title: Prediction of functionally significant single nucleotide polymorphisms in PTEN tumor suppressor gene: An in silico approach.
abstract: The phosphatase and tensin homolog (PTEN) gene plays a crucial role in signal transduction by negatively regulating the PI3K signaling pathway. It is the most frequent mutated gene in many human-related cancers. Considering its critical role, a functional analysis of missense mutations of PTEN gene was undertaken in this study. Thirty five nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of the PTEN gene were selected for our in silico investigation, and five nsSNPs (G129E, C124R, D252G, H61D, and R130G) were found to be deleterious based on combinatorial predictions of different computational tools. Moreover, molecular dynamics (MD) simulation was performed to investigate the conformational variation between native and all the five mutant PTEN proteins having predicted deleterious nsSNPs. The results of MD simulation of all mutant models illustrated variation in structural attributes such as root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and total energy; which depicts the structural stability of PTEN protein. Furthermore, mutant PTEN protein structures also showed a significant variation in the solvent accessible surface area and hydrogen bond frequencies from the native PTEN structure. In conclusion, results of this study have established the deleterious effect of the all the five predicted nsSNPs on the PTEN protein structure. Thus, results of the current study can pave a new platform to sort out nsSNPs that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case of control studies.
authors.affiliation: Department of Biosciences, Integral University, Lucknow, India.
authors.forename: Imran
authors.initials: I
authors.lastname: Khan
authors.affiliation: Department of Biosciences, Integral University, Lucknow, India.
authors.forename: Irfan A
authors.initials: IA
authors.lastname: Ansari
authors.affiliation: School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, India.
authors.forename: Pratichi
authors.initials: P
authors.lastname: Singh
authors.affiliation: School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, India.
authors.forename: Febin Prabhu
authors.initials: FP
authors.lastname: Dass J
mesh_terms: D019295:Computational Biology; D057225:Data Mining; D006801:Humans; D056004:Molecular Dynamics Simulation; D020125:Mutation, Missense / Q000235:genetics / Q000502:physiology; D051059:PTEN Phosphohydrolase / Q000737:chemistry / Q000235:genetics* / Q000502:physiology*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics* / Q000502:physiology*; D011487:Protein Conformation
chemical_list: D051059:PTEN Phosphohydrolase; C494929:PTEN protein, human
keywords: RMSD; SNP; deleterious; in silico, PTEN; signaling pathways