A systematic in-silico functional and structural analysis reveals deleterious missense nsSNPs in the human <i>CSF1R</i> gene.

Colony Stimulating Factor-1 Receptor (CSF1R) is a tyrosine kinase transmembrane receptor that plays a vital role in innate immunity and neurogenesis and controls the differentiation and maintenance of most tissue-resident macrophages. <i>CSF1R</i> mutations have been linked with many neurodegenerative diseases. In this work, we aim to identify the functional and structural impact of deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) mutations on CSF1R, which could help understand the consequences of these mutational changes. A consensus-based prediction approach was used to screen the missense SNPs using six in-silico tools: SIFT, PROVEAN, PMut, MutPred, MISSENSE 3D, and FATHMM. SNPs found to be deleterious by more than five out of six tools were subjected to further analysis, such as protein secondary structure and domain architecture analysis by PSIPRED and NCBI-CDD, respectively. Mutant models of highly deleterious SNPs were modeled using PyMol, followed by energy minimization and Root Mean Square Deviation (RMSD) analysis and molecular dynamic (MD) simulation by YASARA, TM-ALIGN, and WebGro, respectively. Out of 780 missense SNPs screened, we found the four most deleterious SNPs (L301S, A770P, I775N, and F849S) that decreased the protein stability because of their presence in the conserved regions of wild-type CSF1R. Structural and functional studies revealed that these mutations could disrupt the protein's core and surface interactions, leading to destabilization and functional impairment. Moreover, the mutated proteins exhibited enhanced conformational flexibility and instability, as confirmed by MD simulation analysis.

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Journal
PubMed
Published
2025-01-01
DOI
https://doi.org/10.22099/mbrc.2025.53206.2156
Primary Topic
Genomics and Rare Diseases
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article
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0.00

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article

A systematic in-silico functional and structural analysis reveals deleterious missense nsSNPs in the human CSF1R gene.

Chander Jyoti Thakur, A. K. Jaitly, Harkamal Walia, Sandeep Saini et al.
PubMed
Genomics and Rare Diseases
article

A systematic in-silico functional and structural analysis reveals deleterious missense nsSNPs in the human CSF1R gene.

Chander Jyoti Thakur, A. K. Jaitly, Harkamal Walia, Sandeep Saini, Ojasvi Dutta, Deepanshi Rajput, Purvi Malhotra, Mujtaba Husaini
article en

Abstract

Colony Stimulating Factor-1 Receptor (CSF1R) is a tyrosine kinase transmembrane receptor that plays a vital role in innate immunity and neurogenesis and controls the differentiation and maintenance of most tissue-resident macrophages. <i>CSF1R</i> mutations have been linked with many neurodegenerative diseases. In this work, we aim to identify the functional and structural impact of deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) mutations on CSF1R, which could help understand the consequences of these mutational changes. A consensus-based prediction approach was used to screen the missense SNPs using six in-silico tools: SIFT, PROVEAN, PMut, MutPred, MISSENSE 3D, and FATHMM. SNPs found to be deleterious by more than five out of six tools were subjected to further analysis, such as protein secondary structure and domain architecture analysis by PSIPRED and NCBI-CDD, respectively. Mutant models of highly deleterious SNPs were modeled using PyMol, followed by energy minimization and Root Mean Square Deviation (RMSD) analysis and molecular dynamic (MD) simulation by YASARA, TM-ALIGN, and WebGro, respectively. Out of 780 missense SNPs screened, we found the four most deleterious SNPs (L301S, A770P, I775N, and F849S) that decreased the protein stability because of their presence in the conserved regions of wild-type CSF1R. Structural and functional studies revealed that these mutations could disrupt the protein's core and surface interactions, leading to destabilization and functional impairment. Moreover, the mutated proteins exhibited enhanced conformational flexibility and instability, as confirmed by MD simulation analysis.

PubMedVol. 14(4)
Panjab University (IN)
Department of Biotechnology, Ministry of Science and Technology, India, Department of Science and Technology, Ministry of Science and Technology, India
Openalex Percentile: Top 73%
Genomics and Rare Diseases
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