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Structural Consequences of IRS-2 nsSNPs and Implication for Insulin Receptor Substrate-2 Protein Stability. Biochem Genet 2023; 61:69-86. [PMID: 35727487 DOI: 10.1007/s10528-022-10247-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 06/07/2022] [Indexed: 01/24/2023]
Abstract
Single-Nucleotide Polymorphisms (SNPs) are common genetic variations implicated in human diseases. The non-synonymous SNPs (nsSNPs) affect the proteins' structures and their molecular interactions with other interacting proteins during the accomplishment of biochemical processes. This ultimately causes proteins functional perturbation and disease phenotypes. The Insulin receptor substrate-2 (IRS-2) protein promotes glucose absorption and participates in the biological regulation of glucose metabolism and energy production. Several IRS-2 SNPs are reported in association with type 2 diabetes and obesity in human populations. However, there are no comprehensive reports about the protein structural consequences of these nsSNPs. Keeping in view the pathophysiological consequences of the IRS-2 nsSNPs, we designed the current study to understand their possible structural impact on coding protein. The prioritized list of the deleterious IRS-2 nsSNPs was acquired from multiple bioinformatics resources, including VEP (SIFT, PolyPhen, and Condel), PROVEAN, SNPs&GO, PMut, and SNAP2. The protein structure stability assessment of these nsSNPs was performed by MuPro and I-Mutant-3.0 servers via structural modeling approaches. The atomic-level structural and molecular dynamics (MD) impact of these nsSNPs were examined using GROMACS 2019.2 software package. The analyses initially predicted 8 high-risk nsSNPs located in the highly conserved regions of IRS-2. The MD simulation analysis eventually prioritized the N232Y, R218C, and R104H nsSNPs that predicted to significantly compromise the structure stability and may affect the biological function of IRS-2. These nsSNPs are predicted as high-risk candidates for diabetes and obesity. The validation of protein structural impact of these shortlisted nsSNPs may provide biochemical insight into the IRS-2-mediated type-2 diabetes.
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Identification of the most damaging nsSNPs in the human CFL1 gene and their functional and structural impacts on cofilin-1 protein. Gene 2022; 819:146206. [PMID: 35092861 DOI: 10.1016/j.gene.2022.146206] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 11/04/2021] [Accepted: 01/13/2022] [Indexed: 01/28/2023]
Abstract
The cofilin-1 protein, encoded by CFL1, is an actin-binding protein that regulates F-actin depolymerization and nucleation activity through phosphorylation and dephosphorylation. CFL1 has been implicated in the development of neurodegenerative diseases (Alzheimer's disease and Huntington's disease), neuronal migration disorders (lissencephaly, epilepsy, and schizophrenia), and neural tube closure defects. Mutations in CFL1 have been associated with impaired neural crest cell migration and neural tube closure defects. In our study, various computational approaches were utilized to explore single-nucleotide polymorphisms (SNPs) in CFL1. The Variation Viewer and gnomAD databases were used to retrieve CFL1 SNPs, including 46 nonsynonymous SNPs (nsSNPs). The functional and structural annotation of SNPs was performed using 12 sequence-based web applications, which identified 20 nsSNPs as being the most likely to be deleterious or disease-causing. The conservation of cofilin-1 protein structures was illustrated using the ConSurf and PROSITE web servers, which projected the 12 most deleterious nsSNPs onto conserved domains, with the potential to disrupt the protein's functionality. These 12 nsSNPs were selected for protein structure construction, and the DynaMut/DUET servers predicted that the protein variants V7G, L84P, and L99A were the most likely to be damaging to the cofilin-1 protein structure or function. The evaluation of molecular docking studies demonstrated that the L99A and L84P cofilin-1 variants reduce the binding affinity for actin compared with the native cofilin-1 structure, and molecular dynamic simulation studies confirmed that these variants might destabilize the protein structure. The consequences of putative mutations on protein-protein interactions and post-translational modification sites in the cofilin-1 protein structure were analyzed. This study represents the first complete approach to understanding the effects of nsSNPs within the actin-depolymerizing factor/cofilin family, which suggested that SNPs resulting in L84P (rs199716082) and L99A (rs267603119) variants represent significant CFL1 mutations associated with disease development.
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Accurate Sequence-Based Prediction of Deleterious nsSNPs with Multiple Sequence Profiles and Putative Binding Residues. Biomolecules 2021; 11:biom11091337. [PMID: 34572550 PMCID: PMC8469993 DOI: 10.3390/biom11091337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/04/2021] [Accepted: 09/06/2021] [Indexed: 11/17/2022] Open
Abstract
Non-synonymous single nucleotide polymorphisms (nsSNPs) may result in pathogenic changes that are associated with human diseases. Accurate prediction of these deleterious nsSNPs is in high demand. The existing predictors of deleterious nsSNPs secure modest levels of predictive performance, leaving room for improvements. We propose a new sequence-based predictor, DMBS, which addresses the need to improve the predictive quality. The design of DMBS relies on the observation that the deleterious mutations are likely to occur at the highly conserved and functionally important positions in the protein sequence. Correspondingly, we introduce two innovative components. First, we improve the estimates of the conservation computed from the multiple sequence profiles based on two complementary databases and two complementary alignment algorithms. Second, we utilize putative annotations of functional/binding residues produced by two state-of-the-art sequence-based methods. These inputs are processed by a random forests model that provides favorable predictive performance when empirically compared against five other machine-learning algorithms. Empirical results on four benchmark datasets reveal that DMBS achieves AUC > 0.94, outperforming current methods, including protein structure-based approaches. In particular, DMBS secures AUC = 0.97 for the SNPdbe and ExoVar datasets, compared to AUC = 0.70 and 0.88, respectively, that were obtained by the best available methods. Further tests on the independent HumVar dataset shows that our method significantly outperforms the state-of-the-art method SNPdryad. We conclude that DMBS provides accurate predictions that can effectively guide wet-lab experiments in a high-throughput manner.
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Almanasra A, Havranek B, Islam SM. In-silico screening and microsecond molecular dynamics simulations to identify single point mutations that destabilize β-hexosaminidase A causing Tay-Sachs disease. Proteins 2021; 89:1587-1601. [PMID: 34288098 DOI: 10.1002/prot.26180] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 06/17/2021] [Accepted: 07/11/2021] [Indexed: 11/07/2022]
Abstract
β-hexosaminidase A (HexA) protein is responsible for the degradation of GM2 gangliosides in the central and peripheral nervous systems. Tay-Sachs disease occurs when HexA within Hexosaminidase does not properly function and harmful GM2 gangliosides begin to build up within the neurons. In this study, in silico methods such as SIFT, PolyPhen-2, PhD-SNP, and MutPred were utilized to analyze the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) on HexA in order to identify possible pathogenetic and deleterious variants. Molecular dynamics (MD) simulations showed that two mutants, P25S and W485R, experienced an increase in structural flexibility compared to the native protein. Particularly, there was a decrease in the overall number and frequencies of hydrogen bonds for the mutants compared to the wildtype. MM/GBSA calculations were performed to help assess the change in binding affinity between the wildtype and mutant structures and a mechanism-based inhibitor, NGT, which is known to help increase the residual activity of HexA. Both of the mutants experienced a decrease in the binding affinity from -23.8 kcal/mol in wildtype to -20.9 and -18.7 kcal/mol for the P25S and W485R variants of HexA, respectively.
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Affiliation(s)
- Ahmad Almanasra
- Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Brandon Havranek
- Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Shahidul M Islam
- Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois, USA
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Patel S, Thakkar J, Koringa P, Jakhesara S, Patel A, De S, Joshi C. Evolution and diversity studies of innate immune genes in Indian buffalo (Bubalus bubalis) breeds using next generation sequencing. Genes Genomics 2017. [DOI: 10.1007/s13258-017-0585-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Chakrapani V, Rasal KD, Kumar S, Mohapatra SD, Sundaray JK, Jayasankar P, Barman HK. In Silico Analysis of nsSNPs of Carp TLR22 Gene Affecting its Binding Ability with Poly I:C. Interdiscip Sci 2017; 10:641-652. [PMID: 28660537 DOI: 10.1007/s12539-017-0247-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Revised: 02/21/2017] [Accepted: 02/27/2017] [Indexed: 11/29/2022]
Abstract
Immune response mediated by toll-like receptor 22 (TLR22), only found in teleost/amphibians, is triggered by double-stranded RNA binding to its LRR (leucine-rich repeats) ecto-domain. Accumulated evidences suggested that missense mutations in TLR genes affect its function. However, information on mutation linked pathogen recognition for TLR22 was lacking. The present study was commenced for predicting the effect of non-synonymous single-nucleotide polymorphisms (nsSNPs) on the pathogen recognizable LRR domain of TLR22 of farmed carp, Labeo rohita. The sequence-based algorithms (SIFT, PROVEAN and I-Mutant2.0) indicated that three SNPs (out of 27) such as p.L159F (rs76759876) and p.L529P (rs749355507) of LRR, and p.I836M (rs750758397) of intracellular motifs could potentially disrupt protein function. The 3D structure was generated using MODELLER 9.13 and further validated by SAVEs server. The simulated molecular docking of native TLR22 and mutants with poly I:C ligand indicated that mutations positioned at p.L159F and p.L529P of the LRR region affects the binding affinity significantly. This is the first kind of study of predicting nsSNPs of teleost TLR22 with disturbed ligand binding affinity with its extra-cellular LRR domain and thereby likely hindrance in subsequent signal transduction. This study serves as a guide for in vivo evaluation of impact of mutation on immune response mediated by teleost TLR22 gene.
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Affiliation(s)
- Vemulawada Chakrapani
- Fish Genetics and Biotechnology Division, ICAR, Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha, 751002, India
| | - Kiran D Rasal
- Fish Genetics and Biotechnology Division, ICAR, Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha, 751002, India
| | - Sunil Kumar
- ICAR, National Bureau of Agriculturally Important Microorganisms, Mau, Uttar Pradesh, 275103, India
| | - Shibani D Mohapatra
- Fish Genetics and Biotechnology Division, ICAR, Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha, 751002, India
| | - Jitendra K Sundaray
- Fish Genetics and Biotechnology Division, ICAR, Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha, 751002, India
| | - Pallipuram Jayasankar
- Fish Genetics and Biotechnology Division, ICAR, Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha, 751002, India
| | - Hirak K Barman
- Fish Genetics and Biotechnology Division, ICAR, Central Institute of Freshwater Aquaculture, Kausalyaganga, Bhubaneswar, Odisha, 751002, India.
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Thangaraju K, Király R, Demény MA, András Mótyán J, Fuxreiter M, Fésüs L. Genomic variants reveal differential evolutionary constraints on human transglutaminases and point towards unrecognized significance of transglutaminase 2. PLoS One 2017; 12:e0172189. [PMID: 28248968 PMCID: PMC5332030 DOI: 10.1371/journal.pone.0172189] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2016] [Accepted: 02/01/2017] [Indexed: 01/16/2023] Open
Abstract
Transglutaminases (TGMs) catalyze Ca2+-dependent transamidation of proteins with specified roles in blood clotting (F13a) and in cornification (TGM1, TGM3). The ubiquitous TGM2 has well described enzymatic and non-enzymatic functions but in-spite of numerous studies its physiological function in humans has not been defined. We compared data on non-synonymous single nucleotide variations (nsSNVs) and loss-of-function variants on TGM1-7 and F13a from the Exome aggregation consortium dataset, and used computational and biochemical analysis to reveal the roles of damaging nsSNVs of TGM2. TGM2 and F13a display rarer damaging nsSNV sites than other TGMs and sequence of TGM2, F13a and TGM1 are evolutionary constrained. TGM2 nsSNVs are predicted to destabilize protein structure, influence Ca2+ and GTP regulation, and non-enzymatic interactions, but none coincide with conserved functional sites. We have experimentally characterized six TGM2 allelic variants detected so far in homozygous form, out of which only one, p.Arg222Gln, has decreased activities. Published exome sequencing data from various populations have not uncovered individuals with homozygous loss-of-function variants for TGM2, TGM3 and TGM7. Thus it can be concluded that human transglutaminases differ in harboring damaging variants and TGM2 is under purifying selection suggesting that it may have so far not revealed physiological functions.
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Affiliation(s)
- Kiruphagaran Thangaraju
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Róbert Király
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Máté A. Demény
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - János András Mótyán
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Mónika Fuxreiter
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
- MTA-DE Momentum Laboratory of Protein Dynamics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - László Fésüs
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
- MTA-DE Stem cell, Apoptosis and Genomics Research Group of Hungarian Academy of Sciences, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
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Singh HB, Deka D, Das D, Borbora D. Computational prediction of the effects of non-synonymous single nucleotide polymorphisms in the human Quinone Oxidoreductase 1 (NQO1). Meta Gene 2017. [DOI: 10.1016/j.mgene.2016.12.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Patel SM, Koringa PG, Reddy BB, Nathani NM, Joshi CG. In silico analysis of consequences of non-synonymous SNPs of Slc11a2 gene in Indian bovines. GENOMICS DATA 2015; 5:72-9. [PMID: 26484229 PMCID: PMC4583633 DOI: 10.1016/j.gdata.2015.05.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Revised: 05/21/2015] [Accepted: 05/21/2015] [Indexed: 01/20/2023]
Abstract
The aim of our study was to analyze the consequences of non-synonymous SNPs in Slc11a2 gene using bioinformatic tools. There is a current need of efficient bioinformatic tools for in-depth analysis of data generated by the next generation sequencing technologies. SNPs are known to play an imperative role in understanding the genetic basis of many genetic diseases. Slc11a2 is one of the major metal transporter families in mammals and plays a critical role in host defenses. In this study, we performed a comprehensive analysis of the impact of all non-synonymous SNPs in this gene using multiple tools like SIFT, PROVEAN, I-Mutant and PANTHER. Among the total 124 SNPs obtained from amplicon sequencing of Slc11a2 gene by Ion Torrent PGM involving 10 individuals of Gir cattle and Murrah buffalo each, we found 22 non-synonymous. Comparing the prediction of these 4 methods, 5 nsSNPs (G369R, Y374C, A377V, Q385H and N492S) were identified as deleterious. In addition, while tested out for polar interactions with other amino acids in the protein, from above 5, Y374C, Q385H and N492S showed a change in interaction pattern and further confirmed by an increase in total energy after energy minimizations in case of mutant protein compared to the native. 22 nsSNPs were predicted to decrease the stability of protein based on I-Mutant. From these SNPs, 5 was identified as deleterious by SIFT, PROVEAN, and PANTHER. Y374C, Q385H and N492S were found to be damaging.
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Key Words
- ATM, ataxia telangiectasia mutated
- BRAF, B-Raf
- CFTR, cystic fibrosis transmembrane conductance regulator
- GATK, Genome Analysis Tool Kit
- GalNAc-T1, N-acetylgalactosaminyltransferase 1
- HBB, hemoglobin beta
- HMM, Hidden Markov Model
- IGF1R, insulin-like growth factor 1 receptor
- Ion torrent PGM
- NCBI, National Center for Biotechnology Information
- Non-synonymous
- PANTHER
- PANTHER, Protein Analysis Through Evolutionary Relationships
- PROVEAN, Protein Variation Effect Analyzer
- PolyPhen, Polymorphism Phenotyping
- Protein
- RMSD, root-mean-square deviation
- SIFT
- SIFT, sorting intolerant from tolerant
- SNP, single nucleotide polymorphism
- Slc11a2, solute carrier family 11 member 2
- TMDs, transmembrane domains
- TYRP1, tyrosinase-related protein 1
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Affiliation(s)
- Shreya M Patel
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Prakash G Koringa
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Bhaskar B Reddy
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Neelam M Nathani
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
| | - Chaitanya G Joshi
- Department of Animal Biotechnology, College of Veterinary Science and Animal Husbandry, Anand Agricultural University, Anand,388001 Gujarat, India
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MIMP: predicting the impact of mutations on kinase-substrate phosphorylation. Nat Methods 2015; 12:531-3. [DOI: 10.1038/nmeth.3396] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Accepted: 03/30/2015] [Indexed: 12/14/2022]
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