Bioinformatics approach to identifying potential cancer-associated mutations in CCL2

Abstract

Chemokine C-C motif ligand 2 (CCL2), also known as monocyte chemoattractant protein 1 or small inducible cytokine A2, is a cytokine from the CC chemokine family. It plays a crucial role in recruiting monocytes, memory T-cells, and dendritic cells to inflammatory sites resulting from tissue injury or infection. C-C motif chemokine receptor 2 (CCR2) is a chemokine receptor that may influence lymphocyte function. The interaction between CCL2 and CCR2 is essential for inflammatory responses and cancer regulation, as it attracts monocytes and macrophages to tumor sites, facilitating tumor growth and metastasis. Given the importance of CCL2 in regulating cell trafficking and cancer progression, we employed a bioinformatics approach to examine the effects of oncogenic missense mutations in CCL2 on CCR2 activation. We used precise computational methods to identify the molecular characteristics responsible for the altered activity and interactions, thereby enhancing our understanding of the molecular mechanisms underlying disease progression. We generated a three-dimensional model of the CCL2 protein with the identified mutations using the I-TASSER algorithm. The effects of these mutations on the protein’s stability and functional properties were evaluated using various prediction tools, and molecular dynamics simulations were conducted using WebGro software. Our analysis of 83 CCL2 missense mutations identified 10 disease-causing mutations, including C59G, which was directly linked to cancer. The C59G mutation increases the binding interaction between CCL2 and CCR2. The C59G position was determined to be highly conserved, and substitutions of cysteine (C) 59 with glycine (G) altered CCL2 activity. Our results suggest that this mutation alters the CCL2–CCR2 binding activity, lowering the risk of developing cancer and defending against pathogen invasion during the neutrophil-mediated innate immune response.