Artificial Intelligence-Guided De Novo Molecular Design Targeting COVID-19-Reference-Cited by-同舟云学术

Artificial Intelligence-Guided De Novo Molecular Design Targeting COVID-19

Published:2021-05-04 Issue:19 Volume:6 Page:12557-12566
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Srinivasan Srilok¹^ORCID,Batra Rohit¹^ORCID,Chan Henry¹²^ORCID,Kamath Ganesh³,Cherukara Mathew J.¹⁴^ORCID,Sankaranarayanan Subramanian K. R. S.¹²^ORCID

Affiliation:

1. Center for Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, United States

2. Department of Mechanical and Industrial Engineering, University of Illinois, Chicago, Illinois 60607, United States

3. Dalzielfiver LLC, 3500 Carlfield Street, El Sobrante, California 94803, United States

4. Advanced Photon Source, Argonne National Laboratory, Lemont, Illinois 60439, United States

Funder

Basic Energy Sciences

University of Illinois at Chicago

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.1c00477

Reference36 articles.

1. Smith, M.; Smith, J. C. Repurposing Therapeutics for COVID-19: Supercomputer-Based Docking to the SARS-CoV-2 Viral Spike Protein and Viral Spike Protein–Human ACE2 Interface, 2020.

2. The Chemical Space Project

3. How to Discover Antiviral Drugs Quickly

4. Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies

5. Generative Recurrent Networks for De Novo Drug Design

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