Identification and structural characterization of deleterious non-synonymous single nucleotide polymorphisms in the human SKP2 gene

In SCF (Skp, Cullin, F-box) ubiquitin-protein ligase complexes, S-phase kinase 2 (SKP2) is one of the major players of F-box family, that is responsible for the degradation of several important cell regulators and tumor suppressor proteins. Despite of having significant evidence for the role of SKP2 on tumorgenesis, there is a lack of available data regarding the effect of non-synonymous polymorphisms. In this communication, the structural and functional consequences of non-synonymous single nucleotide polymorphisms (nsSNPs) of SKP2 have been reported by employing various computational approaches and molecular dynamics simulation. Initially, several computational tools like SIFT, PolyPhen-2, PredictSNP, I-Mutant 2.0 and ConSurf have been implicated in this study to explore the damaging SNPs. In total of 172 nsSNPs, 5 nsSNPs were identified as deleterious and 3 of them were predicted to be decreased the stability of protein. Guided from ConSurf analysis, P101L (rs761253702) and Y346C (rs755010517) were categorized as the highly conserved and functional disrupting mutations. Therefore, these mutations were subjected to three dimensional model building and molecular dynamics simulation study for the detailed structural consequences upon the mutations. The study revealed that P101L and Y346C mutations increased the flexibility and changed the structural dynamics. As both these mutations are located in the most functional regions of SKP2 protein, these computational insights might be helpful to consider these nsSNPs for wet-lab confirmatory analysis as well as in rationalizing future population based studies and structure based drug design against SKP2.     

Computational analyses prioritize and reveal the deleterious nsSNPs in human angiotensinogen gene

Angiotensinogen (AGT) is a key component of renin-angiotensin-aldosterone system (RAAS), which plays central role in blood pressure homeostasis. Association of AGT polymorphisms have been investigated in different ethnic populations in variety of cardiovascular and non-cardiovascular conditions. In this study, 354 non-synonymous SNPs (nsSNPs) of AGT were evaluated to predict damaging and structurally important variants. Majority of the deleterious nsSNPs occurred in the evolutionary conserved regions. Several of these nsSNPs were found to affect post-translational modifications like methylation, glycosylation, phosphorylation, ubiquitination etc. Structural evaluations predicted 19 variants as destabilizing and some of them were also predicted to destabilize the renin-AGT interaction. Therefore, the present computational investigation predicted pathogenic and functionally important variants of human AGT gene. The study has also shown that AGT deregulation is associated with survival outcome in patients with gastric and breast cancer, using microarray gene expression profile. Furthermore, the computationally screened nsSNPs can be analyzed in population based genotyping studies and may help futuristic drug development in the area of AGT pharmacogenomics.     

A comprehensive in Silico analysis of the functional and structural impact of single nucleotide polymorphisms (SNPs) in the human IL-33 gene

Interleukin 33 (IL-33) is the latest member of the IL-1 cytokine family, which plays both pro - and anti-inflammatory functions. Numerous Single-nucleotide polymorphisms (SNPs) in the IL-33 gene have been recognized to be associated with a vast variety of inflammatory disorders. SNPs associated studies have become a crucial approach in uncovering the genetic background of human diseases. However, distinguishing the functional SNPs in a disease-related gene from a pool of both functional and neutral SNPs is a major challenge and needs multiple experiments of hundreds or thousands of SNPs in candidate genes. This study aimed to identify the possible deleterious SNPs in the IL-33 gene using bioinformatics predictive tools. The nonsynonymous SNPs (nsSNPs) were analyzed by SIFT, PolyPhen, PROVEAN, SNP&GO, MutPred, SNAP, PhD SNP, and I-Mutant tools. The Non-coding SNPs (ncSNPs) were also analyzed by SNPinfo and RegulomeDB tools. In conclusion, our in-silico analysis predicted 5 nsSNPs and 22 ncSNPs as potential candidates in the IL-33 gene for future genetic association studies.     

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.     

Computational analysis for the determination of deleterious nsSNPs in human MTHFD1 gene

Single nucleotide polymorphisms (SNPs) are the most common genetic polymorphisms and play a major role in many inherited diseases. Methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) is one of the enzymes involved in folate metabolism. In the present study, the functional and structural consequences of nsSNPs of human MTHFD1 gene was analyzed using various computational tools like SIFT, PolyPhen2, PANTHER, PROVEAN, SNAP2, nsSNPAnalyzer, PhD-SNP, SNPs&GO, I-Mutant, MuPro, ConSurf, InterPro, NCBI Conserved Domain Search tool, ModPred, SPARKS-X, RAMPAGE, FT Site and PyMol. Out of 327 nsSNPs form human MTHFD1 gene, total 45 SNPs were predicted as functionally most significant SNPs, among which 17 were highly conserved and functional, 17 were highly conserved and structural residues. Among 45 most significant SNPs, 15 were predicted to be involved in post translational modifications. The p.Gly165Arg may interfere in homodimer interface formation. The p.Asn439Lys and p.Asp445Asn may interfere in binding interactions of MTHFD1 protein with cesium cation and potassium. The two SNPs (p.Asp562Gly and p.Gly637Cys) might interfere in interactions of MTHFD1 with ligand.     

In-Silico analysis of missense SNPs in Human HPPD gene associated with Tyrosinemia type III and Hawkinsinuria

HPPD gene codes a dioxygenase enzyme involved in catalysis of different molecules such as tyrosine and phenylalanine by oxidizing them to produce energy. A single change in protein can trigger serious genetic disorders like Tyrosinemia type III and Hawkinsinuria. This study aims to identify the functional missense SNPs of the HPPD gene by using multiple computational tools. All deleterious missense SNPs retrieved from Ensembl and OMIM database were evaluated through six different software. Ultimately, out of 148 missense SNPs, only 27 were confirmed as diseasecausing SNPs by developing a consensus approach. These damaging SNPs were further examined to evaluate their impact on protein stability and energy including their evolutionary conservation. Native and mutated proteins structures were also designed and superimposed by I-TASSER and PyMol respectively. This work results in narrowing down missense SNPs which are still not confirmed experimentally and demands the confirmation by GWAS data. Thus, these missense SNPs could directly or indirectly destabilize the amino acid interactions causing functional deviations of protein.     

Assessment of structurally and functionally high-risk nsSNPs impacts on human bone morphogenetic protein receptor type IA (BMPR1A) by computational approach

BMPR1A (BMP type 1 receptor) is a transmembrane cell-surface receptor also known as ALK3 (activin-like kinases-3) encodes for a type I serine/threonine kinase receptor and a member of the transforming growth-factor β–receptor (TGF-β) super family. The BMPR1A has a significant interaction with BMP-2 for protein activity and also has a low affinity with growth and differentiation factor 5 (GDF5); positively regulates chondrocyte differentiation. The genetic variations can alter the structure and function of the BMPR1A gene that causes several diseases such as juvenile polyposis syndrome or hereditary cancer-predisposing syndrome. The current study was carried out to identify potential deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in BMPR1A by implementing different computational algorithms such as SIFT, PolyPhen2, SNAP2, PROVEAN, PhD-SNP, SNPs&GO, nsSNPAnalyzer, and P-Mut. From 205 nsSNPs in BMPR1A, 7 nsSNPs (C76Y, C124R, C124Y, C376Y, R443C, R480W, and W487R) were predicted as deleterious in 8 prediction algorithms. The Consurf analysis showed that selected 7 nsSNPs were present in the highly conserved regions. Molecular dynamics simulation analysis also performed to explore conformational changes in the variant structure with respect to its native structure. According to the MDS result, all variants flexibility and rigidity were unbalanced, which may alter the structural and functional behavior of the native protein. Although, three nsSNPs i.e., C124R, C376Y, and R443C have already been reported in patients associated with JPS, but their structural and functional molecular studies remain uncharacterized. Therefore, the findings of this study can provide a better understanding of uncharacterized nsSNPS and to find their association with disease susceptibility and also facilitate to the researchers for designing or developing the target dependent drugs.     

Computational prediction of the effects of non-synonymous single nucleotide polymorphisms on the GPI-anchor transamidase subunit GPI8p of Plasmodium falciparum

Drug resistance is increasingly evolving in malaria parasites; hence, it is important to discover and establish alternative drug targets. In this context, GPI-anchor transamidase (GPI-T) is a potential drug target primarily of its crucial role in the development and survival of the parasite in the GPI anchor biosynthesis pathway. The present investigation was undertaken to explore the plausible effects of nsSNP on the structure and functions of GPI-T subunit GPI8p of Plasmodium falciparum. The GPI8p (PF3D7_1128700) was analyzed using various sequence-based and structure-based computational tools such as SIFT, PROVEAN, PredictSNP, SNAP2, I-Mutant, MuPro, ConSurf, NetSurfP, MUSTER, COACH server and STRING server. Of the 34 nsSNPs submitted for functional analysis, 18 nsSNPs (R124 L, N143 K, Y145 F, V157I, T195S, K379E, I392 K, I437 T, Y438H, N439D, Y441H, N442D, N448D, N451D, D457A, D457Y, I458 L and N460 K) were predicted to have deleterious effects on the protein GPI8p. Additionally, I-Mutant 2.0 and MuPro both showed a decrease in stability after mutation as a result of these nsSNPs, suggesting the destabilization of protein. ConSurf findings suggest that most of the regions were highly conserved. In addition, COACH server was used to predict the ligand binding sites. It was found that no mutation was present at the predicted ligand binding site. The results of the STRING database showed that the protein GPI8p interacts with those proteins which either involve the biosynthetic process of attaching GPI anchor to protein or GPI anchor. The present study suggested that the GPI8p could be a novel target for anti-malarial drugs, which provides significant details for further experimentation.     

Haplotyping of putative microRNA-binding sites in the SNAP-25 gene

Synaptosomal-associated protein 25 (SNAP-25) plays a crucial role in exocitosis. Single nucleotide polymorphisms (rs3746544 and rs1051312) in the 3' un-translated region of the SNAP-25 gene have been described to be in association with attention-deficit hyperactivity disorder. As the disease affects millions of children world-wide, understanding the genetic background of attention-deficit hyperactivity disorder is of crucial importance. Efficient and reliable PCR-RFLP protocols were elaborated for the genotyping of the rs3746544 and rs1051312 SNPs employing a high-throughput capillary electrophoresis method for fragment analysis. A novel real-time PCR-based technique was used applying sequence specific TaqMan probes to haplotype the two SNPs, and the G-C haplotype could not be detected in a large Caucasian population (N=1376). These findings have been confirmed by molecular biology tools as well as by the PHASE Bayesian computational approach. In silico analyses have suggested that the two SNPs might alter microRNA binding and thus have an effect on SNAP-25 production. We have demonstrated that this biological information can be revealed only by direct haplotype analysis emphasizing the importance of our novel molecular haplotye analysis protocol. Results of the study of the two SNPs might shed light on the association of SNAP-25 variants and pathological phenotypes at the molecular level.     

In silico explanation for the causalities of deleterious RNF213 SNPs in Moyamoya disease and insulin resistance

Moyamoya disease (MMD), a cerebrovascular disorder caused by the RNF213 gene, is a cerebrovascular, neurological disorder leading to ischemic strokes. Our previous work suggested that RNF213 might be involved in the pro-inflammatory TNFα-mediated insulin-resistance pathway in adipocytes. Insulin resistance can lead to cerebrovascular diseases and ischemic strokes. Though p. R4810 K has been reported as the founder mutation for Asian population with this disease, there are several mutations continuously reported in clinical diagnosis. We are interested to know whether these mutations can modulate insulin resistance. Also, we are intended to understand the causalities of RNF213 and its associated mutations in MMD. For this, we have adopted a computational approach to characterize RNF213 and its naturally occurring SNPs. Clinically reported SNPs and the predicted SNPs were analyzed for their pathogenicity and effect on the biological function of the protein. To increase accuracy, this was performed through three different analysis software (PROVEAN, SIFT, and SNAP2). The mutations that were found to be deleterious in all the three platforms were further analyzed for their effect on the thermal stability of the protein through I-mutant and iStable. It was found that R4810 K and other mutations decreased the thermodynamic stability of the protein. Loss of function of RNF213 was suggested in some reports. Contrary to this, some studies reported a gain of function state due to the R4810K mutation. To understand this we have measured the ligand-binding ability of this mutated protein through COFACTOR and COACH. An increase in ligand binding is always related to the functional stability of a protein. We have observed that the R4810K mutation might increase the iron-binding efficiency of the amino acid residues. This increase in binding was further validated by analyzing the binding efficiencies by docking. Since RNF213 was previously reported as a target for Protein Tyrosine Phosphatase 1B (PTP1B), we have also analyzed whether PTP1B-binding positions are susceptible to mutations. We have re-analyzed our earlier report on the differential expression pattern of RNF213 in cancer and obese samples. We have provided a detailed analysis of the most deleterious SNPs related to RNF213. Also, we provide a prediction for the loss of function and gain of function attributes of RNF213 and its predicted causalities in MMD and insulin resistance.     

Polymorphisms in genes involved in innate immunity and susceptibility to benzene-induced hematotoxicity

Benzene, a recognized hematotoxicant and carcinogen, can damage the human immune system. We studied the association between single nucleotide polymorphisms (SNPs) in genes involved in innate immunity and benzene hematotoxicity in a cross-sectional study of workers exposed to benzene (250 workers and 140 controls). A total of 1,236 tag SNPs in 149 gene regions of six pathways were included in the analysis. Six gene regions were significant for their association with white blood cell (WBC) counts (MBP, VCAM1, ALOX5, MPO, RAC2, and CRP) based on gene-region (P<0.05) and SNP analyses (FDR<0.05). VCAM1 rs3176867, ALOX5 rs7099684, and MPO rs2071409 were the three most significant SNPs. They showed similar effects on WBC subtypes, especially granulocytes, lymphocytes, and monocytes. A 3-SNP block in ALOXE3 (rs7215658, rs9892383, and rs3027208) showed a global association (omnibus P = 0.0008) with WBCs even though the three SNPs were not significant individually. Our study suggests that polymorphisms in innate immunity genes may play a role in benzene-induced hematotoxicity; however, independent replication is necessary.     

Associations between DRDs and schizophrenia in a Korean population: multi-stage association analyses

The dysregulation of the dopaminergic system has been implicated in the pathophysiology of major psychosis, including schizophrenia, with dopamine receptor genes (DRDs) presently targeted as the most promising candidate genes. We investigated DRD1-5 for association with schizophrenia using a multi-stage approach in a Korean sample. One hundred forty-two SNPs in DRD1-5 were selected from the dbSNP, and the associations of each SNP were then screened and typed by MALDI-TOF mass spectrometry using pooled DNA samples from 150 patients with major psychosis and 150 controls. Each of the suggested SNPs was then genotyped and tested for an association within the individual samples comprising each pool. Finally, the positively associated SNPs were genotyped in an extended sample of 270 patients with schizophrenia and 350 controls. Among the 142 SNPs, 88 (62%) SNPs in our Korean population were polymorphic. At the pooling stage, 10 SNPs (DRD1: 2, DRD2: 3, and DRD4: 5) were identified (P<0.05). SNPs rs1799914 of DRD1 (P=0.046) and rs752306 of DRD4 (P=0.017) had significantly different allele frequencies in the individually genotyped samples comprising the pool. In the final stage, with the extended sample, the suggestive association of DRD4 with rs752306 was lost, but the association of DRD1 with rs1799914 gained greater significance (P=0.017). In these large-scale multi-stage analyses, we were able to find a possible association between DRD1 and schizophrenia. These findings suggested the potential contribution of a multi-step strategy for finding genes related to schizophrenia.     

Predicting deleterious non-synonymous single nucleotide polymorphisms in signal peptides based on hybrid sequence attributes

Signal peptides play a crucial role in various biological processes, such as localization of cell surface receptors, translocation of secreted proteins and cell–cell communication. However, the amino acid mutation in signal peptides, also called non-synonymous single nucleotide polymorphisms (nsSNPs or SAPs) may lead to the loss of their functions. In the present study, a computational method was proposed for predicting deleterious nsSNPs in signal peptides based on random forest (RF) by incorporating position specific scoring matrix (PSSM) profile, SignalP score and physicochemical properties. These features were optimized by the maximum relevance minimum redundancy (mRMR) method. Then, a cost matrix was used to minimize the effect of the imbalanced data classification problem that usually occurred in nsSNPs prediction. The method achieved an overall accuracy of 84.5% and the area under the ROC curve (AUC) of 0.822 by Jackknife test, when the optimal subset included 10 features. Furthermore, on the same dataset, we compared our predictor with other existing methods, including R-score-based method and D-score-based methods, and the result of our method was superior to those of the two methods. The satisfactory performance suggests that our method is effective in predicting the deleterious nsSNPs in signal peptides.     

Genetic association of the EGR2 gene with bipolar disorder in Korea

The early growth response gene 2 (EGR2) is located at chromosome 10q21, one of the susceptibility loci in bipolar disorder (BD). EGR2 is involved in cognitive function, myelination, and signal transduction related to neuregulin-ErbB receptor, Bcl-2 family proteins, and brain-derived neurotrophic factor. This study investigated the genetic association of the EGR2 gene with BD and schizophrenia (SPR) in Korea. In 946 subjects (350 healthy controls, 352 patients with BD, and 244 with SPR), nine single nucleotide polymorphisms (SNPs) in the EGR2 gene region were genotyped. Five SNPs showed nominally significant allelic associations with BD (rs2295814, rs61865882, rs10995315, rs2297488, and rs2297489), and the positive associations of all except rs2297488 remained significant after multiple testing correction. Linkage disequilibrium structure analysis revealed two haplotype blocks. Among the common identified haplotypes (frequency > 5%), 'T-G-A-C-T (block 1)' and 'A-A-G-C (block 2)' haplotypes were over-represented, while 'C-G-G-T-T (block 1)' haplotype was under-represented in BD. In contrast, no significant associations were found with SPR. Although an extended analysis with a larger sample size or independent replication is required, these findings suggest a genetic association of EGR2 with BD. Combined with a plausible biological function of EGR2, the EGR2 gene is a possible susceptibility gene in BD.     

Global analysis of single nucleotide polymorphisms in the exons of human deoxyribonuclease I-like 1 and 2 genes

Several SNPs in the deoxyribonuclease I-like 1 (DNase 1L1) and DNase 1L2 were investigated. In the present study, the genotype distributions of three synonymous SNPs (V59V, rs1050095; P67P, rs1130929; A277A, rs17849495) in the DNase 1L1 gene and four non-synonymous SNPs, V122I (rs34952165), Q170H (rs6643670), and D227A (rs5987256) in the DNase 1L1 gene, as well as D197A (rs62621282) in the DNase 1L2 gene were investigated in 13 populations. In all the populations, no variation was found in four SNPs (V59V, Q170H, D227A, and A277A) in DNASE1L1 or in D197A in DNASE1L2. As for V122I, only the German population showed a low degree of polymorphism. The SNP V122I in DNASE1L1 was monoallelic for the G-allele in all of the Asian and African populations examined, with no polymorphism being evident. Since the A-allele in SNP V122I was distributed in only the Caucasian populations, not in the other ethnic groups, it was confirmed that the A-allele in SNP V122I was Caucasian-specific. On the other hand, only P67P in DNASE1L1 was polymorphic among three synonymous SNPs. The effect of nucleotide substitution corresponding to polymorphic SNP P67P on DNase 1L1 activity was examined: the corresponding nucleotide substitution in polymorphic SNP P67P has little effect on the DNase activity.     

Confirmation that SNPs in the high mobility group‐A2 gene (HMGA2) are associated with adult height in the Japanese population; wide‐ranging population survey of height‐related SNPs in HMGA2

Adult height is a highly heritable trait in that multiple genes are involved. Recent genome‐wide association studies have identified a novel single‐nucleotide polymorphism (SNP) rs1042725 in the high mobility group‐A2 gene (HMGA2) and shown it to be associated with human height in Caucasian populations. We performed a replication study to examine the associations between SNPs in HMGA2 and adult height in the Japanese population based on autopsy cases. Although we could not confirm a significant association between rs1042725 in HMGA2 and adult height, another SNP, rs7968902, in the gene achieved significance for its association in the same populations, and the effect was the same as that documented previously. These findings permit us to conclude that the SNPs in HMGA2 are common variants influencing human height across different populations. Moreover, a worldwide population study of these SNPs using 14 different populations including Asians, Africans and Caucasians demonstrated that both haplotypes and genotypes for three height‐related SNPs (rs1042725, rs7968682 and rs7968902) in HMGA2 were distributed in an ethnicity‐dependent manner. This information will be useful for clarifying the genetic basis of human height.     

Direct molecular haplotyping of multiple polymorphisms within exon 4 of the human catechol-O-methyltransferase gene by liquid chromatography–electrospray ionization time-of-flight mass spectrometry

The applicability of ion-pair reversed-phase high-performance liquid chromatography hyphenated to electrospray ionization time-of-flight mass spectrometry (ICEMS) for the haplotyping of five SNPs (rs769223, rs4818, rs4986871, rs8192488, rs4680) located within exon 4 of the human catechol-O-methyltransferase (COMT, EC 2.1.1.6) gene is demonstrated. Two differently sized products of polymerase chain reaction—a 71-bp amplicon partially covering the sequence of a 124-bp amplicon—were used to determine unequivocally the allelic states of the single nucleotide polymorphisms linked on both chromosomes. The two amplicons were co-loaded onto the chromatographic column and simultaneously analyzed within a single gradient run. Using the described strategy, 101 individuals representing an Austrian population sample were typed. The obtained haplotype frequencies will serve as reference values in future association studies to examine the impact of the COMT gene on neuropsychiatric disorders. Additionally, two newly discovered polymorphic sites within the sequence of the COMT gene are described (a synonymous C>T mutation at the third position of the amino acid codon 99 in the soluble COMT protein or 149 in the membrane-bound COMT protein; a non-synonymous G>A substitution at the second position of the amino acid codon 95 in the soluble COMT protein or 145 in the membrane-bound-COMT protein).