Predicting Pathogenicity Of nsSNPs Associated With Rb1 -- An In Silico Approach
Anum Munir

TL;DR
This study uses in silico computational tools to analyze SNPs in the Rb1 gene, identifying mutations likely to impact protein structure and function related to cancer risk.
Contribution
It integrates multiple computational methods to predict damaging SNPs in Rb1, providing insights into genetic variations associated with cancer.
Findings
Identified 17 damaging missense mutations in Rb1.
Predicted strong gene associations with 20 other genes.
Analyzed extensive SNP data from NCBI database.
Abstract
Single nucleotide polymorphisms (SNPs) are variations at specific locations in DNA. Sequence responsible for marking genes associated with diseases or tracking inherited diseases within The family. These variations in the Rb1 gene can cause Retinoblastoma and cancer in the retina Of one eye or both, Osteosarcoma, Melanoma, Leukemias, Lungs, and Breast cancer. First of all,The SNP database hosted by NCBI was used to extract some principal data. The association of Rb1 to Other genes were analyzed by GeneMANIA. Ten different computational tools, i.eSIFT,Polyphen-2, I-Mutant 3.0,PROVEAN, SNAP2, PHD-SNP, PMut, SNPs&GO were used for the screening of damaging SNP for the estimation of conserved regions of amino acids Consurf Server was used for the evaluation of the structural stability of both native and mutant proteins, Project Hope was used to examine the structural effects of mutant…
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Taxonomy
TopicsMachine Learning in Bioinformatics · Genetics, Bioinformatics, and Biomedical Research · Genomics and Rare Diseases
