Design and Synthesis of DDR1 Inhibitors with a Desired Pharmacophore Using Deep Generative Models-Reference-Cited by-同舟云学术

Design and Synthesis of DDR1 Inhibitors with a Desired Pharmacophore Using Deep Generative Models

Published:2021-01-15 Issue:6 Volume:16 Page:955-958
ISSN:1860-7179
Container-title:ChemMedChem
language:en
Short-container-title:ChemMedChem

Author:

Yoshimori Atsushi¹^ORCID,Asawa Yasunobu¹,Kawasaki Enzo²,Tasaka Tomohiko³,Matsuda Seiji⁴,Sekikawa Toru⁴,Tanabe Satoshi⁴,Neya Masahiro⁴,Natsugari Hideaki³,Kanai Chisato²

Affiliation:

1. Institute for Theoretical Medicine, Inc. 26-1, Muraoka-Higashi 2-chome Fujisawa Kanagawa 251-0012 Japan

2. INTAGE Healthcare, Inc. 79, Kankoboko-cho, Shimogyo-ku Kyoto 600-8009 Japan

3. Affinity Science Corporation Aios Gotanda-ekimae, 1-11-1 Nishi-Gotanda Shinagawa Tokyo 141-0031 Japan

4. KNC Laboratories Co., Ltd. 7-1-19, Minatojimaminamimachi, Chuo-ku Kobe Hyogo 650-0047 Japan

Publisher

Wiley

Subject

Organic Chemistry,General Pharmacology, Toxicology and Pharmaceutics,Molecular Medicine,Drug Discovery,Biochemistry,Pharmacology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cmdc.202000786

Reference25 articles.

1. H. Huang P. S. Yu C. Wang arXiv:1803.04469v22018.

2. Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

3. DGPose: Deep Generative Models for Human Body Analysis

4. Deep learning for molecular design—a review of the state of the art

5. De Novo Design of Bioactive Small Molecules by Artificial Intelligence

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