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Computational investigation of the increased virulence and pathogenesis of SARS-CoV-2 lineage B.1.1.7
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST). Indraprastha Inst Informat Technol IIIT D, Dept Computat Biol, New Delhi 110020, India..ORCID iD: 0000-0003-0185-5724
Alagappa Univ, Dept Bioinformat, Karaikkudi, Tamil Nadu, India..
Dr Umayal Ramanathan Coll Women, Dept Biotechnol, Karaikkudi, Tamil Nadu, India..
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemistry, Glycoscience.
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2022 (English)In: Physical Chemistry, Chemical Physics - PCCP, ISSN 1463-9076, E-ISSN 1463-9084, Vol. 24, no 34, p. 20371-20380Article in journal (Refereed) Published
Abstract [en]

New variants of SARS-CoV-2 are being reported worldwide. The World Health Organization has reported Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2) and Omicron (B.1.1.529) as the variants of concern. There are speculations that the variants might evade the host immune responses induced by currently available vaccines and develop resistance to drugs under consideration. The first step of viral infection in COVID-19 occurs through the interaction of the spike protein's receptor-binding domain (RBD) with the peptidase domain of the human ACE-2 (hACE-2) receptor. This study aims to get a molecular-level understanding of the mechanism behind the increased infection rate in the alpha variant. We have computationally studied the spike protein interaction in both the wild-type and B.1.1.7 variant with the hACE-2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The binding free energy difference shows that the mutant variant of the spike protein has increased binding affinity for the hACE-2 receptor (i.e. Delta G(N501Y,A570D) is in the range -7.2 to -7.6 kcal mol(-1)) and the results were validated using Density functional theory. We demonstrate that with the use of state-of-the-art computational approaches, we can, in advance, predict the virulent nature of variants of SARS-CoV-2 and alert the world healthcare system.

Place, publisher, year, edition, pages
Royal Society of Chemistry (RSC) , 2022. Vol. 24, no 34, p. 20371-20380
National Category
Infectious Medicine
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URN: urn:nbn:se:kth:diva-321484DOI: 10.1039/d2cp00469kISI: 000841762800001PubMedID: 35983778Scopus ID: 2-s2.0-85136613382OAI: oai:DiVA.org:kth-321484DiVA, id: diva2:1711263
Note

QC 20230614

Correction in: Physical Chemistry Chemical Physics, Volume 24, Issue 42, Page 26316-26316, DOI: 10.1039/d2cp90186b, WOS:000871378000001, Scopus 2-s2.0-85141888970

Available from: 2022-11-16 Created: 2022-11-16 Last updated: 2023-06-14Bibliographically approved

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Natarajan Arul, MuruganAli, Muhammad AkhtarSrivastava, Vaibhav

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