Lingyun; Butch, Christopher J.

Afiliação

Xiong Y; Department of Biomedical Engineering, Nanjing University, Nanjing, 210093, China.
Wang Y; Icekredit Incorporated, Shanghai, 200120, China.
Wang Y; Department of Biomedical Engineering, Nanjing University, Nanjing, 210093, China.
Li C; Department of Biomedical Engineering, Nanjing University, Nanjing, 210093, China.
Yusong P; Department of Biomedical Engineering, Nanjing University, Nanjing, 210093, China.
Wu J; Icekredit Incorporated, Shanghai, 200120, China.
Wang Y; Department of Biomedical Engineering, Nanjing University, Nanjing, 210093, China.
Gu L; Department of Information Systems Technology and Design, Singapore University of Technology and Design, Singapore, Singapore. gu_lingyun@icekredit.com.
Butch CJ; Department of Biomedical Engineering, Nanjing University, Nanjing, 210093, China. chrisbutch@nju.edu.cn.

J Comput Aided Mol Des ; 37(11): 507-517, 2023 11.

Article em En | MEDLINE | ID: mdl-37550462

Assuntos

Aprendizado Profundo; Descoberta de Drogas; Teorema de Bayes; Simulação por Computador; Aprendizado de Máquina; Desenho de Fármacos

Palavras-chave

Bayesian regression; Discoidin domain receptor 1; Generative molecular models; Machine learning in drug design; Molecular docking

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Descoberta de Drogas / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Revista: J Comput Aided Mol Des Assunto da revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China País de publicação: Holanda

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