Computational and structural investigation of deleterious functional SNPs in breast cancer BRCA2 gene.
01 May 2008-Chinese Journal of Biotechnology (Sheng Wu Gong Cheng Xue Bao)-Vol. 24, Iss: 5, pp 851-856
TL;DR: It is proposed that this most deleterious nsSNP with an SNPid rs28897759 is an important candidate for the cause of breast cancer by BRCA2 gene.
About: This article is published in Chinese Journal of Biotechnology.The article was published on 2008-05-01. It has received 39 citations till now. The article focuses on the topics: Untranslated region.
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TL;DR: This study provides a significant insight into the underlying molecular mechanism involved in albinism associated with OCA1A and determines that certain mutations can affect the dynamic properties of protein and can lead to disease conditions.
49 citations
TL;DR: Results show that W239R and W308C variants are likely to be highly deleterious mutations found in the catalytic kinase domain, which may destabilize structure and disrupt the activation of the STK11 protein as well as reduce its catalytic efficiency.
Abstract: Serine-threonine kinase11 (STK11) is a tumor suppressor gene which plays a key role in regulating cell growth and apoptosis. It is widely known as a multitasking kinase and engaged in cell polarity, cell cycle arrest, chromatin remodeling, energy metabolism, and Wnt signaling. The substitutions of single amino acids in highly conserved regions of the STK11 protein are associated with Peutz-Jeghers syndrome (PJS), which is an autosomal dominant inherited disorder. The abnormal function of the STK11 protein is still not well understood. In this study, we classified disease susceptible single nucleotide polymorphisms (SNPs) in STK11 by using different computational algorithms. We identified the deleterious nsSNPs, constructed mutant protein structures, and evaluated the impact of mutation by employing molecular docking and molecular dynamics analysis. Our results show that W239R and W308C variants are likely to be highly deleterious mutations found in the catalytic kinase domain, which may destabilize structure and disrupt the activation of the STK11 protein as well as reduce its catalytic efficiency. The W239R mutant is likely to have a greater impact on destabilizing the protein structure compared to the W308C mutant. In conclusion, these mutants can help to further realize the large pool of disease susceptibilities linked with catalytic kinase domain activation of STK11 and assist to develop an effective drug for associated diseases.
35 citations
TL;DR: The study revealed that P101L and Y346C mutations increased the flexibility and changed the structural dynamics of SKP2 protein, which 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 againstSKP2.
27 citations
TL;DR: In this paper, a review summarizes the interactions between gut microbiota and anticancer therapies, and demonstrates the current strategies for reshaping gut microbiota community, aiming to provide possibilities for finding an alternative approach to lower the damage and improve the efficacy of cancer therapy.
Abstract: In the recent decade, gut microbiota has received growing interest due to its role in human health and disease. On the one hand, by utilizing the signaling pathways of the host and interacting with the immune system, the gut microbiota is able to maintain the homeostasis in human body. This important role is mainly modulated by the composition of microbiota, as a normal microbiota composition is responsible for maintaining the homeostasis of human body, while an altered microbiota profile could contribute to several pathogenic conditions and may further lead to oncogenesis and tumor progression. Moreover, recent insights have especially focused on the important role of gut microbiota in current anticancer therapies, including chemotherapy, radiotherapy, immunotherapy and surgery. Research findings have indicated a bidirectional interplay between gut microbiota and these therapeutic methods, in which the implementation of different therapeutic methods could lead to different alterations in gut microbiota, and the presence of gut microbiota could in turn contribute to different therapeutic responses. As a result, manipulating the gut microbiota to reduce the therapy-induced toxicity may provide an adjuvant therapy to achieve a better therapeutic outcome. Given the complex role of gut microbiota in cancer treatment, this review summarizes the interactions between gut microbiota and anticancer therapies, and demonstrates the current strategies for reshaping gut microbiota community, aiming to provide possibilities for finding an alternative approach to lower the damage and improve the efficacy of cancer therapy.
23 citations
TL;DR: This is the first extensive computational analyses of pentraxin protein family with nsSNPs and will serve as a valuable resource for future population based studies.
Abstract: Pentraxin-3 (PTX-3) protein is an evolutionary conserved protein that acts as a soluble pattern-recognition receptor for pathogens and plays important role in innate immune response. It recognizes various pathogens by interacting with extracellular moieties such as glactomannan of conidia (Aspergillus fumigatus), lipopolysaccharide of Pseudomonas aeruginosa, Streptococcus pneumonia and Salmonella typhimurium. Thus, PTX-3 protein helps to clear these pathogens by activating downstream innate immune process. In this study, computational methods were used to analyze various non-synonymous single nucleotide polymorphisms (nsSNPs) in PTX-3 gene. Three different databases were used to retrieve SNP data sets followed by seven different in silico algorithms to screen nsSNPs in PTX-3 gene. Sequence homology based approach was used to identify nsSNPs. Conservation profile of PTX-3 protein amino acid residues were predicted by ConSurf web server. In total, 10 high-risk nsSNPs were identified in pentraxin-domain of PTX-3 gene. Out of these 10 high-risk nsSNPs, 4 were present in the conserved structural and functional residues of the pentraxin-domain, hence, selected for structural analyses. The results showed alteration in the putative structure of pentraxin-domain. Prediction of protein–protein interactions analysis showed association of PTX-3 protein with C1q component of complement pathway. Different functional and structural residues along with various putative phosphorylation sites and evolutionary relationship were also predicted for PTX-3 protein. This is the first extensive computational analyses of pentraxin protein family with nsSNPs and will serve as a valuable resource for future population based studies.
21 citations
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...So far, 5,000,000 SNPs have been identified in the coding region of human population responsible for genetic variation (Rajasekaran et al., 2008)....
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References
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TL;DR: The dbSNP database is a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, and is integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data.
Abstract: In response to a need for a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, the National Center for Biotechnology Information (NCBI) has established the dbSNP database [S.T.Sherry, M.Ward and K.Sirotkin (1999) Genome Res., 9, 677–679]. Submissions to dbSNP will be integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data. The complete contents of dbSNP are available to the public at website: http://www.ncbi.nlm.nih.gov/SNP. The complete contents of dbSNP can also be downloaded in multiple formats via anonymous FTP at ftp:// ncbi.nlm.nih.gov/snp/.
6,449 citations
TL;DR: SIFT is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study and can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms.
Abstract: Single nucleotide polymorphism (SNP) studies and random mutagenesis projects identify amino acid substitutions in protein-coding regions. Each substitution has the potential to affect protein function. SIFT (Sorting Intolerant From Tolerant) is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study. We have shown that SIFT can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms. SIFT is available at http://blocks.fhcrc.org/sift/SIFT.html.
5,318 citations
TL;DR: The identification of a gene in which six different germline mutations in breast cancer families that are likely to be due to BRCA2 are detected, and results indicate that this is the BRC a2 gene.
Abstract: IN Western Europe and the United States approximately 1 in 12 women develop breast cancer. A small proportion of breast cancer cases, in particular those arising at a young age, are attributable to a highly penetrant, autosomal dominant predisposition to the disease. The breast cancer susceptibility gene, BRCA2, was recently localized to chromosome 13q12-q13. Here we report the identification of a gene in which we have detected six different germline mutations in breast cancer families that are likely to be due to BRCA2. Each mutation causes serious disruption to the open reading frame of the transcriptional unit. The results indicate that this is the BRCA2 gene.
3,333 citations
TL;DR: The lifetime risk of breast cancer appears similar to the risk in BRCA1 carriers, but there was some suggestion of a lower risk in bRCA2 carriers <50 years of age.
Abstract: The contribution of BRCA1 and BRCA2 to inherited breast cancer was assessed by linkage and mutation analysis in 237 families, each with at least four cases of breast cancer, collected by the Breast Cancer Linkage Consortium. Families were included without regard to the occurrence of ovarian or other cancers. Overall, disease was linked to BRCA1 in an estimated 52% of families, to BRCA2 in 32% of families, and to neither gene in 16% (95% confidence interval [CI] 6%-28%), suggesting other predisposition genes. The majority (81%) of the breast-ovarian cancer families were due to BRCA1, with most others (14%) due to BRCA2. Conversely, the majority of families with male and female breast cancer were due to BRCA2 (76%). The largest proportion (67%) of families due to other genes was found in families with four or five cases of female breast cancer only. These estimates were not substantially affected either by changing the assumed penetrance model for BRCA1 or by including or excluding BRCA1 mutation data. Among those families with disease due to BRCA1 that were tested by one of the standard screening methods, mutations were detected in the coding sequence or splice sites in an estimated 63% (95% CI 51%-77%). The estimated sensitivity was identical for direct sequencing and other techniques. The penetrance of BRCA2 was estimated by maximizing the LOD score in BRCA2-mutation families, over all possible penetrance functions. The estimated cumulative risk of breast cancer reached 28% (95% CI 9%-44%) by age 50 years and 84% (95% CI 43%-95%) by age 70 years. The corresponding ovarian cancer risks were 0.4% (95% CI 0%-1%) by age 50 years and 27% (95% CI 0%-47%) by age 70 years. The lifetime risk of breast cancer appears similar to the risk in BRCA1 carriers, but there was some suggestion of a lower risk in BRCA2 carriers <50 years of age.
2,892 citations
TL;DR: A tool that uses sequence homology to predict whether a substitution affects protein function is constructed, which may be used to identify plausible disease candidates among the SNPs that cause missense substitutions.
Abstract: Many missense substitutions are identified in single nucleotide polymorphism (SNP) data and large-scale random mutagenesis projects. Each amino acid substitution potentially affects protein function. We have constructed a tool that uses sequence homology to predict whether a substitution affects protein function. SIFT, which sorts intolerant from tolerant substitutions, classifies substitutions as tolerated or deleterious. A higher proportion of substitutions predicted to be deleterious by SIFT gives an affected phenotype than substitutions predicted to be deleterious by substitution scoring matrices in three test cases. Using SIFT before mutagenesis studies could reduce the number of functional assays required and yield a higher proportion of affected phenotypes. may be used to identify plausible disease candidates among the SNPs that cause missense substitutions.
2,374 citations