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Добірка наукової літератури з теми "NSSNPS AFFECTING STABILITY"
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Статті в журналах з теми "NSSNPS AFFECTING STABILITY"
1
Ait El Cadi, Chaimaa, Al Mehdi Krami, Hicham Charoute, Zouhair Elkarhat, Najat Sifeddine, Hamid Lakhiari, Hassan Rouba, Abdelhamid Barakat, and Halima Nahili. "Prediction of the Impact of Deleterious Nonsynonymous Single Nucleotide Polymorphisms on the Human RRM2B Gene: A Molecular Modeling Study." BioMed Research International 2020 (July 26, 2020): 1–10. http://dx.doi.org/10.1155/2020/7614634.
Повний текст джерелаАнотація:
RRM2B gene encodes ribonucleoside-diphosphate reductase subunit M2 B, the p53-inducible small subunit (p53R2) of ribonucleotide reductase (RNR), an enzyme catalyzing dNTP synthesis for mitochondrial DNA. Defects in this gene may cause severe mitochondrial disease affecting mainly the nervous system. This study is aimed at examining the effect of deleterious nonsynonymous SNP (nsSNP) on the structure of the RRM2B protein, using a variety of prediction tools followed by a molecular modeling analysis. After using 13 algorithms, 19 nsSNPs were predicted deleterious. Among these variants, 18 decreased the protein stability and 16 were localized in very highly conserved regions. Protein 3D structure analysis showed that 18 variants changed amino acid interactions. These results concur with what has been found in experimental trials; 7 deleterious nsSNPs were previously reported in patients suffering from genetic disorders affecting the nervous system. Thus, our study will provide useful information to design more efficient and fast genetic tests to find RRM2B gene mutations.
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Mahmud, Zabed, Syeda Umme Fahmida Malik, Jahed Ahmed, and Abul Kalam Azad. "Computational Analysis of Damaging Single-Nucleotide Polymorphisms and Their Structural and Functional Impact on the Insulin Receptor." BioMed Research International 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/2023803.
Повний текст джерелаАнотація:
Single-nucleotide polymorphisms (SNPs) associated with complex disorders can create, destroy, or modify protein coding sites. Single amino acid substitutions in the insulin receptor (INSR) are the most common forms of genetic variations that account for various diseases like Donohue syndrome or Leprechaunism, Rabson-Mendenhall syndrome, and type A insulin resistance. We analyzed the deleterious nonsynonymous SNPs (nsSNPs) in INSR gene based on different computational methods. Analysis of INSR was initiated with PROVEAN followed by PolyPhen and I-Mutant servers to investigate the effects of 57 nsSNPs retrieved from database of SNP (dbSNP). A total of 18 mutations that were found to exert damaging effects on the INSR protein structure and function were chosen for further analysis. Among these mutations, our computational analysis suggested that 13 nsSNPs decreased protein stability and might have resulted in loss of function. Therefore, the probability of their involvement in disease predisposition increases. In the lack of adequate prior reports on the possible deleterious effects of nsSNPs, we have systematically analyzed and characterized the functional variants in coding region that can alter the expression and function of INSR gene. In silico characterization of nsSNPs affecting INSR gene function can aid in better understanding of genetic differences in disease susceptibility.
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Akter, Shamima, Shafaat Hossain, Md Ackas Ali, Md Ismail Hosen, and Hossain Uddin Shekhar. "Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools." Biomolecules 11, no. 11 (November 20, 2021): 1733. http://dx.doi.org/10.3390/biom11111733.
Повний текст джерелаАнотація:
Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the TP63 gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human TP63 gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on TP63 gene loci and ascertain their association with certain diseases.
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Varghese, Rosemol, Soumya Basu, Ayyanraj Neeravi, Agilakumari Pragasam, V. Aravind, Richa Gupta, Angel Miraclin, Sudha Ramaiah, Anand Anbarasu, and Balaji Veeraraghavan. "Emergence of Meropenem Resistance Among Cefotaxime Non-susceptible Streptococcus pneumoniae: Evidence and Challenges." Frontiers in Microbiology 12 (February 3, 2022). http://dx.doi.org/10.3389/fmicb.2021.810414.
Повний текст джерелаАнотація:
The principal causative agent of acute bacterial meningitis (ABM) in children and the elderly is Streptococcus pneumoniae, with a widespread increase in penicillin resistance. Resistance is due to non-synonymous single-nucleotide polymorphisms (nsSNPs) that alter the penicillin-binding proteins (PBPs), the targets for all β-lactam drugs. Hence, resistance against one β-lactam antibiotic may positively select another. Since meropenem is an alternative to cefotaxime in meningeal infections, we aim to identify whether nsSNPs in the PBPs causing penicillin and cefotaxime resistance can decrease the pneumococcal susceptibility to meropenem. Comparison of the nsSNPs in the PBPs between the cefotaxime-resistant Indian (n = 33) and global isolates (n = 28) revealed that nsSNPs in PBP1A alone elevated meropenem minimal inhibitory concentrations (MICs) to 0.12 μg/ml, and nsSNPs in both PBP2X and 2B combined with PBP1A increases MIC to ≥ 0.25 μg/ml. Molecular docking confirmed the decrease in the PBP drug binding affinity due to the nsSNPs, thereby increasing the inhibition potential and the MIC values, leading to resistance. Structural dynamics and thermodynamic stability pattern in PBPs as a result of mutations further depicted that the accumulation of certain nsSNPs in the functional domains reduced the drug affinity without majorly affecting the overall stability of the proteins. Restricting meropenem usage and promoting combination therapy with antibiotics having non-PBPs as targets to treat cefotaxime non-susceptible S. pneumoniae meningitis can prevent the selection of β-lactam resistance.
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Al-Shuhaib, Mohammed Baqur S. "D76V, L161R, and C117S are the most pathogenic amino acid substitutions with several dangerous consequences on leptin structure, function, and stability." Egyptian Journal of Medical Human Genetics 20, no. 1 (December 2019). http://dx.doi.org/10.1186/s43042-019-0033-2.
Повний текст джерелаАнотація:
Abstract Background Leptin is a versatile hormone with a variety of functions, including regulation of food intake by inhibiting hunger. Any deleterious mutation in this protein can lead to serious consequences for the body. This study was conducted to identify the most deleterious non-synonymous single-nucleotide polymorphisms (nsSNPs) of human LEP gene and their impact on its encoded protein. Methods To predict the possible impact of nsSNPs on leptin, a total of 90 nsSNPs were retrieved from dbSNP and investigated using many in silico tools which specially designed to analyze nsSNPs’ consequences on the protein structure, function, and stability. Results Three nsSNPs, namely D76V, L161R, and C117S, were found to be completely deleterious by all utilized nsSNPs prediction tools, thus affecting leptin protein structure, biological activity, and stability. Evolutionary information indicated L161R and C117S mutations to be located in extremely high conserved positions. Furthermore, several deleterious mechanisms controlled by both L161R and C117S mutations which alter several motifs in the secondary structure of leptin were detected. However, all D76V, L161R, and C117S mutations exhibited alteration in polar interactions in their representative positions. Further in-depth analyses proved several harmful structural effects of the three nsSNPs on leptin, which may lead to multiple intrinsic disorders in the altered protein forms. Conclusions This study provides the first comprehensive computation of the effect of the most damaging nsSNPs on leptin. The exploration of these missense mutations may present novel perspectives for various deleterious consequences originated from such amino acids substitutions. The dynamics of leptin performance, therefore, in many biological pathways, may be changed to create a variety of disorders, such as obesity and diabetes. These findings will help in detecting the most harmful variations needed to be screened for clinically diagnosed patients with leptin disorders. Trial registration ISRCTN73824458
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Chamani, Reyhane, Parnia Sadat Pourhesseini MahmoudAbadi, Yasamin Janati, and Roxana Tajdini. "A comprehensive in silico analysis of pathogenic nsSNPs in the NT5C2 gene involved in relapsed ALL." Iranian Journal of Pediatric Hematology & Oncology, October 22, 2022. http://dx.doi.org/10.18502/ijpho.v12i4.10915.
Повний текст джерелаАнотація:
Background: About 10-20% of children suffering from acute lymphoblastic leukemia (ALL), experience a relapse, which is a major cause of their death. Purine nucleotide analogs are frequently prescribed to maintain the treatment of ALL. Cytosolic 5´-nucleotidase (NT5C2) catalyzes the 5´ dephosphorylation of purine analogs. Gain-of-function mutations in the NT5C2 gene result in resistance to the treatment with purine analogs and subsequently in the relapse of the disease.
Materials and Methods: In this descriptive study, bioinformatics tools were used to assess the effect of single nucleotide polymorphisms (SNPs) in the NT5C2 gene on the function and structure of the protein. So, 352 missense variants were retrieved from the NCBI database and analyzed by SIFT, PROVEAN, PMut, PANTHER, PolyPhen2, SNPs & Go, and PhD-SNP servers. Then, structural evaluations were performed using HOPE, NetSurp-2.0, and PyMOL. Moreover, stability and evolutionary preservation were assessed by I-Mutant2.0 and ConSurf, respectively.
Results: As many as 31 nsSNPs were predicted to be affecting the protein function and stability. Also, the native residues were found to be evolutionarily preserved. The structural evaluation demonstrated that a change of hydrophobicity, flexibility, size, charge, or surface accessibility due to 24 nsSNPs would lead to the change of noncovalent interactions and then the conformation of the protein.
Conclusion: Identification of biomarkers is significant in the prediction of relapses in ALL children. In this study, bioinformatics tools served to identify 24 high-risk deleterious nsSNPs in the NT5C2 gene. These mutations can be used to predict resistance to chemotherapy and relapse in ALL patients.
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Das, Shuvo Chandra, Md Anisur Rahman, and Shipan Das Gupta. "In-silico analysis unravels the structural and functional consequences of non-synonymous SNPs in the human IL-10 gene." Egyptian Journal of Medical Human Genetics 23, no. 1 (January 23, 2022). http://dx.doi.org/10.1186/s43042-022-00223-x.
Повний текст джерелаАнотація:
Abstract Background Interleukin-10 (IL-10) is an anti-inflammatory cytokine that affects different immune cells. It is also associated with the stimulation of the T and B cells for the production of antibodies. Several genetic polymorphisms in the IL-10 gene have been reported to cause or aggravate certain diseases like inflammatory bowel disease, rheumatoid arthritis, systemic sclerosis, asthma, etc. However, the disease susceptibility and abnormal function of the mutated IL-10 variants remain obscure. Results In this study, we used seven bioinformatics tools (SIFT, PROVEAN, PMut, PANTHER, PolyPhen-2, PHD-SNP, and SNPs&GO) to predict the disease susceptible non-synonymous SNPs (nsSNPs) of IL-10. Nine nsSNPs of IL-10 were predicted to be potentially deleterious: R42G, R45Q, F48L, E72G, M95T, A98D, R125S, Y155C, and I168T. Except two, all of the putative deleterious mutations are found in the highly conserved region of IL-10 protein structure, thus affecting the protein's stability. The 3-D structure of mutant proteins was modeled by project HOPE, and the protein–protein interactions were assessed with STRING. The predicted nsSNPs: R42Q, R45Q, F48L, E72G, and I168T are situated in the binding site region of the IL-10R1 receptor. Disruption of binding affinity with its receptor leads to deregulation of the JAK-STAT pathway and results in enhanced inflammation that imbalance in cellular signaling. Finally, Kaplan–Meier Plotter analysis displayed that deregulation of IL-10 expression affects gastric and ovarian cancer patients' survival rate. Thus, IL-10 could be useful as a potential prognostic marker gene for some cancers. Conclusion This study has determined the deleterious nsSNPs of IL-10 that might contribute to the malfunction of IL-10 protein and ultimately lead to the IL-10 associated diseases.
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"In Silico Analysis of Nonsynonumus Single Nucleotide Polymorphisms(nsSNPs) in Human GAAGene." Sudanese Online Research Journal, May 1, 2021, 78–92. http://dx.doi.org/10.51527/v2i2.09.
Повний текст джерелаАнотація:
GATA2 or GATA-binding factor 2 is a transcription factor, which regulates the expression of genes that are critical for the embryonic development, self-renewal, maintenance, and functionality of blood-forming lymphatic system-forming, and other tissue-forming stem cells. GATA2 protein is encoded by the GATA2 gene which often suffers germ line and somatic mutations which lead to a wide range of familial and sporadic diseases. Association of data including protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity were predicted using Gene MANIA software. This gene was investigated in NCBI database and the Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) were analyzed by computational software, (SIFT, PROVEAN, Polyphen-2, SNPs & GO, PHD-SNPs, I-Mutant and MUpro). The Protein structural analysis was done by modelling of amino acid substitutions using Project Hope for all predicted pathological polymorphisms. GeneMANIA results showed that GATA 2 gene was associated with 20 other genes. It interacts mainly with ZFPM1 gene (Zinc Finger Protein), FOG family member 1and HDAC5 histone deacetylase5. A total of 246 nsSNPs were obtained from the SNPs database in NCBI consisting of 47 Deleterious predicted by SIFT software. Using PROVEAN 41 SNPs were predicted to have deleterious effect, 17 SNPs were predicted to be damaging by (Polyphen- 2), while 4 SNPs were benign, 14 SNPs were found to be disease related using SNPs&GO and 30 SNPS were found to be disease related using PHD- SNP. By using I-MUTANT and MUPRO software the stability of the protein was predicted. From the results of SIFT, PROVEAN and PolyPhen-2 with respect to PHD-SNPs and SNPs&GO software programs, 6 nsSNPs (rs148942346 (R344I), rs371096438 (P385N), rs387906629 (R398W), rs387906629 (R384W), rs387906633 (C359R) and rs387906633 (C373R)) were predicted to be deleterious, damaging, affecting the protein stability and related to the formation of a disease variants. These results might be beneficial for a precise diagnosis of GATA2 deficiency and related myeloid neoplasm.
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"Insilco Analysis of Non-Synonymous Single Nucleotide Polymorphisms of GATA 2 binding factor Human Gene." Sudanese Online Research Journal, May 1, 2021, 103–10. http://dx.doi.org/10.51527/v2i2.12.
Повний текст джерелаАнотація:
GATA2 or GATA-binding factor 2 is a transcription factor, which regulates the expression of genes that are critical for the embryonic development, self-renewal, maintenance, and functionality of blood-forming lymphatic system-forming, and other tissue-forming stem cells. GATA2 protein is encoded by the GATA2 gene which often suffers germ line and somatic mutations which lead to a wide range of familial and sporadic diseases. Association of data including protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity were predicted using Gene MANIA software. This gene was investigated in NCBI database and the Non-Synonymous Single Nucleotide Polymorphisms (nsSNPs) were analyzed by computational software, (SIFT, PROVEAN, Polyphen-2, SNPs&GO, PHD-SNPs, I-Mutant and MUpro). The Protein structural analysis was done by modelling of amino acid substitutions using Project Hope for all predicted pathological polymorphisms. GeneMANIA results showed that GATA 2 gene was associated with 20 other genes. It interacts mainly with ZFPM1 gene (Zinc Finger Protein), FOG family member 1and HDAC5 histone deacetylase5. A total of 246 nsSNPs were obtained from the SNPs database in NCBI consisting of 47 Deleterious predicted by SIFT software. Using PROVEAN 41 SNPs were predicted to have deleterious effect, 17 SNPs were predicted to be damaging by (Polyphen- 2), while 4 SNPs were benign, 14 SNPs were found to be disease related using SNPs&GO and 30 SNPS were found to be disease related using PHD- SNP. By using I-MUTANT and MUPRO software the stability of the protein was predicted. From the results of SIFT, PROVEAN and PolyPhen-2 with respect to PHD-SNPs and SNPs&GO software programs, 6 nsSNPs (rs148942346 (R344I), rs371096438 (P385N), rs387906629 (R398W), rs387906629 (R384W), rs387906633 (C359R) and rs387906633 (C373R)) were predicted to be deleterious, damaging, affecting the protein stability and related to the formation of a disease variants. These results might be beneficial for a precise diagnosis of GATA2 deficiency and related myeloid neoplasm.
Дисертації з теми "NSSNPS AFFECTING STABILITY"
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GUPTA, HIMANI. "IN SILICO ANALYSIS OF NSSNPS AFFECTING STABILITY AND DYNAMICS OF P-GLYCOPROTEIN -A BREAST CANCER ASSOCIATED PROTEIN IDENTIFIED FROM GENE-ENVIRONMENT INTERACTION STUDIES." Thesis, 2014. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15634.
Повний текст джерелаАнотація:
The correct identification of functional SNPs of any gene is an important aspect in the study of genomics but loss of consistent genotype and phenotype data hampers any experiment to characterize the functional influence of all SNPs in humans. Therefore, in silico methods assist in providing useful information for characterizing functional aspect of SNPs. In this study, we have made an intense effort to identify potentially functional SNPs influencing protein function in environment susceptible genes discovered in Breast Cancer pathway. For this we used set of bioinformatic tools that utilize homology-based structure profile information, sequence-based conservation profile, and support vector algorithm in order to examine the nsSNPs found in the breast cancer patients. ABCB1 is one such environment susceptible gene coding for P-glycoprotein which is found to be overexpressed in tumour cells and is the root cause for drug efflux in breast cancer. Six different somatic missense mutations in the human ABCB1 gene in breast cancer patients have been reported in COSMIC database as of 2014.
In this study we have applied a set of tools like PolyPhen 2.0, PhD-SNP, and MutPred to display with accurate prediction the disease-associated mutations in ABCB1 gene and their structural impact. Further, we have carried out molecular dynamic simulations (MDS) to study the molecular as well as structural role of predicted disease associated nsSNPs. MDS was used to observe the atomic interaction and motion trajectory of native and mutant (R538S and M701R) P-glycoprotein. Out of these six nsSNPs, two mutations R538S which is present in the ATP binding domain at NMD interface and M701R present in the TMD domain of P-gp have been predicted to be deleterious by our analysis.