Anzala, M. Pierre (2024) A method for detecting amino acid correlation with application to SARS-CoV-2 PRE - Research Project, ENSTA.

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Abstract

Direct Coupling Analysis is a central method to the biostatistical study of RNA viruses. In the case of SARS-CoV-2, it has been used to detect correlations between sites and predict site mutability. In this project, we propose an added layer of information for prediction and SARS-CoV-2 study. Three-point correlations can be added to existing DCA models to further identify mutable sites and help determine crucial epistatic links. We thus identified neighbouring sites in the envelope protein of SARS-CoV-2 with high epistatic energy as well as the influence of the chemical properties of amino acids on mutations within the virus. However, as DCA neglects the evolutionary history between sequences, elements from phylogenetic study can be included to add evolution as an element of examination. A rate matrix of amino acid pair substitution has been computed for critical domains of SARS-CoV-2 and helped uncover the appearance of many substitutions towards aliphatic hydrophobic amino acids which impact the protein folding process and have been shown to accelerate binding to ACE2 (Jiacheng Li, Xiaoliang Ma, Shuai Guo, Chengyu Hou, Liping Shi, Hongchi Zhang, Bing Zheng, Chenchen Liao, Lin Yang, Lin Ye, and Xiaodong He. A hydrophobic-interaction-based mechanism triggers docking between the sars-cov-2 spike and angiotensin-converting enzyme 2. Global Challenges, 4(12), 2020. Cited by: 21; All Open Access, Gold Open Access.)

Item Type:Thesis (PRE - Research Project)
Uncontrolled Keywords:Direct Coupling Analysis, Phylogeny, RNA, Epistasis, SARS-CoV-2
Subjects:Mathematics and Applications
Life Sciences and Engineering
ID Code:10069
Deposited By:Pierre ANZALA
Deposited On:09 sept. 2024 13:39
Dernière modification:09 sept. 2024 13:39

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