Quantitative Structure–Activity Relationship Machine Learning Models and their Applications for Identifying Viral 3CLpro- and RdRp-Targeting Compounds as Potential Therapeutics for COVID-19 and Related Viral Infections-Reference-Cited by-同舟云学术

Quantitative Structure–Activity Relationship Machine Learning Models and their Applications for Identifying Viral 3CLpro- and RdRp-Targeting Compounds as Potential Therapeutics for COVID-19 and Related Viral Infections

Published:2020-10-14 Issue:42 Volume:5 Page:27344-27358
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Ivanov Julian¹^ORCID,Polshakov Dmitrii¹,Kato-Weinstein Junko¹,Zhou Qiongqiong¹^ORCID,Li Yingzhu¹,Granet Roger¹,Garner Linda¹,Deng Yi¹,Liu Cynthia¹^ORCID,Albaiu Dana¹,Wilson Jeffrey¹,Aultman Christopher¹

Affiliation:

1. CAS, A Division of the American Chemical Society, Columbus, Ohio 43210-3012, United States

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acsomega.0c03682

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3. X-ray Structure of Main Protease of the Novel Coronavirus SARS-CoV-2 Enables Design of α-Ketoamide Inhibitors