Predicting the functional and structural consequences of nsSNPs in human methionine synthase gene using computational tools

Desai, Mansi; Chauhan, Jenabhai B.

doi:10.1080/19396368.2019.1568611

Cited by 11 publications

(7 citation statements)

References 48 publications

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“…The second is HumVar, which contains all common human single nucleotide polymorphisms and nondamaging proteins. 22 All the IDH1 R132H, IDH2 R172M, and TP53 K305N, R158G, and R175H mutations present a score more than 0.5, so these variants are predicted to be damaging; however, R175H in p53 is a benign mutation.…”

Section: Resultsmentioning

confidence: 99%

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas

et al. 2020

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Introduction: The emergence of new omics approaches, such as genomic algorithms to identify tumor mutations and molecular modeling tools to predict the three-dimensional structure of proteins, has facilitated the understanding of the dynamic mechanisms involved in the pathogenesis of low-grade gliomas including oligodendrogliomas and astrocytomas. Methods: In this study, we targeted known mutations involved in low-grade gliomas, starting with the sequencing of genomic regions encompassing exon 4 of isocitrate dehydrogenase 1 ( IDH1) and isocitrate dehydrogenase 2 ( IDH2) and the four exons (5-6 and 7-8) of TP53 from 32 samples, followed by computational analysis to study the impact of these mutations on the structure and function of 3 proteins IDH1, IDH2, and p53. Results: We obtain a mutation that has an effect on the catalytic site of the protein IDH1 as R132H and on the catalytic site of the protein IDH2 as R172M. Other mutations at p53 have been identified as K305N, which is a pathogenic mutation; R175 H, which is a benign mutation; and R158G, which disrupts the structural conformation of the tumor suppressor protein. Conclusion: In low-grade gliomas, mutations in IDH1, IDH2, and TP53 may be the key to tumor progression because they have an effect on the function of the protein such as mutations R132H in IDH1 and R172M in IDH2, which change the function of the enzyme alpha-ketoglutarate, or R158G in TP53, which affects the structure of the generated protein, thus their importance in understanding gliomagenesis and for more accurate diagnosis complementary to the anatomical pathology tests.

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Section: Resultsmentioning

confidence: 99%

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas

et al. 2020

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“…This computationally predicted protein model for AQP9, the significant target protein for rheumatoid arthritis could be further used for active site prediction and docking analysis. 11…”

Section: Discussionmentioning

confidence: 99%

Comparative Modeling, Characterization and Energy Minimization Studies of Aquaporin 9: An Exclusive Target Protein for Rheumatoid Arthritis

Das

Johri²,

Sharma

et al. 2019

IJPI

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Background: In the absence of the experimentally determined structure, computer aided protein structure prediction, evaluation and their energetically stable structure identification is the only way out of the problem. The main objective of the study was to perform the structure prediction of Aquaporin 9 (APQ9) the most targeted protein for rheumatoid arthritis, using in-silico methodology and validate the generated models. Methods: Secondary structure prediction of AQP9 was performed using GOR4, SOPMA and CFSSP algorithm. This was followed by the three-dimensional structure identification from MODELLER, LOMETS and MUSTER server. Many models were built and the best amongst them was identified on the basis of their DOPE score. RAMPAGE was used to validate these models and finally the selected model was energetically stabilized. Results: Amongst the 4 predicted models, model predicted using MODELLER software with 1FX8 PDB template (MODELER MODEL 2) was selected as the best. This model showed the best results in Ramachandran plot validation. In the Ramachandran Plot, 223 residues (95.7%) were found to be in the favored region, 9 residues (3.9%) in the Allowed region and the rest 1 residue (0.4%) in the Outlier region. Energy minimization calculations were also done for the four models using SPBDV software and Modeler Model 2 model showed the least energy (E= 3484.038 KJ/mol). Conclusion:The accurate three-dimensional structure prediction of proteins is a grand challenge now. Massive amount of sequence and structural data is available now with low cost. The choice of one or other method depends solely on the type of protein sequence and the quality of the predicted structure. The accurate structure prediction, fold recognition, energy calculation, side chain modeling and target template identification are the crucial edges of the molecular modeling process which need to be scrutinized for the best predicted model.

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“… 10 - 13 Thus, studying the association between different SNPs and their phenotypic impacts can help in understanding the molecular basis of many complex hereditary diseases. 5 , 14 - 18 …”

Section: Introductionmentioning

confidence: 99%

“…We investigated the functional consequences of the missense SNPs: whether they are normal or disease-causing or effective by any chance using SIFT, Align GVGD, PolyPhen2, PROVEAN, SNAP2, P-Mut, PhD-SNP, SNPs&GO, and PANTHER. 6 , 17 , 19 The stability of the mutated proteins was analyzed using computational tools like MUpro and I-Mutant. Then most potential nsSNPs were further analyzed using MutPred2.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Structural and Functional Effects of Nonsynonymous SNPs in the Human Serotonin Transporter Gene Through In Silico Approaches

Mia

Uddin

Akter

et al. 2022

Bioinform Biol Insights

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The sodium-dependent serotonin transporter SLC6A4 (solute carrier family 6 member 4) gene encodes an intrinsic membrane protein that transmits the serotonin neurotransmitter from synaptic clefts into presynaptic neurons. The product of the SLC6A4 gene is related to the regulation of mood and social behavior, sleep, appetite, memory, digestion, and sexual desire. This protein is a target for antidepressant and psychostimulant drugs, thus prolonged neurotransmitter signaling remains blocked. In this study, the functional consequences of nsSNPs in the human SLC6A4 gene were explored through computational tools: PhD-SNP, SIFT, Align GVGD, PROVEAN, PMut, nsSNP Analyzer, SNPs&GO, SNAP2, PolyPhen2, and PANTHER to identify the most deleterious and damaging nsSNPs. Then the mutant protein stabilities were assessed using I-Mutant, MUpro, and MutPred2; amino acid conservation using ConSurf, and posttranslational modification analysis using MusiteDEEP and PROSPER. Furthermore, the 3-dimensional (3D) model of the mutated proteins was predicted and validated using SPARKS-X, Verify3D, and PROCHECK. The protein–ligand binding sites were analyzed using the COACH meta-server. Results from this study predicted that T192M, G342E, R607C, W282S, R104C, P131L, P156L, and N351S were the most structurally and functionally significant nsSNPs in the human SLC6A4 gene. Arg607 and Pro156 were the predicted sites for posttranslational modifications, and Thr192 and Try282 were the ligand-binding sites in the human SLC6A4 gene. The analyzed data also suggested that R104C, P131L, P156L, T192M, G342E, and W282S mutants might affect the binding of sodium ions with this protein. Taken together, this study provided important information on structurally and functionally important nsSNPs of the human SLC6A4 gene for further experimental validation. In the future, these damaging nsSNPs of the SLC6A4 gene have the potential to be evaluated as prognostic biomarkers for SLC6A4-related disorder diagnosis and research.

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Predicting the functional and structural consequences of nsSNPs in human methionine synthase gene using computational tools

Cited by 11 publications

References 48 publications

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas

Computational Analysis of IDH1, IDH2, and TP53 Mutations in Low-Grade Gliomas Including Oligodendrogliomas and Astrocytomas

Comparative Modeling, Characterization and Energy Minimization Studies of Aquaporin 9: An Exclusive Target Protein for Rheumatoid Arthritis

Exploring the Structural and Functional Effects of Nonsynonymous SNPs in the Human Serotonin Transporter Gene Through In Silico Approaches

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