Advances and Applications in Bioinformatics and Chemistry最新文献

{"title":"In silico-based vaccine design against Ebola virus glycoprotein.","authors":"Raju Dash,&nbsp;Rasel Das,&nbsp;Md Junaid,&nbsp;Md Forhad Chowdhury Akash,&nbsp;Ashekul Islam,&nbsp;Sm Zahid Hosen","doi":"10.2147/AABC.S115859","DOIUrl":"https://doi.org/10.2147/AABC.S115859","url":null,"abstract":"<p><p>Ebola virus (EBOV) is one of the lethal viruses, causing more than 24 epidemic outbreaks to date. Despite having available molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet for the management and avoidance of EBOV infections in humans. Disclosing this, the present study described an epitope-based peptide vaccine against EBOV, using a combination of B-cell and T-cell epitope predictions, followed by molecular docking and molecular dynamics simulation approach. Here, protein sequences of all glycoproteins of EBOV were collected and examined via in silico methods to determine the most immunogenic protein. From the identified antigenic protein, the peptide region ranging from 186 to 220 and the sequence HKEGAFFLY from the positions of 154-162 were considered the most potential B-cell and T-cell epitopes, correspondingly. Moreover, this peptide (HKEGAFFLY) interacted with HLA-A*32:15 with the highest binding energy and stability, and also a good conservancy of 83.85% with maximum population coverage. The results imply that the designed epitopes could manifest vigorous enduring defensive immunity against EBOV.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"10 ","pages":"11-28"},"PeriodicalIF":0.0,"publicationDate":"2017-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S115859","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34868040","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":"Molecular docking as a popular tool in drug design, an in silico travel.","authors":"Jerome de Ruyck,&nbsp;Guillaume Brysbaert,&nbsp;Ralf Blossey,&nbsp;Marc F Lensink","doi":"10.2147/AABC.S105289","DOIUrl":"https://doi.org/10.2147/AABC.S105289","url":null,"abstract":"<p><p>New molecular modeling approaches, driven by rapidly improving computational platforms, have allowed many success stories for the use of computer-assisted drug design in the discovery of new mechanism-or structure-based drugs. In this overview, we highlight three aspects of the use of molecular docking. First, we discuss the combination of molecular and quantum mechanics to investigate an unusual enzymatic mechanism of a flavoprotein. Second, we present recent advances in anti-infectious agents' synthesis driven by structural insights. At the end, we focus on larger biological complexes made by protein-protein interactions and discuss their relevance in drug design. This review provides information on how these large systems, even in the presence of the solvent, can be investigated with the outlook of drug discovery. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"9 ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2016-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S105289","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34648246","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":"Parallel computing in genomic research: advances and applications.","authors":"Kary Ocaña, Daniel de Oliveira","doi":"10.2147/AABC.S64482","DOIUrl":"https://doi.org/10.2147/AABC.S64482","url":null,"abstract":"<p><p>Today's genomic experiments have to process the so-called \"biological big data\" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"8 ","pages":"23-35"},"PeriodicalIF":0.0,"publicationDate":"2015-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4655901/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140195057","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":"Tools for visualization and analysis of molecular networks, pathways, and -omics data.","authors":"Jose M Villaveces,&nbsp;Prasanna Koti,&nbsp;Bianca H Habermann","doi":"10.2147/AABC.S63534","DOIUrl":"https://doi.org/10.2147/AABC.S63534","url":null,"abstract":"<p><p>Biological pathways have become the standard way to represent the coordinated reactions and actions of a series of molecules in a cell. A series of interconnected pathways is referred to as a biological network, which denotes a more holistic view on the entanglement of cellular reactions. Biological pathways and networks are not only an appropriate approach to visualize molecular reactions. They have also become one leading method in -omics data analysis and visualization. Here, we review a set of pathway and network visualization and analysis methods and take a look at potential future developments in the field. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"8 ","pages":"11-22"},"PeriodicalIF":0.0,"publicationDate":"2015-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S63534","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33275551","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":"Identification and analysis of potential targets in Streptococcus sanguinis using computer aided protein data analysis.","authors":"Md Rabiul Hossain Chowdhury,&nbsp;Md IqbalKaiser Bhuiyan,&nbsp;Ayan Saha,&nbsp;Ivan Mhai Mosleh,&nbsp;Sobuj Mondol,&nbsp;C M Sabbir Ahmed","doi":"10.2147/AABC.S67336","DOIUrl":"https://doi.org/10.2147/AABC.S67336","url":null,"abstract":"<p><strong>Purpose: </strong>Streptococcus sanguinis is a Gram-positive, facultative aerobic bacterium that is a member of the viridans streptococcus group. It is found in human mouths in dental plaque, which accounts for both dental cavities and bacterial endocarditis, and which entails a mortality rate of 25%. Although a range of remedial mediators have been found to control this organism, the effectiveness of agents such as penicillin, amoxicillin, trimethoprim-sulfamethoxazole, and erythromycin, was observed. The emphasis of this investigation was on finding substitute and efficient remedial approaches for the total destruction of this bacterium.</p><p><strong>Materials and methods: </strong>In this computational study, various databases and online software were used to ascertain some specific targets of S. sanguinis. Particularly, the Kyoto Encyclopedia of Genes and Genomes databases were applied to determine human nonhomologous proteins, as well as the metabolic pathways involved with those proteins. Different software such as Phyre2, CastP, DoGSiteScorer, the Protein Function Predictor server, and STRING were utilized to evaluate the probable active drug binding site with its known function and protein-protein interaction.</p><p><strong>Results: </strong>In this study, among 218 essential proteins of this pathogenic bacterium, 81 nonhomologous proteins were accrued, and 15 proteins that are unique in several metabolic pathways of S. sanguinis were isolated through metabolic pathway analysis. Furthermore, four essentially membrane-bound unique proteins that are involved in distinct metabolic pathways were revealed by this research. Active sites and druggable pockets of these selected proteins were investigated with bioinformatic techniques. In addition, this study also mentions the activity of those proteins, as well as their interactions with the other proteins.</p><p><strong>Conclusion: </strong>Our findings helped to identify the type of protein to be considered as an efficient drug target. This study will pave the way for researchers to develop and discover more effective and specific therapeutic agents against S. sanguinis.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"7 ","pages":"45-54"},"PeriodicalIF":0.0,"publicationDate":"2014-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S67336","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32879497","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":"The hemagglutinin of the influenza A(H1N1)pdm09 is mutating towards stability.","authors":"Juan A Castelán-Vega,&nbsp;Anastasia Magaña-Hernández,&nbsp;Alicia Jiménez-Alberto,&nbsp;Rosa María Ribas-Aparicio","doi":"10.2147/AABC.S68934","DOIUrl":"https://doi.org/10.2147/AABC.S68934","url":null,"abstract":"<p><p>The last influenza A pandemic provided an excellent opportunity to study the adaptation of the influenza A(H1N1)pdm09 virus to the human host. Particularly, due to the availability of sequences taken from isolates since the beginning of the pandemic until date, we could monitor amino acid changes that occurred in the hemagglutinin (HA) as the virus spread worldwide and became the dominant H1N1 strain. HA is crucial to viral infection because it binds to sialidated cell-receptors and mediates fusion of cell and viral membranes; because antibodies that bind to HA may block virus entry to the cell, this protein is subjected to high selective pressure. Multiple alignment analysis of sequences of the HA from isolates taken since 2009 to date allowed us to find amino acid changes that were positively selected as the pandemic progressed. We found nine changes that became prevalent: HA1 subunits D104N, K166Q, S188T, S206T, A259T, and K285E; and HA2 subunits E47K, S124N, and E172K. Most of these changes were located in areas involved in inter- and intrachain interactions, while only two (K166Q and S188T) were located in known antigenic sites. We conclude that selective pressure on HA was aimed to improve its functionality and hence virus fitness, rather than at avoidance of immune recognition. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"7 ","pages":"37-44"},"PeriodicalIF":0.0,"publicationDate":"2014-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S68934","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32758358","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":"In silico predictive model to determine vector-mediated transport properties for the blood-brain barrier choline transporter.","authors":"Sergey Shityakov,&nbsp;Carola Förster","doi":"10.2147/AABC.S63749","DOIUrl":"https://doi.org/10.2147/AABC.S63749","url":null,"abstract":"<p><p>The blood-brain barrier choline transporter (BBB-ChT) may have utility as a drug delivery vector to the central nervous system (CNS). We therefore initiated molecular docking studies with the AutoDock and AutoDock Vina (ADVina) algorithms to develop predictive models for compound screening and to identify structural features important for binding to this transporter. The binding energy predictions were highly correlated with r(2) =0.88, F=692.4, standard error of estimate =0.775, and P-value<0.0001 for selected BBB-ChT-active/inactive compounds (n=93). Both programs were able to cluster active (Gibbs free energy of binding <-6.0 kcal*mol(-1)) and inactive (Gibbs free energy of binding >-6.0 kcal*mol(-1)) molecules and dock them significantly better than at random with an area under the curve value of 0.86 and 0.84, respectively. In ranking smaller molecules with few torsional bonds, a size-related bias in scoring producing false-negative outcomes was detected. Finally, important blood-brain barrier parameters, such as the logBBpassive and logBBactive values, were assessed to predict compound transport to the CNS accurately. Knowledge gained from this study is useful to better understand the binding requirements in BBB-ChT, and until such time as its crystal structure becomes available, it may have significant utility in developing a highly predictive model for the rational design of drug-like compounds targeted to the brain. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"7 ","pages":"23-36"},"PeriodicalIF":0.0,"publicationDate":"2014-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S63749","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32662367","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":"Three-dimensional quantitative structure-activity relationship and docking studies in a series of anthocyanin derivatives as cytochrome P450 3A4 inhibitors.","authors":"Sergey Shityakov,&nbsp;István Puskás,&nbsp;Norbert Roewer,&nbsp;Carola Förster,&nbsp;Jens Broscheit","doi":"10.2147/AABC.S56478","DOIUrl":"https://doi.org/10.2147/AABC.S56478","url":null,"abstract":"<p><p>The cytochrome P450 (CYP)3A4 enzyme affects the metabolism of most drug-like substances, and its inhibition may influence drug safety. Modulation of CYP3A4 by flavonoids, such as anthocyanins, has been shown to inhibit the mutagenic activity of mammalian cells. Considering the previous investigations addressing CYP3A4 inhibition by these substances, we studied the three-dimensional quantitative structure-activity relationship (3D-QSAR) in a series of anthocyanin derivatives as CYP3A4 inhibitors. For the training dataset (n=12), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) yielded crossvalidated and non-crossvalidated models with a q (2) of 0.795 (0.687) and r (2) of 0.962 (0.948), respectively. The models were also validated by an external test set of four compounds with r (2) of 0.821 (CoMFA) and r (2) of 0.812 (CoMSIA). The binding affinity modes associated with experimentally derived IC50 (half maximal inhibitory concentration) values were confirmed by molecular docking into the CYP3A4 active site with r (2) of 0.66. The results obtained from this study are useful for a better understanding of the effects of anthocyanin derivatives on inhibition of carcinogen activation and cellular DNA damage. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"7 ","pages":"11-21"},"PeriodicalIF":0.0,"publicationDate":"2014-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S56478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32269605","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":"In silico structure-based screening of versatile P-glycoprotein inhibitors using polynomial empirical scoring functions.","authors":"Sergey Shityakov,&nbsp;Carola Förster","doi":"10.2147/AABC.S56046","DOIUrl":"https://doi.org/10.2147/AABC.S56046","url":null,"abstract":"<p><p>P-glycoprotein (P-gp) is an ATP (adenosine triphosphate)-binding cassette transporter that causes multidrug resistance of various chemotherapeutic substances by active efflux from mammalian cells. P-gp plays a pivotal role in limiting drug absorption and distribution in different organs, including the intestines and brain. Thus, the prediction of P-gp-drug interactions is of vital importance in assessing drug pharmacokinetic and pharmacodynamic properties. To find the strongest P-gp blockers, we performed an in silico structure-based screening of P-gp inhibitor library (1,300 molecules) by the gradient optimization method, using polynomial empirical scoring (POLSCORE) functions. We report a strong correlation (r (2)=0.80, F=16.27, n=6, P<0.0157) of inhibition constants (Kiexp or pKiexp; experimental Ki or negative decimal logarithm of Kiexp) converted from experimental IC50 (half maximal inhibitory concentration) values with POLSCORE-predicted constants (KiPOLSCORE or pKiPOLSCORE), using a linear regression fitting technique. The hydrophobic interactions between P-gp and selected drug substances were detected as the main forces responsible for the inhibition effect. The results showed that this scoring technique might be useful in the virtual screening and filtering of databases of drug-like compounds at the early stage of drug development processes. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"7 ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S56046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32245658","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":"Hypergeometric analysis of tiling-array and sequence data: detection and interpretation of peaks.","authors":"Erdogan Taskesen,&nbsp;Remco Hoogeboezem,&nbsp;Ruud Delwel,&nbsp;Marcel Jt Reinders","doi":"10.2147/AABC.S51271","DOIUrl":"https://doi.org/10.2147/AABC.S51271","url":null,"abstract":"<p><p>Probing protein-deoxyribonucleic acid (DNA) is gaining popularity as it sheds light on molecular mechanisms that regulate the expression of genes. Currently, tiling-arrays and next-generation sequencing technology can be used to measure these interactions. Both methods generate a signal over the genome in which contiguous regions of peaks on the genome represent the presence of an interacting molecule. Many methods do exist to identify functional regions of interest (ROIs) on the genome. However the detection of ROIs are often not an end-point in research questions and it therefore requires data dragging between tools to relate the ROIs to information present in databases, such as gene-ontology, pathway information, or enrichment of certain genomic content. We introduce hypergeometric analysis of tiling-array and sequence data (HATSEQ), a powerful tool that accurately identifies functional ROIs on the genome where a genomic signal significantly deviates from the general genome-wide behavior. HATSEQ also includes a number of built-in post-analyses with which biological meaning can be attached to the detected ROIs in terms of gene pathways and de-novo motif analysis, and provides different visualizations and statistical summaries for the detected ROIs. In addition, HATSEQ has an intuitive graphic user interface that lowers the barrier for researchers to analyze their data without the need of scripting languages. We compared the results of HATSEQ against two other popular chromatin immunoprecipitation sequencing (ChIP-Seq) methods and observed overlap in the detected ROIs but HATSEQ is more specific in delineating the peak boundaries. We also discuss the versatility of HATSEQ by using a Signal Transducer and Activator of Transcription 1 (STAT1) ChIP-Seq data-set, and show that the detected ROIs are highly specific for the expected STAT1 binding motif. HATSEQ is freely available at: http://hema13.erasmusmc.nl/index.php/HATSEQ. </p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"6 ","pages":"55-62"},"PeriodicalIF":0.0,"publicationDate":"2013-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S51271","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31829546","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}