Computational investigation of natural compounds as potential main protease (M <sup>pro</sup>) inhibitors for SARS-CoV-2 virus

Patel, Chirag N.; Jani, Siddhi P.; Prasanth Kumar, Sivakumar; Modi, Krunal M.; Kumar, Yogesh

doi:10.1016/j.compbiomed.2022.106318

ScienceOpen: research and publishing network

For Publishers

For Researchers

Blog
About

Search
Advanced search

views

recommends

Record: found
Abstract: found
Article: not found

Computational investigation of natural compounds as potential main protease (M ^pro) inhibitors for SARS-CoV-2 virus

research-article

Author(s): Chirag N. Patel ^a ^, ^c ^, ¹ ^, ^∗ , Siddhi P. Jani ^b ^, ¹ , Sivakumar Prasanth Kumar ^c , Krunal M. Modi ^d ^, ^e ^, ^∗∗ , Yogesh Kumar ^f

Publication date (Electronic): 18 November 2022

Journal: Computers in Biology and Medicine

Publisher: Elsevier Ltd.

Keywords: Main proteases (Mpro), DFT calculation, Dynamics simulation, Binding free energy, Omicron

Read this article at

ScienceOpenPublisher PMC

Bookmark

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is significantly impacting human lives, overburdening the healthcare system and weakening global economies. Plant-derived natural compounds are being largely tested for their efficacy against COVID-19 targets to combat SARS-CoV-2 infection. The SARS-CoV-2 Main protease (M ^pro) is considered an appealing target because of its role in replication in host cells. We curated a set of 7809 natural compounds by combining the collections of five databases viz Dr Duke's Phytochemical and Ethnobotanical database, IMPPAT, PhytoHub, AromaDb and Zinc. We applied a rigorous computational approach to identify lead molecules from our curated compound set using docking, dynamic simulations, the free energy of binding and DFT calculations. Theaflavin and ginkgetin have emerged as better molecules with a similar inhibition profile in both SARS-CoV-2 and Omicron variants.

Graphical abstract

Related collections

Most cited references 74

Record: found
Abstract: found
Article: not found

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

0 comments Cited 22227 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

Comparison of simple potential functions for simulating liquid water

William L Jorgensen, Jayaraman Chandrasekhar, Jeffry Madura … (1983)

0 comments Cited 3381 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

A smooth particle mesh Ewald method

Ulrich Essmann, Lalith Perera, Max Berkowitz … (1995)

0 comments Cited 2065 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): Comput Biol Med

Journal ID (iso-abbrev): Comput Biol Med

Title: Computers in Biology and Medicine

Publisher: Elsevier Ltd.

ISSN (Print): 0010-4825

ISSN (Electronic): 1879-0534

Publication date PMC-release: 18 November 2022

Publication date (Print): December 2022

Publication date (Electronic): 18 November 2022

Volume: 151

Page: 106318

Affiliations

[a ]Computer-Aided Drug Design Group, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institute of Health, Frederick, MD, 21702, USA

[b ]Institute of Science, Nirma University, Ahmedabad, 382481, Gujarat, India

[c ]Department of Botany, Bioinformatics, and Climate Change Impacts Management, School of Sciences, Gujarat University, Ahmedabad, 380009, Gujarat, India

[d ]Department of Molecular Electrochemistry and Catalysis, J. Heyrovsky Institute of Physical Chemistry, Academy of Sciences of the Czech Republic, Dolejskova 2155/3, 182 23 Prague 8, Czech Republic

[e ]Department of Humanities and Science, School of Engineering, Indrashil University, Mehsana, 382740, Gujarat, India

[f ]Department of General Visceral and Thoracic Surgery, University Medical Center Hamburg- Eppendorf, Martinistrasse 52, Hamburg, 20246, Germany

Author notes

[∗ ]Corresponding author. Computer-Aided Drug Design Group, Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institute of Health, Frederick, MD 21702, USA.

[∗∗ ]Corresponding author. Department of Humanities and Science, School of Engineering, Indrashil University, Mehsana, 382740, Gujarat, India.

[1]

Chirag N. Patel and Siddhi P. Jani have contributed equally and are equal first authors.

Article

Publisher Item ID: S0010-4825(22)01026-5 Publisher ID: 106318

DOI: 10.1016/j.compbiomed.2022.106318

PMC ID: 9673090

PubMed ID: 36423529

SO-VID: b7bc0154-b487-4b12-84c0-31b631939dff

License:

Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

History

Date received : 13 February 2022

Date revision received : 5 November 2022

Date accepted : 13 November 2022

Comments

Comment on this article

scite_

Cited by 7

See all cited by