Exploring the structural and functional effect of pRB by significant nsSNP in the coding region of RB1 gene causing retinoblastoma

In this study,we identified the most deleterious nsSNP in RB1 gene through structural and functional properties of its protein (pRB) and investigated its binding affinity with E2F-2.Out of 956 SNPs,we investigated 12 nsSNPs in coding region in which three of them (SNPids rs3092895,rs3092903 and rs3092905) are commonly found to be damaged by I-Mutant 2.0,SIFT and PolyPhen programs.With this effort,we modeled the mutant pRB proteins based on these deleterious nsSNPs.From a comparison of total energy,stabilizing residues and RMSD of these three mutant proteins with native pRB protein,we identified that the major mutation is from Glutamic acid to Glycine at the residue position of 746 of pRB.Further,we compared the binding efficiency of both native and mutant pRB (E746G) with E2F-2.We found that mutant pRB has less binding affinity with E2F-2 as compared to native type.This is due to sixteen hydrogen bonding and two salt bridges that exist between native type and E2F-2,whereas mutant type makes only thirteen hydrogen bonds and one salt bridge with E2F-2.Based on our investigation,we propose that the SNP with an id rs3092905 could be the most deleterious nsSNP in RB1 gene causing retinoblastoma.     

Effect of deleterious nsSNP on the HER2 receptor based on stability and binding affinity with herceptin: a computational approach

In this study, we identified the most deleterious non-synonymous SNP of ERBB2 (HER2) receptors by its stability and investigated its binding affinity with herceptin. Out of 135 SNPs, 10 are nsSNPs in the coding region, in which one of the nsSNP (SNPid rs4252633) is commonly found to be damaged by I-Mutant 2.0, SIFT and PolyPhen servers. With this effort, we modelled the mutant HER2 protein based on this deleterious nsSNP (rs4252633). The modeled mutant showed less stability than native HER 2 protein, based on both total energy of the mutant and stabilizing residues in the mutant protein. This is due to a deviation between the mutant and the native HER2, having an RMSD of about 2.81 A. Furthermore, we compared the binding efficiency of herceptin with native and mutant HER2 receptors. We found that herceptin has a high binding affinity with mutant HER2 receptor, with a binding energy of -24.40 kcal/mol, as compared to the native type, which has a binding energy of -15.26 kcal/mol due to six-hydrogen bonding and two salt bridges exist between herceptin and the mutant type, whereas the native type establishes four hydrogen bonds and two salt bridges with herceptin. This analysis portrays that mutant type has two additional hydrogen bonds with herceptin compared with the native type. Normal mode analysis also showed that the two amino acids, namely Asp596 and Glu598 of mutant HER2, forming additional hydrogen bonding with herceptin, had a slightly higher flexibility than the native type. Based on our investigations, we propose that SNPid rs4252633 could be the most deleterious nsSNP for HER2 receptor, and that herceptin could be the best drug for mutant compared to the native HER2 target.     

In silico analysis of structural and functional consequences in p16INK4A by deleterious nsSNPs associated CDKN2A gene in malignant melanoma

In this study, we identified the most deleterious nsSNP in CDKN2A gene through structural and functional properties of its protein (p16INK4A) and investigated its binding affinity with cdk6. Out of 118 SNPs, 14 are nsSNPs in the coding region and 17 SNPs were found in the untranslated region (UTR). FastSNP suggested that 7 SNPs in the 5' UTR might change the protein expression levels. Sixty-four percent of nsSNPs are found to be damaged in PolyPhen server among the 14 nsSNPs investigated. With this effort, we modeled the mutant p16INK4A proteins based on these deleterious nsSNPs, out of which three nsSNPs associated p16INK4A had RMSD values of greater than 3.00 A with native protein. From a comparison of total energy of these three mutant proteins, we identified that the major mutation is from Aspartic acid to Tyrosine at the residue position of 84 of p16INK4A. Further, we compared the binding efficiency of both native and mutant p16INK4A with cdk6. We found that mutant p16INK4A has less binding affinity with cdk6 compared to native type. This is due to ten hydrogen bonds and eight salt bridges which exist between the native type and cdk6, whereas the mutant type makes only nine hydrogen bonds and five salt bridges with cdk6. Based on our investigation, we propose that the SNP with the ID rs11552822 could be the most deleterious nsSNP in CDKN2A gene, causing malignant melanoma, as it was well correlated with experimental studies carried out elsewhere.     

Screening and structural evaluation of deleterious Non-Synonymous SNPs of ePHA2 gene involved in susceptibility to cataract formation

Age-related cataract is clinically and genetically heterogeneous disorder affecting the ocular lens, and the leading cause of vision loss and blindness worldwide. Here we screened nonsynonymous single nucleotide polymorphisms (nsSNPs) of a novel gene, EPHA2 responsible for age related cataracts. The SNPs were retrieved from dbSNP. Using I-Mutant, protein stability change was calculated. The potentially functional nsSNPs and their effect on protein was predicted by PolyPhen and SIFT respectively. FASTSNP was used for functional analysis and estimation of risk score. The functional impact on the EPHA2 protein was evaluated by using SWISSPDB viewer and NOMAD-Ref server. Our analysis revealed 16 SNPs as nonsynonymous out of which 6 nsSNPs, namely rs11543934, rs2291806, rs1058371, rs1058370, rs79100278 and rs113882203 were found to be least stable by I-Mutant 2.0 with DDG value of > -1.0. nsSNPs, namely rs35903225, rs2291806, rs1058372, rs1058370, rs79100278 and rs113882203 showed a highly deleterious tolerance index score of 0.00 by SIFT server. Four nsSNPs namely rs11543934, rs2291806, rs1058370 and rs113882203 were found to be probably damaging with PSIC score of ≥ 2. 0 by Polyp hen server. Three nsSNPs namely, rs11543934, rs2291806 and rs1058370 were found to be highly polymorphic with a risk score of 3-4 with a possible effect of Non-conservative change and splicing regulation by FASTSNP. The total energy and RMSD value was higher for the mutant-type structure compared to the native type structure. We concluded that the nsSNP namely rs2291806 as the potential functional polymorphic that is likely to have functional impact on the EPHA2 gene.     

E2F-1 binding affinity for pRb is not the only determinant of the E2F-1 activity

E2F-1 is the major cellular target of pRB and is regulated by pRB during cell proliferation. Interaction between pRB and E2F-1 is dependent on the phosphorylation status of pRB. Despite the fact that E2F-1 and pRB have antagonistic activities when they are overexpressed, the role of the E2F-1-pRB interaction in cell growth largely remains unknown. Ideally, it would be better to study the properties of a pRB mutant that fails to bind to E2F, but retains all other activities. To date, no pRB mutation has been characterized in sufficient detail to show that it specifically eliminates E2F binding but leaves other interactions intact. An alternative approach to this issue is to ask whether mutations that change E2F proteins binding affinity to pRB are sufficient to change cell growth in aspect of cell cycle and tumor formation. Therefore, we used the E2F-1 mutants including E2F-1/S332-7A, E2F-1/S375A, E2F-1/S403A, E2F-1/Y411A and E2F-1/L132Q that have different binding affinities for pRB to better understand the roles of the E2F-1 phosphorylation and E2F-1-pRB interaction in the cell cycle, as well as in transformation and gene expression. Data presented in this study suggests that in vivo phosphorylation at amino acids 332-337, 375 and 403 is important for the E2F-1 and pRB interaction in vivo. However, although E2F-1 mutants 332-7, 375 and 403 showed similar binding affinity to pRB, they showed different characteristics in transformation efficiency, G₀ accumulation, and target gene experiments.     

Computational detection of deleterious SNPs and their effect on sequence and structural level of the <Emphasis Type="Italic">VHL</Emphasis> gene

In this work we have analyzed the genetic variation that can alter the expression and the function of the VHL gene using computational methods. Of 110 single nucleotide polymorphisms (SNPs), 33 were found to be nonsynonymous (nsSNPs) and 23 SNPs were found in untranslated regions. Of the 33 nsSNPs investigated, 36.3% were found to be deleterious by both SIFT and PolyPhen servers. An untranslated region (UTR) resource tool suggested that two SNPs in the 5' UTR region and six SNPs in the 3' UTR region might change the protein expression levels. It was found by both SIFT and PolyPhen servers that a mutation from histidine to arginine at position 115 of the native protein of the VHL gene was most deleterious. A structural analysis of this mutated protein and the native protein was performed and had a root mean square deviation (RMSD) of 2.78 A. Based on this work, we propose that the nsSNP with a SNPid of rs5030812 is an important candidate for the cause of von Hippel-Lindau syndrome via the VHL gene.     

Computational and Structural Investigation of Deleterious Functional SNPs in Breast Cancer BRCA2 Gene

In this work, we have analyzed the genetic variation that can alter the expression and the function in BRCA2 gene using computational methods. Out of the total 534 SNPs, 101 were found to be non synonymous (nsSNPs). Among the 7 SNPs in the untranslated region, 3 SNPs were found in 5′ and 4 SNPs were found in 3′ un-translated regions (UTR). Of the nsSNPs 20.7% were found to be damaging by both SIFT and PolyPhen server among the 101 nsSNPs investigated. UTR resource tool suggested that 2 SNPs in the 5′ UTR region and 4 SNPs in the 3′ UTR regions might change the protein expression levels. The mutation from asparagine to isoleucine at the position 3124 of the native protein of BRCA2 gene was most deleterious by both SIFT and PolyPhen servers. A structural analysis of this mutated protein and the native protein was made which had an RMSD value of 0.301 nm. Based on this work, we proposed that this most deleterious nsSNP with an SNPid rs28897759 is an important candidate for the cause of breast cancer by BRCA2 gene.     

Evidence of colorectal cancer risk associated variant Lys25Ser in the proximity of human bone morphogenetic protein 2

Colorectal cancer (CRC) is the third most prevalent cancer and fourth leading cause of cancer-related deaths globally. It has been shown that the nsSNP variants play an important role in diseases, however it remained unclear how these variants are associated with the disease. Recently, several CRC risk associated SNPs have been discovered, however rs961253 (Lys25Arg at 20p12.3) located in the proximity of bone morphogenetic protein 2 (Bmp2) and fermitin family homolog 1 Fermt1 genes have been reported to be highly associated with the CRC risk. Here we provide evidence for the first time in silico biological functional and structural implications of non-synonymous (nsSNPs) CRC disease-associated variant Lys25Arg via molecular dynamic (MD) simulation. Protein structural analysis was performed with a particular variant allele (A/C, Lys25Arg) and compared with the predicted native protein structure. Our results showed that this nsSNP will cause changes in the protein structure and as a result is associated with the disease. In addition to the native and mutant 3D structures of CRC associated risk allele protein domain (CRAPD), they were also analyzed using solvent accessibility models for further protein stability confirmation. Taken together, this study confirmed that this variant has functional effect and structural impact on the CRAPD and may play an important role in CRC disease progression; hence it could be a reasonable approach for studying the effect of other deleterious variants in future studies.     

Deleterious amino acid polymorphisms in Arabidopsis thaliana and rice

Plant genetic diversity has been mainly investigated with neutral markers, but large-scale DNA sequencing projects now enable the identification and analysis of different classes of genetic polymorphisms, such as non-synonymous single nucleotide polymorphisms (nsSNPs) in protein coding sequences. Using the SIFT and MAPP programs to predict whether nsSNPs are tolerated (i.e., effectively neutral) or deleterious for protein function, genome-wide nsSNP data from Arabidopsis thaliana and rice were analyzed. In both species, about 20% of polymorphic sites with nsSNPs were classified as deleterious; they segregate at lower allele frequencies than tolerated nsSNPs due to purifying selection. Furthermore, A. thaliana accessions from marginal populations show a higher relative proportion of deleterious nsSNPs, which likely reflects differential selection or demographic effects in subpopulations. To evaluate the sensitivity of predictions, genes from model and crop plants with known functional effects of nsSNPs were inferred with the algorithms. The programs predicted about 70% of nsSNPs correctly as tolerated or deleterious, i.e., as having a functional effect. Forward-in-time simulations of bottleneck and domestication models indicated a high power to detect demographic effects on nsSNP frequencies in sufficiently large datasets. The results indicate that nsSNPs are useful markers for analyzing genetic diversity in plant genetic resources and breeding populations to infer natural/artificial selection and genetic drift.     

E1A induces phosphorylation of the retinoblastoma protein independently of direct physical association between the E1A and retinoblastoma products.

We have studied the initial effects of adenovirus E1A expression on the retinoblastoma (RB) gene product in normal quiescent cells. Although binding of the E1A products to pRB could, in theory, make pRB phosphorylation unnecessary for cell cycle progression, we have found that the 12S wild-type E1A product is capable of inducing phosphorylation of pRB in normal quiescent cells. The induction of pRB phosphorylation correlates with E1A-mediated induction of p34cdc2 expression and kinase activity, consistent with the possibility that p34cdc2 is a pRB kinase. Expression of simian virus 40 T antigen induces similar effects. Induction of pRB phosphorylation is independent of the pRB binding activity of the E1A products; E1A domain 2 mutants do not bind detectable levels of pRB but remain competent to induce pRB phosphorylation and to activate cdc2 protein kinase expression and activity. Although the kinetics of induction are slower, domain 2 mutants induce wild-type levels of pRB phosphorylation and host cell DNA synthesis and yet fail to induce cell proliferation. These results imply that direct physical interaction between the RB and E1A products does not play a required role in the early stages of E1A-mediated cell cycle induction and that pRB phosphorylation is not, of itself, sufficient to allow quiescent cells to divide. These results suggest that the E1A products do not need to bind pRB in order to stimulate resting cells to enter the cell cycle. Indeed, a more important role of the RB binding activity of the E1A products may be to prevent dividing cells from returning to G0.     

A novel computational and structural analysis of nsSNPs in CFTR gene

Single Nucleotide Polymorphisms (SNPs) are being intensively studied to understand the biological basis of complex traits and diseases. The Genetics of human phenotype variation could be understood by knowing the functions of SNPs. In this study using computational methods, we analyzed the genetic variations that can alter the expression and function of the CFTR gene responsible candidate for causing cystic fibrosis. We applied an evolutionary perspective to screen the SNPs using a sequence homology-based SIFT tool, which suggested that 17 nsSNPs (44%) were found to be deleterious. The structure-based approach PolyPhen server suggested that 26 nsSNPS (66%) may disrupt protein function and structure. The PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutation that occurred in the native protein coded by CFTR gene, and which is at amino acid position F508C for nsSNP with id (rs1800093). The amino acid residues in the native and mutant modeled protein were further analyzed for solvent accessibility, secondary structure and stabilizing residues to check the stability of the proteins. The SNPs were further subjected to iHAP analysis to identify htSNPs, and we report potential candidates for future studies on CFTR mutations.     

Extrapolating the effect of deleterious nsSNPs in the binding adaptability of flavopiridol with CDK7 protein: a molecular dynamics approach

Background

Recent reports suggest the role of nonsynonymous single nucleotide polymorphisms (nsSNPs) in cyclin-dependent kinase 7 (CDK7) gene associated with defect in the DNA repair mechanism that may contribute to cancer risk. Among the various inhibitors developed so far, flavopiridol proved to be a potential antitumor drug in the phase-III clinical trial for chronic lymphocytic leukemia. Here, we described a theoretical assessment for the discovery of new drugs or drug targets in CDK7 protein owing to the changes caused by deleterious nsSNPs.

Methods

Three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on protein function by SIFT, PolyPhen2, I-Mutant3, PANTHER, SNPs&GO, PhD-SNP, and screening for non-acceptable polymorphisms (SNAP). Furthermore, we analyzed the native and proposed mutant models in atomic level 10 ns simulation using the molecular dynamics (MD) approach. Finally, with the aid of Autodock 4.0 and PatchDock, we analyzed the binding efficacy of flavopiridol with CDK7 protein with respect to the deleterious mutations.

Results

By comparing the results of all seven prediction tools, three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on the protein function. The results of protein stability analysis inferred that I63R and H135R exhibited less deviation in root mean square deviation in comparison with the native and T285M protein. The flexibility of all the three mutant models of CDK7 protein is diverse in comparison with the native protein. Following to that, docking study revealed the change in the active site residues and decrease in the binding affinity of flavopiridol with mutant proteins.

Conclusion

This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. The identification of disease related SNPs by computational methods has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases.

Lay abstract

Cell cycle regulatory protein, CDK7, is linked with DNA repair mechanism which can contribute to cancer risk. The main aim of this study is to extrapolate the relationship between the nsSNPs and their effects in drug-binding capability. In this work, we propose a new methodology which (1) efficiently identified the deleterious nsSNPs that tend to have functional effect on protein function upon mutation by computational tools, (2) analyze d the native protein and proposed mutant models in atomic level using MD approach, and (3) investigated the protein-ligand interactions to analyze the binding ability by docking analysis. This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. Overall, this approach has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases.

     

Computational SNP Analysis: Current Approaches and Future Prospects

The computational approaches in determining disease-associated Non-synonymous single nucleotide polymorphisms (nsSNPs) have evolved very rapidly. Large number of deleterious and disease-associated nsSNP detection tools have been developed in last decade showing high prediction reliability. Despite of all these highly efficient tools, we still lack the accuracy level in determining the genotype–phenotype association of predicted nsSNPs. Furthermore, there are enormous questions that are yet to be computationally compiled before we might talk about the prediction accuracy. Earlier we have incorporated molecular dynamics simulation approaches to foster the accuracy level of computational nsSNP analysis roadmap, which further helped us to determine the changes in the protein phenotype associated with the computationally predicted disease-associated mutation. Here we have discussed on the present scenario of computational nsSNP characterization technique and some of the questions that are crucial for the proper understanding of pathogenicity level for any disease associated mutations.     

Exploration of deleterious single nucleotide polymorphisms in late-onset Alzheimer disease susceptibility genes

Non-synonymous single nucleotide polymorphisms (nsSNPs) are considered as biomarkers to disease susceptibility. In the present study, nsSNPs in CLU, PICALM and BIN1 genes were screened for their functional impact on concerned proteins and their plausible role in Alzheimer disease (AD) susceptibility. Initially, SNPs were retrieved from dbSNP database, followed by identification of potentially deleterious nsSNPs and prediction of their effect on proteins by PolyPhen and SIFT. Protein stability and the probability of mutation occurrence were predicted using I-Mutant and PANTHER respectively. SNPs3D and FASTSNP were used for the functional analysis of nsSNPs. The functional impact on the 3D structure of proteins was evaluated by SWISSPDB viewer and NOMAD-Ref server. On analysis, 3 nsSNPs with IDs rs12800974 (T158P) of PICALM and rs11554585 (R397C) and rs11554585 (N106D) of BIN1 were predicted to be functionally significant with higher scores of I-Mutant, SIFT, PolyPhen, PANTHER, FASTSNP and SNPs3D. The mutant models of these nsSNPs also showed very high energies and RMSD values compared to their native structures. Current study proposes that the three nsSNPs identified in this study constitute a unique resource of potential genetic factors for AD susceptibility.     

Investigating the Function of Three Non-Synonymous SNPs in EGFR Gene: Structural Modelling and Association With Breast Cancer

Non-synonymous single nucleotide polymorphisms (nsSNPs) represent common genomic variations that alter protein sequence and function. Some nsSNPs affecting conserved amino acids have been reported to be associated with cancer susceptibility. Interestingly, Epidermal Growth Factor Receptor (EGFR) is commonly overexpressed and mutated in many cancers. In this study, we investigated the structural effect of three deleterious nsSNPs: rs17337451 (R962G), rs1140476 (R977C) and rs17290699 (H988P) within EGFR using computational tools. The modelled mutant dimers showed less stability than wild type EGFR dimer. Furthermore, we showed the important role of R962 and H988 residues in the EGFR dimer formation. We also report preliminary experimental data for SNP R977C suggesting that the variant C977 might confer greater risk for breast cancer. These results contribute to an improved understanding of the EGFR dimer stability and provide new elements for understanding the relationship between EGFR and cancer.