Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape

Mengxu Zhu; Kongyan Li; Hong Yan

doi:10.1109/bibm55620.2022.9995089

Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape

^*Corresponding author for this work

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Covid-19 has become a world pandemic for years. With the appearance of mutations, immune escape has become a problem, reducing the effectiveness of vaccines and antibodies. To reveal the mechanism of immune escape, we analyze the geometrical properties of the receptor-binding domain in the SARS-CoV-2 spike protein, which plays a vital role in the immune reaction. Several important variants are taken as examples, and the wild type model is prepared as a reference. The computational method is applied to simulate the behaviors of the models, and alpha shape algorithm is employed to extract geometrical data of the protein surface. Average moving distance of the surface atoms is used to quantify their activity. Our results show that the mutations changed the properties of the protein. The variants have different distributions of active sites, which may change the specific antigenicity and influence the binding abilities of drugs and antibodies. This study explains the mechanism of immune escape of SARS-CoV-2, and provides a geometrical method to find potential new target sites for the design of drugs and vaccines. ©2022 IEEE

Original language	English
Title of host publication	2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Publisher	IEEE
Pages	3528-3534
ISBN (Electronic)	978-1-6654-6819-0
ISBN (Print)	978-1-6654-6820-6
DOIs	https://doi.org/10.1109/bibm55620.2022.9995089
Publication status	Published - Dec 2022
Event	IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2022) - WorldHotel Grand Jiaxing Hunan (Changsha, Hunan) & Caesars Palace (Las Vegas, USA) Duration: 7 Dec 2022 → 8 Dec 2022

Conference

Conference	IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2022)
Period	7/12/22 → 8/12/22

Funding

This work is supported by the Hong Kong Research Grants Council (Project 11204821).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Keywords

covid-19
receptor-binding domains
geometrical features
alpha shape
average moving distance

RGC Funding Information

RGC-funded

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10.1109/bibm55620.2022.9995089

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title = "Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape",

abstract = "Covid-19 has become a world pandemic for years. With the appearance of mutations, immune escape has become a problem, reducing the effectiveness of vaccines and antibodies. To reveal the mechanism of immune escape, we analyze the geometrical properties of the receptor-binding domain in the SARS-CoV-2 spike protein, which plays a vital role in the immune reaction. Several important variants are taken as examples, and the wild type model is prepared as a reference. The computational method is applied to simulate the behaviors of the models, and alpha shape algorithm is employed to extract geometrical data of the protein surface. Average moving distance of the surface atoms is used to quantify their activity. Our results show that the mutations changed the properties of the protein. The variants have different distributions of active sites, which may change the specific antigenicity and influence the binding abilities of drugs and antibodies. This study explains the mechanism of immune escape of SARS-CoV-2, and provides a geometrical method to find potential new target sites for the design of drugs and vaccines. {\textcopyright}2022 IEEE ",

keywords = "covid-19, receptor-binding domains, geometrical features, alpha shape, average moving distance",

author = "Mengxu Zhu and Kongyan Li and Hong Yan",

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doi = "10.1109/bibm55620.2022.9995089",

language = "English",

isbn = "978-1-6654-6820-6",

pages = "3528--3534",

booktitle = "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",

publisher = "IEEE",

address = "United States",

note = "IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2022) ; Conference date: 07-12-2022 Through 08-12-2022",

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Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape. / Zhu, Mengxu ; Li, Kongyan ; Yan, Hong.
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022. p. 3528-3534.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape

AU - Zhu, Mengxu

AU - Li, Kongyan

AU - Yan, Hong

PY - 2022/12

Y1 - 2022/12

N2 - Covid-19 has become a world pandemic for years. With the appearance of mutations, immune escape has become a problem, reducing the effectiveness of vaccines and antibodies. To reveal the mechanism of immune escape, we analyze the geometrical properties of the receptor-binding domain in the SARS-CoV-2 spike protein, which plays a vital role in the immune reaction. Several important variants are taken as examples, and the wild type model is prepared as a reference. The computational method is applied to simulate the behaviors of the models, and alpha shape algorithm is employed to extract geometrical data of the protein surface. Average moving distance of the surface atoms is used to quantify their activity. Our results show that the mutations changed the properties of the protein. The variants have different distributions of active sites, which may change the specific antigenicity and influence the binding abilities of drugs and antibodies. This study explains the mechanism of immune escape of SARS-CoV-2, and provides a geometrical method to find potential new target sites for the design of drugs and vaccines. ©2022 IEEE

AB - Covid-19 has become a world pandemic for years. With the appearance of mutations, immune escape has become a problem, reducing the effectiveness of vaccines and antibodies. To reveal the mechanism of immune escape, we analyze the geometrical properties of the receptor-binding domain in the SARS-CoV-2 spike protein, which plays a vital role in the immune reaction. Several important variants are taken as examples, and the wild type model is prepared as a reference. The computational method is applied to simulate the behaviors of the models, and alpha shape algorithm is employed to extract geometrical data of the protein surface. Average moving distance of the surface atoms is used to quantify their activity. Our results show that the mutations changed the properties of the protein. The variants have different distributions of active sites, which may change the specific antigenicity and influence the binding abilities of drugs and antibodies. This study explains the mechanism of immune escape of SARS-CoV-2, and provides a geometrical method to find potential new target sites for the design of drugs and vaccines. ©2022 IEEE

KW - covid-19

KW - receptor-binding domains

KW - geometrical features

KW - alpha shape

KW - average moving distance

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BT - 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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ER -

Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape

Abstract

Conference

Funding

UN SDGs

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

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GRF: Matching Large Feature Sets based on Hypergraph Models and Structurally Adaptive CUR Decompositions of Compatibility Tensors

Cite this

Computational Analysis of Receptor-Binding Domains of SARS-CoV-2 to Reveal the Mechanism of Immune Escape

Abstract

Conference

Funding

UN SDGs

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Projects

GRF: Matching Large Feature Sets based on Hypergraph Models and Structurally Adaptive CUR Decompositions of Compatibility Tensors

Cite this