InfoSys 2025 Congress
March 09, 2025 to March 13, 2025 - Lisbon, Portugal

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InfoWare 2025 Congress
March 09, 2025 to March 13, 2025 - Lisbon, Portugal

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DataSys 2025 Congress
April 06, 2025 to April 10, 2025 - Valencia, Spain

  • AICT 2025, The Twenty-Second Advanced International Conference on Telecommunications
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ComputationWorld 2025 Congress
April 06, 2025 to April 10, 2025 - Valencia, Spain

  • SERVICE COMPUTATION 2025, The Seventeenth International Conference on Advanced Service Computing
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NexComm 2025 Congress
May 18, 2025 to May 22, 2025 - Nice, France

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DigitalWorld 2025 Congress
May 18, 2025 to May 22, 2025 - Nice, France

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IARIA Congress 2025, The 2025 IARIA Annual Congress on Frontiers in Science, Technology, Services, and Applications
July 06, 2025 to July 10, 2025 - Athens, Greece

DigiTech 2025 Congress
July 06, 2025 to July 10, 2025 - Athens, Greece

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NexTech 2025 Congress
September 28, 2025 to October 02, 2025 - Lisbon, Portugal

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SoftNet 2025 Congress
September 28, 2025 to October 02, 2025 - Lisbon, Portugal

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SocSys 2025 Congress
October 26, 2025 to October 30, 2025 - Barcelona, Spain

NetWare 2025 Congress
October 26, 2025 to October 30, 2025 - Barcelona, Spain

  • SENSORCOMM 2025, The Nineteenth International Conference on Sensor Technologies and Applications
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  • AFIN 2025, The Seventeenth International Conference on Advances in Future Internet
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  • FASSI 2025, The Eleventh International Conference on Fundamentals and Advances in Software Systems Integration
  • GREEN 2025, The Tenth International Conference on Green Communications, Computing and Technologies
  • HEALTHINFO 2025, The Tenth International Conference on Informatics and Assistive Technologies for Health-Care, Medical Support and Wellbeing

TechWorld 2025 Congress
October 26, 2025 to October 30, 2025 - Barcelona, Spain

 


ThinkMind // International Journal On Advances in Life Sciences, volume 15, numbers 3 and 4, 2023 // View article lifsci_v15_n34_2023_4


Comprehensive Machine Learning Analysis of Key Residues in Variants and Polymorphisms for Ace2-Spike Interaction in SARS-CoV-2

Authors:
Ana Luísa Rodrigues de Ávila
Ana Carolina Damasceno Sanches
Arthur Scorsolini Fares
Levy Bueno Alves
Silvana Giuliatti

Keywords: COVID-19; Bioinformatics; Virus-host interaction; Polymorphism; Variants

Abstract:
The invasion of SARS-CoV-2 into host cells depends on the interaction of the Spike protein with the human angiotensin-converting enzyme 2 (Ace2). Specific Ace2 polymorphisms have been associated with increased susceptibility to SARS-CoV-2, potentially affecting the risk of infection and the severity of COVID-19. Furthermore, SARS-CoV-2 has a high probability of mutating and adapting to the environment. However, the effect of these genetic variations on the stability and affinity of the Spike-Ace2 interaction is not well understood. For a deeper understanding of this interaction, molecular dynamics simulations are used. Despite generating extensive data, these simulations do not easily facilitate the identification of essential residues that influence protein interaction. To address this challenge, we combined molecular dynamics simulations and supervised machine learning techniques to identify the residues that are subtly important in the interaction and dynamics of the complexes. The molecular dynamics simulations revealed subtle trajectory variations, emphasizing key residues and loop regions residues. While complexes show stable behavior with slight differences, machine learning techniques offer deep insights into how genetic variations in both the virus and host receptor influence the interaction region of these proteins.

Pages: 99 to 108

Copyright: Copyright (c) to authors, 2023. Used with permission.

Publication date: December 30, 2023

Published in: journal

ISSN: 1942-2660

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