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Updated: Jan 28, 2026

Genotyping Single Nucleotide Polymorphisms in the Mitochondrial Genome by Pyrosequencing
Published on: February 10, 2023
Identification and structural characterization of deleterious non-synonymous single nucleotide polymorphisms in the
S M Zahid Hosen1, Raju Dash2, Md Junaid1
1Molecular Modeling and Drug Design Laboratory, Pharmacology Research Division, Bangladesh Council of Scientific and Industrial Research, Chittagong, 4220, Bangladesh.
Abstract:
In SCF (Skp, Cullin, F-box) ubiquitin-protein ligase complexes, S-phase kinase 2 (SKP2) is one of the major players of F-box family, that is responsible for the degradation of several important cell regulators and tumor suppressor proteins. Despite of having significant evidence for the role of SKP2 on tumorgenesis, there is a lack of available data regarding the effect of non-synonymous polymorphisms. In this communication, the structural and functional consequences of non-synonymous single nucleotide polymorphisms (nsSNPs) of SKP2 have been reported by employing various computational approaches and molecular dynamics simulation. Initially, several computational tools like SIFT, PolyPhen-2, PredictSNP, I-Mutant 2.0 and ConSurf have been implicated in this study to explore the damaging SNPs. In total of 172 nsSNPs, 5 nsSNPs were identified as deleterious and 3 of them were predicted to be decreased the stability of protein. Guided from ConSurf analysis, P101L (rs761253702) and Y346C (rs755010517) were categorized as the highly conserved and functional disrupting mutations. Therefore, these mutations were subjected to three dimensional model building and molecular dynamics simulation study for the detailed structural consequences upon the mutations. The study revealed that P101L and Y346C mutations increased the flexibility and changed the structural dynamics. As both these mutations are located in the most functional regions of SKP2 protein, these computational insights might be helpful to consider these nsSNPs for wet-lab confirmatory analysis as well as in rationalizing future population based studies and structure based drug design against SKP2.
Insights
Computational analysis identified two specific non-synonymous single nucleotide polymorphisms (nsSNPs) in S-phase kinase 2 (SKP2) that disrupt protein structure and function, offering insights into cancer mechanisms and drug design.
Area of Science:
- Biochemistry
- Molecular Biology
- Computational Biology
Background:
- The SCF (Skp, Cullin, F-box) ubiquitin-protein ligase complex regulates protein degradation.
- S-phase kinase 2 (SKP2) is a key F-box protein involved in cell cycle regulation and tumor suppression.
- The impact of SKP2 non-synonymous single nucleotide polymorphisms (nsSNPs) on its function is largely uncharacterized.
Purpose of the Study:
- To computationally investigate the structural and functional consequences of nsSNPs in SKP2.
- To identify specific nsSNPs that may negatively impact SKP2 stability and function.
- To provide a basis for further experimental validation and drug development targeting SKP2.
Main Methods:
- Utilized multiple computational tools (SIFT, PolyPhen-2, PredictSNP, I-Mutant 2.0, ConSurf) to predict damaging nsSNPs.
- Performed 3D model building and molecular dynamics simulations for selected mutations.
- Analyzed the impact of mutations on protein stability, flexibility, and structural dynamics.
Main Results:
- Identified 5 deleterious nsSNPs out of 172 analyzed.
- Three nsSNPs were predicted to decrease protein stability.
- P101L (rs761253702) and Y346C (rs755010517) were identified as highly conserved and functionally disruptive mutations.
- Molecular dynamics simulations showed P101L and Y346C mutations increase protein flexibility and alter structural dynamics.
Conclusions:
- The identified nsSNPs, particularly P101L and Y346C, significantly alter SKP2 protein structure and dynamics.
- These mutations occur in functionally important regions of SKP2.
- The findings support further wet-lab investigation of these nsSNPs and their role in cancer.
- Computational insights can guide future population studies and structure-based drug design targeting SKP2.
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