Computational Analysis of Damaging Single-Nucleotide Polymorphisms and Their Structural and Functional Impact on the Insulin Receptor

Identification and In-Silico study of non-synonymous functional SNPs in the human SCN9A gene

Single nucleotide polymorphisms are the most common form of DNA alterations at the level of a single nucleotide in the genomic sequence. Genome-wide association studies (GWAS) were carried to identify potential risk genes or genomic regions by screening for SNPs associated with disease. Recent studies have shown that SCN9A comprises the NaV1.7 subunit, Na+ channels have a gene encoding of 1988 amino acids arranged into 4 domains, all with 6 transmembrane regions, and are mainly found in dorsal root ganglion (DRG) neurons and sympathetic ganglion neurons. Multiple forms of acute hypersensitivity conditions, such as primary erythermalgia, congenital analgesia, and paroxysmal pain syndrome have been linked to polymorphisms in the SCN9A gene. Under this study, we utilized a variety of computational tools to explore out nsSNPs that are potentially damaging to heath by modifying the structure or activity of the SCN9A protein. Over 14 potentially damaging and disease-causing nsSNPs (E1889D, L1802P, F1782V, D1778N, C1370Y, V1311M, Y1248H, F1237L, M936V, I929T, V877E, D743Y, C710W, D623H) were identified by a variety of algorithms, including SNPnexus, SNAP-2, PANTHER, PhD-SNP, SNP & GO, I-Mutant, and ConSurf. Homology modeling, structure validation, and protein-ligand interactions also were performed to confirm 5 notable substitutions (L1802P, F1782V, D1778N, V1311M, and M936V). Such nsSNPs may become the center of further studies into a variety of disorders brought by SCN9A dysfunction. Using in-silico strategies for assessing SCN9A genetic variations will aid in organizing large-scale investigations and developing targeted therapeutics for disorders linked to these variations.

Autosomal dominant polycystic kidney disease (ADPKD) in Tunisia: From molecular genetics to the development of prognostic tools

A high prevalence of genetic kidney disease in Tunisia has been detected, and their study provides very important clinical and genetic information. Autosomal dominant polycystic kidney disease (ADPKD) is one of the main causes of morbidity and mortality associated with the kidneys in Tunisia. We present here clinical and genetic characteristics of a cohort of Tunisian patients with ADPKD. Nineteen Tunisian patients with ADPKD, among 4 familial cases and 11 sporadic cases, and 50 Healthy individuals were included in this cohort. Genetic studies of PKD1/2 were carried on using Sanger sequencing and MLPA. In our study, the mean age at diagnosis was 47 ± 18 years. In addition, 84.21% of cases present a family history of ADPKD. Overall, 57.89% of the affected individuals had HTA and 26.31% patients had hematuria. 15.78 % of the patient has extra-renal cysts i.e. one patient with splenic cysts and two patients had liver cysts. 57.89 % of patients were diagnosed with various extra-renal clinical presentations i.e. myopia, hernia, deafness, intracranial aneurysm, respiratory distress, hyperthyroidism, urinary tract infection and lower back pains. The PKD1 genotype showed earlier onset of ESRD compared to PKD2 genotype (43 vs. 55 years old). Six mutations have been detected in PKD1 gene. Among them, three were novels e.g. c.688 T>G, p.C230G and c.690C>G, p.C230W among exon 5 and c.8522A>G, p.N2841S among exon 23. In addition, thirteen single nucleotides polymorphisms have been reported in PKD1 gene. Among them, eleven previously reported in heterozygous state and two novel single nucleotides polymorphisms in heterozygous and homozygous state and predicted to be probable polymorphisms by computational tools: c.496C>T, p.L166= among the exon 4, and c.10165G>C and p.E3389Gln among the exon 31. Only three single nucleotides polymorphisms previously reported in ADPKD database have been identified in PKD2 gene. The description and analysis of our cohort can help in rapid and reliable diagnosis for early management of patients in Tunisia. Indeed, predictive genetic testing can facilitate donor evaluation and increase living related kidney transplantation.

Conceptualization of functional single nucleotide polymorphisms of polycystic ovarian syndrome genes: an in silico approach

PURPOSE

Polycystic ovarian syndrome (PCOS) is a multi-faceted endocrinopathy frequently observed in reproductive-aged females, causing infertility. Cumulative evidence revealed that genetic and epigenetic variations, along with environmental factors, were linked with PCOS. Deciphering the molecular pathways of PCOS is quite complicated due to the availability of limited molecular information. Hence, to explore the influence of genetic variations in PCOS, we mapped the GWAS genes and performed a computational analysis to identify the SNPs and their impact on the coding and non-coding sequences.

METHODS

The causative genes of PCOS were searched using the GWAS catalog, and pathway analysis was performed using ClueGO. SNPs were extracted using an Ensembl genome browser, and missense variants were shortlisted. Further, the native and mutant forms of the deleterious SNPs were modeled using I-TASSER, Swiss-PdbViewer, and PyMOL. MirSNP, PolymiRTS, miRNASNP3, and SNP2TFBS, SNPInspector databases were used to find SNPs in the miRNA binding site and transcription factor binding site (TFBS), respectively. EnhancerDB and HaploReg were used to characterize enhancer SNPs. Linkage Disequilibrium (LD) analysis was performed using LDlink.

RESULTS

25 PCOS genes showed interaction with 18 pathways. 7 SNPs were predicted to be deleterious using different pathogenicity predictions. 4 SNPs were found in the miRNA target site, TFBS, and enhancer sites and were in LD with reported PCOS GWAS SNPs.

CONCLUSION

Computational analysis of SNPs residing in PCOS genes may provide insight into complex molecular interactions among genes involved in PCOS pathophysiology. It may also aid in determining the causal variants and consequently contributing to predicting disease strategies.

A comprehensive study on identifying the structural and functional SNPs of human neuronal membrane glycoprotein M6A (GPM6A)

Glycoprotein M6A, a stress related gene, plays an important role in synapse and filopodia formation. Filopodia formation is vital for development, immunity, angiogenesis, wound healing and metastasis. In this study, structural and functional analysis of high-risk SNPs associated with Glycoprotein M6-A were evaluated using six different bioinformatics tools. Results classified T210I, T134I, Y153H, I215T, F156L, T160I, I226T, R247W, R178C, W159R, N157S and P151L as deleterious mutants that are crucial for the structure and function of the protein causing malfunction of M6-a and ultimately leads to disease development. The three-dimensional structure of wild-type M6-a and mutant M6-a were also predicted. Furthermore, the effects of high risk substitutions were also analyzed with interaction with valproic acid. Based on structural models obtained, the binding pocket of ligand bound glycoprotein M6-A structure showed few core interacting residues which are different in the mutant models. Among all substitutions, F156L showed complete loss of binding pocket when interacting with valproic acid as compared to the wild type model. Up to the best of our knowledge this is the first comprehensive study where GPM6A mutations were analyzed. The mechanism of action of GPM6A is still not fully defined which limits the understanding of functional details encoding M6-A. Our results may help enlighten some molecular aspects underlying glycoprotein M6-A. Communicated by Ramaswamy H. Sarma.

Screening and insilico analysis of deleterious nsSNPs (missense) in human CSF3 for their effects on protein structure, stability and function

Human granulocyte colony stimulating factor (hG-CSF), known as CSF3, plays an important role in the growth, differentiation, proliferation, survival, and activation of the granulocyte cell lineage such as neutrophils and their precursors. Functional reduction in native CSF3 protein results in reduced proliferation and activation of neutrophils and leads to neutropenia. Single nucleotide polymorphisms (SNPs) in the CSF3 gene may have deleterious effects on the CSF3 protein function. This study was undertaken to find the functional SNPs in the human CSF3 gene. Results suggest that 18.9% of all the SNPs in the dbSNP database for CSF3 gene were present in the coding region. Out of 59 non-synonymous SNPs (nsSNPs), 26 nsSNPs were predicted to be non-tolerable by SIFT whereas 18 and 7 nsSNPs were predicted as probably damaging and possibly damaging, respectively by PolyPhen. Among this 31 nsSNPs, 16 nsSNPs were identified to be potentially deleterious by PANTHER server, and 4 nsSNPs were found to be neutral by PROVEAN. SNPAnalyzer predicted 7 nsSNPs to be neutral phenotype and the remaining 24 nsSNPs to be associated with diseases. Among the predicted nsSNPs, rs144408123, rs144408123, rs145136406, rs145311241, rs373191696, rs762945096, rs763688260, rs767572172, rs775326370, rs777777864, rs777983866, rs781596455, rs139072004, rs757612684, rs772911210, rs139072004, rs746634544, rs749993200, rs763426127, rs772466210 were identified as deleterious and potentially damaging. I-Mutant analysis revealed that th 20 nsSNPs were important for protein stability of CSF3. Therefore, th 20 nsSNPs may be used for the wider population-based genetic studies and also should be taken into account while engineering the recombinant CSF3 protein for clinical use.

Molecular and in-silico analysis of single nucleotide polymorphism targeting human TP53 gene exon 5-8 in Sudanese esophageal cancer patients

Background: The protein product of the normal TP53 gene performs an essential function in cell cycle control and tumor suppression, and the mutation of a TP53 gene is an essential step in the development of many cancers. Despite the reported association of TP53 gene mutations with many human cancers, the comprehensive computational analysis of single nucleotide polymorphisms (SNPs), and their functional impacts, still remains rare. Methods: In this study DNA were extracted from formalin fixed paraffin embedded samples followed by the conventional polymerase chain reaction and DNA sequencing. Computational analysis was performed using different algorithms to screen for deleterious SNPs. Results: The results demonstrate that there are synonymous SNPs (sSNPs) and non-synonymous SNPs (nsSNPs) in the TP53 gene that may be deleterious to p53 structure and function. Additionally, TP53 gene mutations were found in 40% of samples. Six out of ten of TP53 gene mutations occurred in exon 5, two mutation in exon 6 and other two were present in exon 8. Only one SNP in position E298Q was predicted to have a neutral effect and other SNPs were predicted to be disease related according to Mutation Taster software. A total of 37.2% of squamous cell carcinoma (SCC) samples were found to be mutated, 87.5% of them exist in exon 5, 12.5% in exon 6 and 6.3% in exon 8, whereas adenocarcinoma (AC) achieved a higher rate of mutation (57.1%) with 100% exon 5 involvement. Conclusions: Mutation of TP53 exon 5 in esophageal cancer patients were the most frequent. Genomic results have identified a higher TP53 mutation rate in esophageal AC in contrast to SCC.