首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Identification and structural characterization of deleterious non-synonymous single nucleotide polymorphisms in the human SKP2 gene
Institution:1. School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India;2. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India;3. Department of Neuroscience Technology, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Jubail, Saudi Arabia;4. Department of Biotechnology, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India;5. Department of Biomedical Sciences, College of Health and Sciences, Qatar University, Doha, Qatar;1. Department of Biotechnology, Sri Ramachandra Institute of Higher Education and Research (DU), Chennai, Tamil Nadu, India;2. Laboratory of Integrative Genomics, Department of Integrative Biology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India;3. Meenakshi Academy of Higher Education and Research (Deemed to be University), Chennai, India
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.
Keywords:nsSNP  SKP2  Cancer  Molecular dynamics simulations  SIFT  PolyPhen-2
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号