Predicting Evolutionary Importance of Amino Acids through Mutation of Codons Using K-means Clustering

Nasrin Irshad Hussain; Kuntala Boruah; Adil Akhtar

doi:10.35882/jeeemi.v7i1.538

Nasrin Irshad Hussain Department of Computer Application, Sibsagar University, Sivasagar, India
Kuntala Boruah Department of Computer Application, Sibsagar University, Sivasagar, India https://orcid.org/0000-0002-8936-7145
Adil Akhtar Department of Mathematics, Golaghat Engineering College, Assam, India https://orcid.org/0000-0001-6940-8176

DOI: https://doi.org/10.35882/jeeemi.v7i1.538

Keywords: Amino acid, Codons, Machine learning, K-means clustering

Abstract

Mutation is a random biological event that may cause permanent (long term) change in living organism induced by several structural or composition alteration in the proteins. During mutation genetic materials such as nucleotide bases in the codons is changed which potentially contributed to the alteration in the codons and consequently the amino acid that new codon encodes. In this study mutation at different nucleotide base positions within the codons is analyzed to understand the evolutionary importance of amino acids. By creating hypothetical mutations at the first, second and third positions of all 61 codons (excluding stop codons) and using K-means clustering, we categorized the resulting amino acids. Our analysis reveals that mutations at the second base position generate the highest number of distinct amino acids, indicating greater evolutionary significance compared to first and third position mutations. We applied the proposed framework on COVID-2 SARS-CoV-2 (Homo sapiens) amino acid sequence and are able to deduce several significant findings about the mutation patterns. The clustering analysis revealed that amino acids such as Glycine (G), Alanine (A), Proline (P), Valine (V) and one polar amino acid are recurrent in the combined centroids of the clusters. These amino acids, predominantly hydrophobic, play a crucial role in stabilizing protein structures. This framework not only gives the insight understanding of mutation patterns and their biological significance but also underscores the importance of specific amino acids in the evolutionary process.

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