In-silico structural and functional analysis of nonsynonymous single nucleotide polymorphisms in human FOLH1 gene.

Area of Science:

• Genetics
• Biochemistry
• Computational Biology

Background:

• Non-synonymous single nucleotide polymorphisms (nsSNPs) can alter protein function and influence disease susceptibility.
• The Folate Hydrolase 1 (FOLH1) gene encodes Prostate-Specific Membrane Antigen (PSMA), a protein implicated in prostate cancer.

Purpose of the Study:

• To perform an in-silico analysis of nsSNPs in the FOLH1 gene to understand their structural and functional consequences on the PSMA protein.
• To identify pathogenic nsSNPs within FOLH1 and assess their potential impact on prostate cancer.

Main Methods:

• Retrieved 504 SNPs from databases and filtered to identify 15 potentially pathogenic nsSNPs using five in-silico tools.
• Utilized MutPred2 for predicting structural/functional changes and I-Mutant 2.0 for protein stability analysis.
• Employed ConSurf for conservation analysis and analyzed post-translational modifications (PTMs).

Main Results:

• Identified 15 pathogenic nsSNPs, with R255H, R255C, and G168E consistently predicted as pathogenic.
• Observed significant alterations in PSMA protein structure, including changes in helical content, glycosylation, and transmembrane properties.
• Found decreased protein stability for most nsSNPs, except G168E, and identified loss of glycosylation sites in R255H and R255C variants.

Conclusions:

• In-silico analysis is crucial for understanding the functional impact of FOLH1 nsSNPs on PSMA.
• Pathogenic nsSNPs, particularly R255H and R255C, may affect PSMA function through altered stability and glycosylation, potentially influencing prostate cancer.
• These findings contribute to understanding nsSNP roles in prostate cancer pathogenesis and drug resistance.