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The development of methods to assess the impact of amino acid mutations on human health has become an important goal in biomedical research, due to the growing number of nonsynonymous SNPs identified. Within this context, computational methods constitute a valuable tool, because they can easily process large amounts of mutations and give useful, almost cost-free, information on their pathological character. In this paper we present a computational approach to the prediction of disease-associated amino acid mutations, using only sequence-based information (amino acid properties, evolutionary information, secondary structure and accessibility predictions, and database annotations) and neural networks, as a model building tool. Mutations are predicted to be either pathological or neutral. Our results show that the method has a good overall success rate, 83%, that can reach 95% when trained for specific proteins. The methodology is fast and flexible enough to provide good estimates of the pathological character of large sets of nonsynonymous SNPs, but can also be easily adapted to give more precise predictions for proteins of special biomedical interest. 相似文献
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Hepatitis C virus (HCV) is considered as a foremost cause affecting numerous human liver‐related disorders. An effective immuno‐prophylactic measure (like stable vaccine) is still unavailable for HCV. We perform an in silico analysis of nonstructural protein 5B (NS5B) based CD4 and CD8 epitopes that might be implicated in improvement of treatment strategies for efficient vaccine development programs against HCV. Here, we report on effective utilization of knowledge obtained from multiple sequence alignment and phylogenetic analysis for investigation and evaluation of candidate epitopes that have enormous potential to be used in formulating proficient vaccine, embracing multiple strains prevalent among major geographical locations. Mutational variability data discussed herein focus on discriminating the region under active evolutionary pressure from those having lower mutational potential in existing experimentally verified epitopes, thus, providing a concrete framework for designing an effective peptide‐based vaccine against HCV. Additionally, we measured entropy distribution in NS5B residues and pinpoint the positions in epitopes that are more susceptible to mutations and, thus, account for virus strategy to evade the host immune system. Findings from this study are expected to add more details on the sequence and structural aspects of NS5B protein, ultimately facilitating our understanding about the pathophysiology of HCV and assisting advance studies on the function of NS5B antigen on the epitope level. We also report on the mutational crosstalk between functionally important coevolving residues, using correlated mutation analysis, and identify networks of coupled mutations that represent pathways of allosteric communication inside and among NS5B thumb, finger, and palm domains. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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Casandra Riera Sergio Lois Carmen Domínguez Israel Fernandez‐Cadenas Joan Montaner Victor Rodríguez‐Sureda Xavier de la Cruz 《Proteins》2015,83(1):91-104
Loss‐of‐function mutations of the enzyme alpha‐galactosidase A (GLA) causes Fabry disease (FD), that is a rare and potentially fatal disease. Identification of these pathological mutations by sequencing is important because it allows an early treatment of the disease. However, before taking any treatment decision, if the mutation identified is unknown, we first need to establish if it is pathological or not. General bioinformatic tools (PolyPhen‐2, SIFT, Condel, etc.) can be used for this purpose, but their performance is still limited. Here we present a new tool, specifically derived for the assessment of GLA mutations. We first compared mutations of this enzyme known to cause FD with neutral sequence variants, using several structure and sequence properties. Then, we used these properties to develop a family of prediction methods adapted to different quality requirements. Trained and tested on a set of known Fabry mutations, our methods have a performance (Matthews correlation: 0.56–0.72) comparable or better than that of the more complex method, Polyphen‐2 (Matthews correlation: 0.61), and better than those of SIFT (Matthews correl.: 0.54) and Condel (Matthews correl.: 0.51). This result is validated in an independent set of 65 pathological mutations, for which our method displayed the best success rate (91.0%, 87.7%, and 73.8%, for our method, PolyPhen‐2 and SIFT, respectively). These data confirmed that our specific approach can effectively contribute to the identification of pathological mutations in GLA, and therefore enhance the use of sequence information in the identification of undiagnosed Fabry patients. Proteins 2015; 83:91–104. © 2014 Wiley Periodicals, Inc. 相似文献
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David Dineen Toby J Gibson Kevin Karplus Weizhong Li Rodrigo Lopez Hamish McWilliam Michael Remmert Johannes Söding Julie D Thompson Desmond G Higgins 《Molecular systems biology》2011,7(1)
Multiple sequence alignments are fundamental to many sequence analysis methods. Most alignments are computed using the progressive alignment heuristic. These methods are starting to become a bottleneck in some analysis pipelines when faced with data sets of the size of many thousands of sequences. Some methods allow computation of larger data sets while sacrificing quality, and others produce high‐quality alignments, but scale badly with the number of sequences. In this paper, we describe a new program called Clustal Omega, which can align virtually any number of protein sequences quickly and that delivers accurate alignments. The accuracy of the package on smaller test cases is similar to that of the high‐quality aligners. On larger data sets, Clustal Omega outperforms other packages in terms of execution time and quality. Clustal Omega also has powerful features for adding sequences to and exploiting information in existing alignments, making use of the vast amount of precomputed information in public databases like Pfam. 相似文献
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Hauschild L Pomar C Lovatto PA 《Animal : an international journal of animal bioscience》2010,4(5):714-723
Empirical and factorial methods are currently used to estimate nutrient requirements for domestic animals. The purpose of this study was to estimate the nutrient requirements of a given pig population using the empirical and factorial methods; to establish the relationship between the requirements estimated with these two methods; and to study the limitations of the methods when used to determine the level of a nutrient needed to optimize individual and population responses of growing pigs. A systematic analysis was carried out on optimal lysine-to-net-energy (Lys : NE) ratios estimated by the empirical and factorial methods using a modified InraPorc® growth model. Sixty-eight pigs were individually simulated based on detailed experimental data. In the empirical method, population responses were estimated by feeding pigs with 11 diets of different Lys : NE ratios. Average daily gain and feed conversion ratio were the chosen performance criteria. These variables were combined with economic information to estimate the economic responses. In the factorial method, the Lys : NE ratio for each animal was estimated by model inversion. Optimal Lys : NE ratios estimated for growing pigs (25 to 105 kg) differed between the empirical and the factorial method. When the average pig is taken to represent a population, the factorial method does not permit estimation of the Lys : NE ratio that maximizes the response of heterogeneous populations in a given time or weight interval. Although optimal population responses are obtained by the empirical method, the estimated requirements are fixed and cannot be used for other growth periods or populations. This study demonstrates that the two methods commonly used to estimate nutrient requirements provide different nutrient recommendations and have important limitations that should be considered when the goal is to optimize the response of individuals or pig populations. 相似文献
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Shen WY Lai CM Lai YK Zhang D Zaknich T Sutanto EN Constable IJ Rakoczy PE 《The journal of gene medicine》2003,5(7):576-587
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杜氏肌营养不良症（Duchenne muscular dystrophy,DMD）属于X连锁隐性遗传病.DMD基因是人类最大基因,突变机制复杂.随着分子生物学的研究进展,对DMD的基因和其编码的抗肌萎缩蛋白（dystrophin）及抗肌萎缩蛋白相关蛋白（utrophin）的认识不断深入.本文就DMD的病理学特点,Dys基因结构、表达、功能,DMD突变及其相关检测技术,DMD实验动物模型及相关治疗的研究进展进行综述. 相似文献
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There are more than 40 different forms of inherited lysosomal storage diseases (LSDs) known to occur in humans and the aggregate incidence has been estimated to approach 1 in 7000 live births. Most LSDs are associated with high morbidity and mortality and represent a significant burden on patients, their families, and health care providers. Except for symptomatic therapies, many LSDs remain untreatable, and gene therapy is among the only viable treatment options potentially available. Therapies for some LSDs do exist, or are under evaluation, including heterologous bone marrow transplantation (BMT), enzyme replacement therapy (ERT), and substrate reduction therapy (SRT), but these treatment options are associated with significant concerns, including high morbidity and mortality (BMT), limited positive outcomes (BMT), incomplete response to therapy (BMT, ERT, and SRT), life-long therapy (ERT, SRT), and cost (BMT, ERT, SRT). Gene therapy represents a potential alternative therapy, albeit a therapy with its own attendant concerns. Animal models of LSDs play a critical role in evaluating the efficacy and safety of therapy for many of these conditions. Naturally occurring animal homologs of LSDs have been described in the mouse, rat, dog, cat, guinea pig, emu, quail, goat, cattle, sheep, and pig. In this review we discuss those animal models that have been used in gene therapy experiments and those with promise for future evaluations. 相似文献
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《Addiction biology》2017,22(5):1246-1256
Recent evidence suggests that the trace amine‐associated receptor 1 (TAAR1) plays a pivotal role in the regulation of dopamine (DA) transmission and psychostimulant action. Several selective TAAR1 agonists have previously shown efficacy in models of cocaine addiction. However, the effects of TAAR1 activation on methamphetamine (METH)‐induced behaviours are less well understood, as indeed are the underlying neurochemical mechanisms mediating potential interactions between TAAR1 and METH. Here, in a progressive ratio schedule of reinforcement the partial TAAR1 agonist, RO5263397, reduced the break‐point for METH self‐administration, while significantly increasing responding maintained by food reward. Following self‐administration and extinction training, RO5263397 completely blocked METH‐primed reinstatement of METH seeking. Moreover, when used as a substitute, unlike a low dose of METH, which sustained vigorous responding when substituting for the training dose of METH, RO5263397 was not self‐administered at any dose, thus exhibiting no apparent abuse liability. Fast‐scan cyclic voltammetry experiments showed that RO5263397 prevented METH‐induced DA overflow in slices of the nucleus accumbens, while having no effect on DA transmission in its own right. Collectively, the present observations demonstrate that partial TAAR1 activation decreases the motivation to self‐administer METH, blocks METH‐primed reinstatement of METH seeking and prevents METH‐induced DA elevations in the nucleus accumbens, and strongly support the candidacy of TAAR1‐based medications as potential substitute treatment in METH addiction. 相似文献
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The authors have made a genome-wide analysis of mutations in Src homology 2 (SH2) domains associated with human disease. Disease-causing mutations have been detected in the SH2 domains of cytoplasmic signaling proteins Bruton tyrosine kinase (BTK), SH2D1A, Ras GTPase activating protein (RasGAP), ZAP-70, SHP-2, STAT1, STAT5B, and the p85alpha subunit of the PIP3. Mutations in the BTK, SH2D1A, ZAP70, STAT1, and STAT5B genes have been shown to cause diverse immunodeficiencies, whereas the mutations in RASA1 and PIK3R1 genes lead to basal carcinoma and diabetes, respectively. PTPN11 mutations cause Noonan sydrome and different types of cancer, depending mainly on whether the mutation is inherited or sporadic. We collected and analyzed all known pathogenic mutations affecting human SH2 domains by bioinformatics methods. Among the investigated protein properties are sequence conservation and covariance, structural stability, side chain rotamers, packing effects, surface electrostatics, hydrogen bond formation, accessible surface area, salt bridges, and residue contacts. The majority of the mutations affect positions essential for phosphotyrosine ligand binding and specificity. The structural basis of the SH2 domain diseases was elucidated based on the bioinformatic analysis. 相似文献
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Abstract: The genetic similarity between humans and nonhuman primates makes nonhuman primates uniquely suited as models for genetic research on complex physiological and behavioral phenotypes. By comparison with human subjects, nonhuman primates, like other animal models, have several advantages for these types of studies: 1) constant environmental conditions can be maintained over long periods of time, greatly increasing the power to detect genetic effects; 2) different environmental conditions can be imposed sequentially on individuals to characterize genotype-environment interactions; 3) complex pedigrees that are much more powerful for genetic analysis than typically available human pedigrees can be generated; 4) genetic hypotheses can be tested prospectively by selective matings; and 5) essential invasive and terminal experiments can be conducted. Limitations of genetic research with nonhuman primates include cost and availability. However, the ability to manipulate both genetic and environmental factors in captive primate populations indicates the promise of genetic research with these important animal models for illuminating complex disease processes. The utility of nonhuman primates for biomedical research on human health problems is illustrated by examples concerning the use of baboons in studies of osteoporosis, alcohol metabolism, and lipoproteins. 相似文献
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Introduction: Toxicoproteomics is an emerging area of omics, intended to explore the changes in protein expression and modifications in biological samples exposed to toxicants. The development of techniques that utilize sophisticated instruments in proteomics has facilitated the exploration of a wide-range of protein coverage and assisted the quantitative and qualitative evaluation of protein changes as a result of the toxic effects of toxic substances.
Areas covered: Studies on toxicoproteomics have an immense potential to explore the molecular mechanism of action of a variety of toxic substances through deciphering the proteomic map altered as a result of toxicant exposure. Here, we provide an overview of toxicoproteomic approaches and the current paradigm of toxicoproteomics.
Expert commentary: Research in this area continues to increase our understanding of the role of toxicants in worsening human health and toxicity driven diseases. The progress in toxicoproteomics may realize the development of novel biomarkers, drug targets and personalized medicines by incorporating the advanced proteomic applications in this field. 相似文献
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Brian J. Stucky 《Journal of biomolecular techniques》2012,23(3):90-93
Modern applications of Sanger DNA sequencing often require converting a large number of chromatogram trace files into high-quality DNA sequences for downstream analyses. Relatively few nonproprietary software tools are available to assist with this process. SeqTrace is a new, free, and open-source software application that is designed to automate the entire workflow by facilitating easy batch processing of large numbers of trace files. SeqTrace can identify, align, and compute consensus sequences from matching forward and reverse traces, filter low-quality base calls, and end-trim finished sequences. The software features a graphical interface that includes a full-featured chromatogram viewer and sequence editor. SeqTrace runs on most popular operating systems and is freely available, along with supporting documentation, at http://seqtrace.googlecode.com/. 相似文献
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An n-gram pattern (NP{n,m}) in a protein sequence is a set of n residues and m wildcards in a window of size n+m. Each window of n+m amino acids is associated with a collection of NP{n,m} patterns based on the combinatorics of n+m objects taken m at a time. NP{n,m} patterns that are shared between sequences reflect evolutionary relationships. Recently the authors developed an alignment-independent protein classification algorithm based on shared NP{4,2} patterns that compared favorably to PSI-BLAST. Theoretically, NP{4,2} patterns should also reflect secondary structure propensity since they contain all possible n-grams for 1 < or = n < or = 4 and a window of 6 residues is wide enough to capture periodicities in the 2 < or = n < or = 5 range. This sparked interest in differentiating the information content in NP{4,2} patterns related to evolution from the content related to local propensity. The probability of alpha-, beta-, and coil components was determined for every NP{4,2} pattern over all the chains in the Protein Data Bank (PDB). An algorithm exclusively based on the Z-values of these distributions was developed, which accurately predicted 71-76% of alpha-helical segments and 62-67% of beta-sheets in rigorous jackknife tests. This provided evidence for the strong correlation between NP{4,2} patterns and secondary structure. By grouping PDB chains into subsets with increasing levels of sequence identity, it was also possible to separate the evolutionary and local propensity contributions to the classification process. The results showed that information derived from evolutionary relationships was more important for beta-sheet prediction than alpha-helix prediction. 相似文献
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Jean Armengaud 《Proteomics》2017,17(21)
Vitis vinifera has been an emblematic plant for humans since the Neolithic period. Human civilization has been shaped by its domestication as both its medicinal and nutritional values were exploited. It is now cultivated on all habitable continents, and more than 5000 varieties have been developed. A global passion for the art of wine fuels innovation and a profound desire for knowledge on this plant. The genome sequence of a homozygotic cultivar and several RNA‐seq datasets on other varieties have been released paving the way to gaining further insight into its biology and tailoring improvements to varieties. However, its genome annotation remains unpolished. In this issue of Proteomics, Chapman and Bellgard (Proteomics 2017, 17, 1700197) discuss how proteogenomics can help improve genome annotation. By mining shotgun proteomics data, they defined new protein‐coding genes, refined gene structures, and corrected numerous mRNA splicing events. This stimulating study shows how large international consortia could work together to improve plant and animal genome annotation on a large scale. To achieve this aim, time should be invested to generate comprehensive, high‐quality experimental datasets for a wide range of well‐defined lineages and exploit them with pipelines capable of handling giant datasets. 相似文献