Advances and Applications in Bioinformatics and Chemistry最新文献

{"title":"Role of Shwachman-Bodian-Diamond syndrome protein in translation machinery and cell chemotaxis: a comparative genomics approach.","authors":"Olga Vasieva","doi":"10.2147/AABC.S23510","DOIUrl":"https://doi.org/10.2147/AABC.S23510","url":null,"abstract":"<p><p>Shwachman-Bodian-Diamond syndrome (SBDS) is linked to a mutation in a single gene. The SBDS proinvolved in RNA metabolism and ribosome-associated functions, but SBDS mutation is primarily linked to a defect in polymorphonuclear leukocytes unable to orient correctly in a spatial gradient of chemoattractants. Results of data mining and comparative genomic approaches undertaken in this study suggest that SBDS protein is also linked to tRNA metabolism and translation initiation. Analysis of crosstalk between translation machinery and cytoskeletal dynamics provides new insights into the cellular chemotactic defects caused by SBDS protein malfunction. The proposed functional interactions provide a new approach to exploit potential targets in the treatment and monitoring of this disease.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":" ","pages":"43-50"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S23510","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40121176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Affinity of estrogens for human progesterone receptor A and B monomers and risk of breast cancer: a comparative molecular modeling study.","authors":"Tarique N Hasan,&nbsp;Leena Grace B,&nbsp;Tariq A Masoodi,&nbsp;Gowhar Shafi,&nbsp;Ali A Alshatwi,&nbsp;P Sivashanmugham","doi":"10.2147/AABC.S17371","DOIUrl":"https://doi.org/10.2147/AABC.S17371","url":null,"abstract":"<p><strong>Background: </strong>The human progesterone receptor (hPR) belongs to the steroid receptor family. It may be found as monomers (A and B) and or as a dimer (AB). hPR is regarded as the prognostic biomarker for breast cancer. In a cellular dimer system, AB is the dominant species in most cases. However, when a cell coexpresses all three isoforms of hPR, the complexity of the action of this receptor increases. For example, hPR A suppresses the activity of hPR B, and the ratio of hPR A to hPR B may determine the physiology of a breast tumor. Also, persistent exposure of hPRs to nonendogenous ligands is a common risk factor for breast cancer. Hence we aimed to study progesterone and some nonendogenous ligand interactions with hPRs and their molecular docking.</p><p><strong>Methods and results: </strong>A pool of steroid derivatives, namely, progesterone, cholesterol, testosterone, testolectone, estradiol, estrone, norethindrone, exemestane, and norgestrel, was used for this in silico study. Dockings were performed on AutoDock 4.2. We found that estrogens, including estradiol and estrone, had a higher affinity for hPR A and B monomers in comparison with the dimer, hPR AB, and that of the endogenous progesterone ligand. hPR A had a higher affinity to all the docked ligands than hPR B.</p><p><strong>Conclusion: </strong>This study suggests that the exposure of estrogens to hPR A as well as hPR B, and more particularly to hPR A alone, is a risk factor for breast cancer.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"4 ","pages":"29-36"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S17371","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29996573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LifePrint: a novel k-tuple distance method for construction of phylogenetic trees.","authors":"Fabián Reyes-Prieto,&nbsp;Adda J García-Chéquer,&nbsp;Hueman Jaimes-Díaz,&nbsp;Janet Casique-Almazán,&nbsp;Juana M Espinosa-Lara,&nbsp;Rosaura Palma-Orozco,&nbsp;Alfonso Méndez-Tenorio,&nbsp;Rogelio Maldonado-Rodríguez,&nbsp;Kenneth L Beattie","doi":"10.2147/AABC.S15021","DOIUrl":"https://doi.org/10.2147/AABC.S15021","url":null,"abstract":"<p><strong>Purpose: </strong>Here we describe LifePrint, a sequence alignment-independent k-tuple distance method to estimate relatedness between complete genomes.</p><p><strong>Methods: </strong>We designed a representative sample of all possible DNA tuples of length 9 (9-tuples). The final sample comprises 1878 tuples (called the LifePrint set of 9-tuples; LPS9) that are distinct from each other by at least two internal and noncontiguous nucleotide differences. For validation of our k-tuple distance method, we analyzed several real and simulated viroid genomes. Using different distance metrics, we scrutinized diverse viroid genomes to estimate the k-tuple distances between these genomic sequences. Then we used the estimated genomic k-tuple distances to construct phylogenetic trees using the neighbor-joining algorithm. A comparison of the accuracy of LPS9 and the previously reported 5-tuple method was made using symmetric differences between the trees estimated from each method and a simulated \"true\" phylogenetic tree.</p><p><strong>Results: </strong>The identified optimal search scheme for LPS9 allows only up to two nucleotide differences between each 9-tuple and the scrutinized genome. Similarity search results of simulated viroid genomes indicate that, in most cases, LPS9 is able to detect single-base substitutions between genomes efficiently. Analysis of simulated genomic variants with a high proportion of base substitutions indicates that LPS9 is able to discern relationships between genomic variants with up to 40% of nucleotide substitution.</p><p><strong>Conclusion: </strong>Our LPS9 method generates more accurate phylogenetic reconstructions than the previously proposed 5-tuples strategy. LPS9-reconstructed trees show higher bootstrap proportion values than distance trees derived from the 5-tuple method.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"4 ","pages":"13-27"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S15021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29996572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A kinetic platform for in silico modeling of the metabolic dynamics in Escherichia coli.","authors":"Aditya Barve,&nbsp;Anvita Gupta,&nbsp;Suresh M Solapure,&nbsp;Ansu Kumar,&nbsp;Vasanthi Ramachandran,&nbsp;Kothandaraman Seshadri,&nbsp;Shireen Vali,&nbsp;Santanu Datta","doi":"10.2147/AABC.S14368","DOIUrl":"https://doi.org/10.2147/AABC.S14368","url":null,"abstract":"<p><strong>Background: </strong>A prerequisite for a successful design and discovery of an antibacterial drug is the identification of essential targets as well as potent inhibitors that adversely affect the survival of bacteria. In order to understand how intracellular perturbations occur due to inhibition of essential metabolic pathways, we have built, through the use of ordinary differential equations, a mathematical model of 8 major Escherichia coli pathways.</p><p><strong>Results: </strong>Individual in vitro enzyme kinetic parameters published in the literature were used to build the network of pathways in such a way that the flux distribution matched that reported from whole cells. Gene regulation at the transcription level as well as feedback regulation of enzyme activity was incorporated as reported in the literature. The unknown kinetic parameters were estimated by trial and error through simulations by observing network stability. Metabolites, whose biosynthetic pathways were not represented in this platform, were provided at a fixed concentration. Unutilized products were maintained at a fixed concentration by removing excess quantities from the platform. This approach enabled us to achieve steady state levels of all the metabolites in the cell. The output of various simulations correlated well with those previously published.</p><p><strong>Conclusion: </strong>Such a virtual platform can be exploited for target identification through assessment of their vulnerability, desirable mode of target enzyme inhibition, and metabolite profiling to ascribe mechanism of action following a specific target inhibition. Vulnerability of targets in the biosynthetic pathway of coenzyme A was evaluated using this platform. In addition, we also report the utility of this platform in understanding the impact of a physiologically relevant carbon source, glucose versus acetate, on metabolite profiles of bacterial pathogens.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"3 ","pages":"97-110"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S14368","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29996569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting recurrent aphthous ulceration using genetic algorithms-optimized neural networks.","authors":"Najla S Dar-Odeh,&nbsp;Othman M Alsmadi,&nbsp;Faris Bakri,&nbsp;Zaer Abu-Hammour,&nbsp;Asem A Shehabi,&nbsp;Mahmoud K Al-Omiri,&nbsp;Shatha M K Abu-Hammad,&nbsp;Hamzeh Al-Mashni,&nbsp;Mohammad B Saeed,&nbsp;Wael Muqbil,&nbsp;Osama A Abu-Hammad","doi":"10.2147/aabc.s10177","DOIUrl":"https://doi.org/10.2147/aabc.s10177","url":null,"abstract":"<p><strong>Objective: </strong>To construct and optimize a neural network that is capable of predicting the occurrence of recurrent aphthous ulceration (RAU) based on a set of appropriate input data.</p><p><strong>Participants and methods: </strong>Artificial neural networks (ANN) software employing genetic algorithms to optimize the architecture neural networks was used. Input and output data of 86 participants (predisposing factors and status of the participants with regards to recurrent aphthous ulceration) were used to construct and train the neural networks. The optimized neural networks were then tested using untrained data of a further 10 participants.</p><p><strong>Results: </strong>THE OPTIMIZED NEURAL NETWORK, WHICH PRODUCED THE MOST ACCURATE PREDICTIONS FOR THE PRESENCE OR ABSENCE OF RECURRENT APHTHOUS ULCERATION WAS FOUND TO EMPLOY: gender, hematological (with or without ferritin) and mycological data of the participants, frequency of tooth brushing, and consumption of vegetables and fruits.</p><p><strong>Conclusions: </strong>FACTORS APPEARING TO BE RELATED TO RECURRENT APHTHOUS ULCERATION AND APPROPRIATE FOR USE AS INPUT DATA TO CONSTRUCT ANNS THAT PREDICT RECURRENT APHTHOUS ULCERATION WERE FOUND TO INCLUDE THE FOLLOWING: gender, hemoglobin, serum vitamin B12, serum ferritin, red cell folate, salivary candidal colony count, frequency of tooth brushing, and the number of fruits or vegetables consumed daily.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"3 ","pages":"7-13"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/aabc.s10177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30142069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating affinities of calcium ions to proteins.","authors":"Stefan Franke,&nbsp;Julia Herfurth,&nbsp;Daniel Hoffmann","doi":"10.2147/aabc.s8589","DOIUrl":"https://doi.org/10.2147/aabc.s8589","url":null,"abstract":"<p><p>Ca(2+)-ions have a range of affinities to different proteins, depending on the various functions of these proteins. This makes the determination of Ca(2+)-protein affinities an interesting subject for functional studies. We have investigated the performance of two methods - Fold-X and AutoDock vina - in the prediction of Ca(2+)-protein affinities. Both methods, although based on different energy functions, showed virtually the same correlation with experimental affinities. Guided by insight from experiment, we further derived a simple linear model based on the solvent accessible surface of Ca(2+) that had practically the same performance in terms of absolute errors as the more complex docking methods.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"3 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/aabc.s8589","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30142067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient algorithms for multidimensional global optimization in genetic mapping of complex traits.","authors":"Kajsa Ljungberg,&nbsp;Kateryna Mishchenko,&nbsp;Sverker Holmgren","doi":"10.2147/AABC.S9240","DOIUrl":"https://doi.org/10.2147/AABC.S9240","url":null,"abstract":"<p><p>We present a two-phase strategy for optimizing a multidimensional, nonconvex function arising during genetic mapping of quantitative traits. Such traits are believed to be affected by multiple so called quantitative trait loci (QTL), and searching for d QTL results in a d-dimensional optimization problem with a large number of local optima. We combine the global algorithm DIRECT with a number of local optimization methods that accelerate the final convergence, and adapt the algorithms to problem-specific features. We also improve the evaluation of the QTL mapping objective function to enable exploitation of the smoothness properties of the optimization landscape. Our best two-phase method is demonstrated to be accurate in at least six dimensions and up to ten times faster than currently used QTL mapping algorithms.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"3 ","pages":"75-88"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S9240","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30143031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SNP analysis of follistatin gene associated with polycystic ovarian syndrome.","authors":"Palanisamy Panneerselvam,&nbsp;Kanakarajan Sivakumari,&nbsp;Ponmani Jayaprakash,&nbsp;Ramanathan Srikanth","doi":"10.2147/AABC.S11013","DOIUrl":"https://doi.org/10.2147/AABC.S11013","url":null,"abstract":"<p><p>Follistatin has been reported as a candidate gene for polycystic ovarian syndrome (PCOS) based on linkage and association studies. In this study, investigation of polymorphisms in the FST gene was done to determine if genetic variation is associated with susceptibility to PCOS. The nucleotide sequence of human follistatin and the protein sequence of human follistatin were retrieved from the NCBI database using Entrez. The follistatin protein of human was retrieved from the Swiss-Prot database. There are 344 amino acids and the molecular weight is 38,007 Da. The ProtParam analysis shows that the isoelectric point is 5.53 and the aliphatic index is 61.25. The hydropathicity is -0.490. The domains in FST protein are as follows: Pfam-B 5005 domain from 1 to 92; EGF-like subdomain from 93 to 116; Kazal 1 domain, occurred in three places, namely, 118-164, 192-239, and 270-316. There are 31 single-nucleotide polymorphisms (SNPs) for this gene. Some are nonsynonymous, some occur in the intron region, and some in an untranslated region. Two nonsynonymous SNPs, namely, rs11745088 and rs1127760, were taken for analysis. In the SNP rs11745088, the change is E152Q. Likewise, in rs1127760, the change is C239S. SIFT (Sorting Intolerant from Tolerant) showed positions of amino acids and the single letter code of amino acids that can be tolerated or deleterious for each position. There were six SNP results and each result had links to it. The dbSNP id, primary database id, and the type of mutation whether silent and if occurring in coding region are given as phenotype alterations. The FASTA format of protein was given to the nsSNP Analyzer tool, and the variation E152Q and C239S were given as inputs in the SNP data field. E152Q change was neutral and C239S causes disease. Using PANTHER for evolutionary analysis of coding SNPs, the protein sequence was given as input and analyzed for the E152Q and C239S SNPs for deleterious effect on protein function. The genetic association database results showed that FST gene SNPs are linked to PCOS coming under the disease class of metabolic disorders. The list of intronic and synonymous SNPs, with their nucleotide position, amino acid change information, and dbSNP link, is provided for further analysis.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"3 ","pages":"111-9"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S11013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29996570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An unsupervised strategy for biomedical image segmentation.","authors":"Roberto Rodríguez,&nbsp;Rubén Hernández","doi":"10.2147/AABC.S11918","DOIUrl":"https://doi.org/10.2147/AABC.S11918","url":null,"abstract":"<p><p>Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"3 ","pages":"67-73"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S11918","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30143030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling of thermodynamic and physico-chemical properties of coumarins bioactivity against Candida albicans using a Levenberg-Marquardt neural network.","authors":"Seyyedeh Soghra Mousavi,&nbsp;Hanieh Bokharaie,&nbsp;Shadi Rahimi,&nbsp;Sima Azadi Soror,&nbsp;Mehrdad Hamidi","doi":"10.2147/aabc.s11812","DOIUrl":"https://doi.org/10.2147/aabc.s11812","url":null,"abstract":"<p><p>In recent years, due to vital need for novel fungicidal agents, investigation on natural antifungal resources has been increased. The special features exhibited by neural network classifiers make them suitable for handling complex problems like analyzing different properties of candidate compounds in computer-aided drug design. In this study, by using a Levenberg-Marquardt (LM) neural network (the fastest of the training algorithms), the relation between some important thermodynamic and physico-chemical properties of coumarin compounds and their biological activities (tested against Candida albicans) has been evaluated. A set of already reported antifungal bioactive coumarin and some well-known physical descriptors have been selected and using LM training algorithm the best architecture of neural model has been designed for forecasting the new bioactive compounds.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"3 ","pages":"59-66"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/aabc.s11812","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30143029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}