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Virtual Screening of Traditional Chinese Medicine for Discovery of Potential Anti-SARS-CoV-2 Lead Molecules

Authors:

Xin Zhang,

Quan ZouAuthors Info & Claims

ICBBT '23: Proceedings of the 2023 15th International Conference on Bioinformatics and Biomedical Technology

Pages 238 - 242

https://doi.org/10.1145/3608164.3608199

Published: 07 November 2023 Publication History

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ICBBT '23: Proceedings of the 2023 15th International Conference on Bioinformatics and Biomedical Technology

Virtual Screening of Traditional Chinese Medicine for Discovery of Potential Anti-SARS-CoV-2 Lead Molecules

Pages 238 - 242

Abstract
Supplementary Material

Abstract

The SARS-CoV-2 pandemic has had a global impact, resulting in millions of infections and deaths. Traditional Chinese medicine (TCM), with its extensive clinical experience, offers valuable insights for controlling and treating COVID-19 patients. In this study, traditional Chinese medicine prescriptions used for treating COVID-19 patients were compiled, 55 Chinese herbs were analyzed, and a library of 488 small-molecule compounds was generated. The authors identified several molecules that have the potential to bind to target proteins of SARS-CoV-2 and host via virtual screening. Based on docking score, five small molecules were identified as having multi-target antagonistic effects against SARS-CoV-2, providing a theoretical foundation for developing candidate lead molecules.

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Virtual Screening of Traditional Chinese Medicine for Discovery of Potential Anti-SARS-CoV-2 Lead Molecules
1. Applied computing
  1. Life and medical sciences
    1. Bioinformatics

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ICBBT '23: Proceedings of the 2023 15th International Conference on Bioinformatics and Biomedical Technology

May 2023

313 pages

ISBN:9798400700385

DOI:10.1145/3608164

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 November 2023

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National Natural Science Foundation of China
The Municipal Government of Quzhou
Municipal Government of Quzhou

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ICBBT 2023

ICBBT 2023: 2023 15th International Conference on Bioinformatics and Biomedical Technology

May 26 - 28, 2023

Xi'an, China

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Abstract

Supplementary Material

Index Terms

Recommendations

Potential of turmeric-derived compounds against RNA‐dependent RNA polymerase of SARS‐CoV‐2: An in-silico approach

A multi-targeted approach to identify potential flavonoids against three targets in the SARS-CoV-2 life cycle

Design of Multi-Epitope Vaccine against SARS-CoV-2

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