<i>De Novo</i> Generation of Chemical Structures of Inhibitor and Activator Candidates for Therapeutic Target Proteins by a Transformer-Based Variational Autoencoder and Bayesian Optimization-Reference-Cited by-同舟云学术

De Novo Generation of Chemical Structures of Inhibitor and Activator Candidates for Therapeutic Target Proteins by a Transformer-Based Variational Autoencoder and Bayesian Optimization

Published:2023-09-28 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Matsukiyo Yuki¹^ORCID,Yamanaka Chikashige¹^ORCID,Yamanishi Yoshihiro¹²

Affiliation:

1. Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan

2. Graduate School of Informatics, Nagoya University, Chikusa, Nagoya, Aichi 464-8601, Japan

Funder

Japan Agency for Medical Research and Development

Japan Society for the Promotion of Science

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c00824

Reference43 articles.

1. Trends in Risks Associated With New Drug Development: Success Rates for Investigational Drugs

2. Innovation in the pharmaceutical industry: New estimates of R&D costs

3. The art and practice of structure-based drug design: A molecular modeling perspective

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