FANCA: In-Silico deleterious mutation analysis for early prediction of leukemia

TL;DR

This study uses computational tools to analyze FANCA gene mutations, identifying deleterious SNPs that could serve as early biomarkers for leukemia, aiding in precision medicine development.

Contribution

The paper introduces a comprehensive in-silico approach combining multiple tools to identify deleterious FANCA mutations linked to leukemia, advancing early prediction methods.

Findings

24 missense SNPs identified as deleterious by all analyses

Six computational tools used to study leukemia-associated nsSNPs

Deleterious nsSNPs may contribute to FANCA up-regulation and leukemia progression

Abstract

As a novel biomarker from the Fanconi anemia complementation group (FANC) family, FANCA is antigens to Leukemia cancer. The overexpression of FANCA has predicted the second most common cancer in the world that is responsible for cancer-related deaths. Non-synonymous SNPs are an essential group of SNPs that lead to alterations in encoded polypeptides. Changes in the amino acid sequences of gene products lead to Leukemia. First, we study individual SNPs in the coding region of FANCA and computational tools like PROVEAN, PolyPhen2, MuPro, and PANTHER to compute deleterious mutation scores. The three-dimensional structural and functional prediction conducted using I-TASSER. Further, the predicted structure refined using the GlaxyWeb tool. In the study, the proteomic data has been retrieved from the UniProtKB. The coding region of the dataset contains 100 non-synonymous single nucleotide polymorphisms (nsSNPs), and 24 missense SNPs have been determined as deleterious by all analyses. In this work, six well-known computational tools were employed to study Leukemia-associated nsSNPs. It is inferred that these nsSNPs could play their role in the up-regulation of FANCA, which further leads to provoke leukemia advancement. The current research would benefit researchers and practitioners in handling cancer-associated diseases related to FANCA. The proposed study would also help to develop precision medicine in the field of drug discovery.