Gargoyles: An Open Source Graph-Based Molecular Optimization Method Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Gargoyles: An Open Source Graph-Based Molecular Optimization Method Based on Deep Reinforcement Learning

Published:2023-09-28 Issue:40 Volume:8 Page:37431-37441
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Erikawa Daiki¹,Yasuo Nobuaki²^ORCID,Suzuki Takamasa¹^ORCID,Nakamura Shogo³^ORCID,Sekijima Masakazu¹^ORCID

Affiliation:

1. Department of Computer Science, Tokyo Institute of Technology, 4259-J3-23, Nagatsuta-cho, Midori-ku, Yokohama 226-8501, Japan

2. Academy for Convergence of Materials and Informatics (TAC-MI), Tokyo Institute of Technology, S6-23, Ookayama, Meguro-ku, Tokyo 152-8550, Japan

3. Department of Life Science and Technology, Tokyo Institute of Technology, 4259-J3-23, Nagatsuta-cho, Midori-ku, Yokohama 226-8501, Japan

Funder

Japan Agency for Medical Research and Development

Japan Society for the Promotion of Science

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.3c05430

Reference50 articles.

1. Principles of early drug discovery

2. Screening for Inhibitors of Main Protease in SARS-CoV-2: In Silico and In Vitro Approach Avoiding Peptidyl Secondary Amides

3. In silico, in vitro, X-ray crystallography, and integrated strategies for discovering spermidine synthase inhibitors for Chagas disease

4. Discovery of a Hidden Trypanosoma cruzi Spermidine Synthase Binding Site and Inhibitors through In Silico, In Vitro, and X-ray Crystallography

5. Dephospho-Coenzyme A Kinase Is an Exploitable Drug Target against Plasmodium falciparum: Identification of Selective Inhibitors by High-Throughput Screening of a Large Chemical Compound Library

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