Chemistry42: An AI-Driven Platform for Molecular Design and Optimization-Reference-Cited by-同舟云学术

Chemistry42: An AI-Driven Platform for Molecular Design and Optimization

Published:2023-02-02 Issue:3 Volume:63 Page:695-701
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Ivanenkov Yan A.¹^ORCID,Polykovskiy Daniil²^ORCID,Bezrukov Dmitry¹,Zagribelnyy Bogdan³,Aladinskiy Vladimir³,Kamya Petrina²,Aliper Alex³,Ren Feng⁴^ORCID,Zhavoronkov Alex¹^ORCID

Affiliation:

1. Insilico Medicine Kong Kong Ltd., Unit 310, 3/F, Building 8W, Phase 2, Hong Kong Science Park, Pak Shek Kok, Hong Kong

2. Insilico Medicine Canada Inc., 3710-1250 René-Lévesque Blvd W, Montreal, Quebec, H3B 4W8 Canada

3. Insilico Medicine AI Limited, Level 6, Unit 08, Block A, IRENA HQ Building, Masdar City, PO Box 145748, Abu Dhabi, UAE

4. Insilico Medicine Shanghai Ltd., Suite 901, Tower C, Changtai Plaza, 2889 Jinke Road, Pudong New District, Shanghai 201203, China

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.2c01191

Reference33 articles.

1. The rise of deep learning in drug discovery

2. The Advent of Generative Chemistry

3. Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery

4. The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology

5. Deep learning enables rapid identification of potent DDR1 kinase inhibitors

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