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Journal articles on the topic 'Structural Bioinformatic'

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Author: Grafiati

Published: 9 March 2023

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1

Zok, Tomasz. "BioCommons: a robust java library for RNA structural bioinformatics." Bioinformatics 37, no. 17 (February 3, 2021): 2766–67. http://dx.doi.org/10.1093/bioinformatics/btab069.

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Abstract Motivation Biomolecular structures come in multiple representations and diverse data formats. Their incompatibility with the requirements of data analysis programs significantly hinders the analytics and the creation of new structure-oriented bioinformatic tools. Therefore, the need for robust libraries of data processing functions is still growing. Results BioCommons is an open-source, Java library for structural bioinformatics. It contains many functions working with the 2D and 3D structures of biomolecules, with a particular emphasis on RNA. Availability and implementation The library is available in Maven Central Repository and its source code is hosted on GitHub: https://github.com/tzok/BioCommons Supplementary information Supplementary data are available at Bioinformatics online.

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2

Breiteneder, Heimo, and Clare Mills. "Structural bioinformatic approaches to understand cross-reactivity." Molecular Nutrition & Food Research 50, no. 7 (July 2006): 628–32. http://dx.doi.org/10.1002/mnfr.200500274.

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3

Stan, George, D. Thirumalai, George H. Lorimer, and Bernard R. Brooks. "Annealing function of GroEL: structural and bioinformatic analysis." Biophysical Chemistry 100, no. 1-3 (December 2002): 453–67. http://dx.doi.org/10.1016/s0301-4622(02)00298-3.

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4

Burnim, Audrey, Matthew Spence, Darren Xu, Colin Jackson, and Nozomi Ando. "Structural and bioinformatic analysis of an ancient enzyme family." Acta Crystallographica Section A Foundations and Advances 78, a1 (July 29, 2022): a26. http://dx.doi.org/10.1107/s2053273322099739.

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5

Grahame, Douglas S. A., John H. Dupuis, Brian C. Bryksa, Takuji Tanaka, and Rickey Y. Yada. "Comparative bioinformatic and structural analyses of pepsin and renin." Enzyme and Microbial Technology 141 (November 2020): 109632. http://dx.doi.org/10.1016/j.enzmictec.2020.109632.

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Shi, Li-ying, Mei Li, Xiao-mian Li, Li-jun Yuan, and Qing Wang. "Bioinformatic analysis of structural proteins of paramyxovirus Tianjin strain." Virologica Sinica 23, no. 4 (August 2008): 279–86. http://dx.doi.org/10.1007/s12250-008-2947-6.

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Kantardjieff, Katherine, and Bernhard Rupp. "Structural Bioinformatic Approaches to the Discovery of New Antimycobacterial Drugs." Current Pharmaceutical Design 10, no. 26 (October 1, 2004): 3195–211. http://dx.doi.org/10.2174/1381612043383205.

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Alsop, E., M. Silver, and D. R. Livesay. "Optimized electrostatic surfaces parallel increased thermostability: a structural bioinformatic analysis." Protein Engineering Design and Selection 16, no. 12 (December 1, 2003): 871–74. http://dx.doi.org/10.1093/protein/gzg131.

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9

Allen, C. Leigh, and Andrew M. Gulick. "Structural and bioinformatic characterization of anAcinetobacter baumanniitype II carrier protein." Acta Crystallographica Section D Biological Crystallography 70, no. 6 (May 30, 2014): 1718–25. http://dx.doi.org/10.1107/s1399004714008311.

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Microorganisms produce a variety of natural productsviasecondary metabolic biosynthetic pathways. Two of these types of synthetic systems, the nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs), use large modular enzymes containing multiple catalytic domains in a single protein. These multidomain enzymes use an integrated carrier protein domain to transport the growing, covalently bound natural product to the neighboring catalytic domains for each step in the synthesis. Interestingly, some PKS and NRPS clusters contain free-standing domains that interact intermolecularly with other proteins. Being expressed outside the architecture of a multi-domain protein, these so-called type II proteins present challenges to understand the precise role they play. Additional structures of individual and multi-domain components of the NRPS enzymes will therefore provide a better understanding of the features that govern the domain interactions in these interesting enzyme systems. The high-resolution crystal structure of a free-standing carrier protein fromAcinetobacter baumanniithat belongs to a larger NRPS-containing operon, encoded by the ABBFA_003406–ABBFA_003399 genes ofA. baumanniistrain AB307-0294, that has been implicated inA. baumanniimotility, quorum sensing and biofilm formation, is presented here. Comparison with the closest structural homologs of other carrier proteins identifies the requirements for a conserved glycine residue and additional important sequence and structural requirements within the regions that interact with partner proteins.

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Bae, E., R. M. Bannen, and G. N. Phillips. "Bioinformatic method for protein thermal stabilization by structural entropy optimization." Proceedings of the National Academy of Sciences 105, no. 28 (July 8, 2008): 9594–97. http://dx.doi.org/10.1073/pnas.0800938105.

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Pérez de la Lastra, José Manuel, Patricia Asensio-Calavia, Sergio González-Acosta, Victoria Baca-González, and Antonio Morales-delaNuez. "Bioinformatic Analysis of Genome-Predicted Bat Cathelicidins." Molecules 26, no. 6 (March 23, 2021): 1811. http://dx.doi.org/10.3390/molecules26061811.

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Bats are unique in their potential to serve as reservoir hosts for intracellular pathogens. Recently, the impact of COVID-19 has relegated bats from biomedical darkness to the frontline of public health as bats are the natural reservoir of many viruses, including SARS-Cov-2. Many bat genomes have been sequenced recently, and sequences coding for antimicrobial peptides are available in the public databases. Here we provide a structural analysis of genome-predicted bat cathelicidins as components of their innate immunity. A total of 32 unique protein sequences were retrieved from the NCBI database. Interestingly, some bat species contained more than one cathelicidin. We examined the conserved cysteines within the cathelin-like domain and the peptide portion of each sequence and revealed phylogenetic relationships and structural dissimilarities. The antibacterial, antifungal, and antiviral activity of peptides was examined using bioinformatic tools. The peptides were modeled and subjected to docking analysis with the region binding domain (RBD) region of the SARS-CoV-2 Spike protein. The appearance of multiple forms of cathelicidins verifies the complex microbial challenges encountered by these species. Learning more about antiviral defenses of bats and how they drive virus evolution will help scientists to investigate the function of antimicrobial peptides in these species.

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Hotinger, Julia A., Allison Hannah Gallagher, and Aaron E. May. "Phage-Related Ribosomal Proteases (Prps): Discovery, Bioinformatics, and Structural Analysis." Antibiotics 11, no. 8 (August 16, 2022): 1109. http://dx.doi.org/10.3390/antibiotics11081109.

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Many new antimicrobials are analogs of existing drugs, sharing the same targets and mechanisms of action. New antibiotic targets are critically needed to combat the growing threat of antimicrobial-resistant bacteria. Phage-related ribosomal proteases (Prps) are a recently structurally characterized antibiotic target found in pathogens such as Staphylococcus aureus, Clostridioides difficile, and Streptococcus pneumoniae. These bacteria encode an N-terminal extension on their ribosomal protein L27 that is not present in other bacteria. The cleavage of this N-terminal extension from L27 by Prp is necessary to create a functional ribosome. Thus, Prp inhibition may serve as an alternative to direct binding and inhibition of the ribosome. This bioinformatic and structural analysis covers the discovery, function, and structural characteristics of known Prps. This information will be helpful in future endeavors to design selective therapeutics targeting the Prps of important pathogens.

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Santos-Martin, Carlos, Geqing Wang, Pramod Subedi, Lilian Hor, Makrina Totsika, Jason John Paxman, and Begoña Heras. "Structural bioinformatic analysis of DsbA proteins and their pathogenicity associated substrates." Computational and Structural Biotechnology Journal 19 (2021): 4725–37. http://dx.doi.org/10.1016/j.csbj.2021.08.018.

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NISHI, Hafumi. "Structural and Functional Characteristics of Protein Phosphorylation Revealed by Bioinformatic Approaches." Seibutsu Butsuri 56, no. 4 (2016): 207–11. http://dx.doi.org/10.2142/biophys.56.207.

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Páez-Pérez, Edgar D., Miriam Livier Llamas-García, Claudia G. Benítez-Cardoza, Gabriela M. Montero-Morán, and Samuel Lara-González. "Bioinformatic Analysis and Biophysical Characterization Reveal Structural Disorder in G0S2 Protein." ACS Omega 5, no. 40 (October 5, 2020): 25841–47. http://dx.doi.org/10.1021/acsomega.0c03171.

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Cázares-García, Saila Viridiana, Ma Soledad Vázquez-Garcidueñas, and Gerardo Vázquez-Marrufo. "Structural and Phylogenetic Analysis of Laccases from Trichoderma: A Bioinformatic Approach." PLoS ONE 8, no. 1 (January 31, 2013): e55295. http://dx.doi.org/10.1371/journal.pone.0055295.

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Sosa, Ezequiel J., Germán Burguener, Esteban Lanzarotti, Lucas Defelipe, Leandro Radusky, Agustín M. Pardo, Marcelo Marti, Adrián G. Turjanski, and Darío Fernández Do Porto. "Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens." Nucleic Acids Research 46, no. D1 (November 2, 2017): D413—D418. http://dx.doi.org/10.1093/nar/gkx1015.

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Sosa, E., G. Burguener, A. Pardo, M. Marti, A. Turjanski, and D. A. Fernández Do Porto. "Target-Pathogen: A structural bioinformatic approach to prioritize drug targets in pathogens." International Journal of Infectious Diseases 73 (August 2018): 84. http://dx.doi.org/10.1016/j.ijid.2018.04.3616.

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SONG, JIANGNING, HAO TAN, SARAH E. BOYD, HONGBIN SHEN, KHALID MAHMOOD, GEOFFREY I. WEBB, TATSUYA AKUTSU, JAMES C. WHISSTOCK, and ROBERT N. PIKE. "BIOINFORMATIC APPROACHES FOR PREDICTING SUBSTRATES OF PROTEASES." Journal of Bioinformatics and Computational Biology 09, no. 01 (February 2011): 149–78. http://dx.doi.org/10.1142/s0219720011005288.

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Proteases have central roles in "life and death" processes due to their important ability to catalytically hydrolyze protein substrates, usually altering the function and/or activity of the target in the process. Knowledge of the substrate specificity of a protease should, in theory, dramatically improve the ability to predict target protein substrates. However, experimental identification and characterization of protease substrates is often difficult and time-consuming. Thus solving the "substrate identification" problem is fundamental to both understanding protease biology and the development of therapeutics that target specific protease-regulated pathways. In this context, bioinformatic prediction of protease substrates may provide useful and experimentally testable information about novel potential cleavage sites in candidate substrates. In this article, we provide an overview of recent advances in developing bioinformatic approaches for predicting protease substrate cleavage sites and identifying novel putative substrates. We discuss the advantages and drawbacks of the current methods and detail how more accurate models can be built by deriving multiple sequence and structural features of substrates. We also provide some suggestions about how future studies might further improve the accuracy of protease substrate specificity prediction.

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Schneider, Bohdan, Jiří Černý, Daniel Svozil, Petr Čech, Jean-Christophe Gelly, and Alexandre G. de Brevern. "Bioinformatic analysis of the protein/DNA interface." Nucleic Acids Research 42, no. 5 (December 11, 2013): 3381–94. http://dx.doi.org/10.1093/nar/gkt1273.

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Abstract To investigate the principles driving recognition between proteins and DNA, we analyzed more than thousand crystal structures of protein/DNA complexes. We classified protein and DNA conformations by structural alphabets, protein blocks [de Brevern, Etchebest and Hazout (2000) (Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Prots. Struct. Funct. Genet., 41:271–287)] and dinucleotide conformers [Svozil, Kalina, Omelka and Schneider (2008) (DNA conformations and their sequence preferences. Nucleic Acids Res., 36:3690–3706)], respectively. Assembling the mutually interacting protein blocks and dinucleotide conformers into ‘interaction matrices’ revealed their correlations and conformer preferences at the interface relative to their occurrence outside the interface. The analyzed data demonstrated important differences between complexes of various types of proteins such as transcription factors and nucleases, distinct interaction patterns for the DNA minor groove relative to the major groove and phosphate and importance of water-mediated contacts. Water molecules mediate proportionally the largest number of contacts in the minor groove and form the largest proportion of contacts in complexes of transcription factors. The generally known induction of A-DNA forms by complexation was more accurately attributed to A-like and intermediate A/B conformers rare in naked DNA molecules.

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Adikes, Rebecca C., William C. Unrath, Christopher M. Yengo, and Omar A. Quintero. "Biochemical and bioinformatic analysis of the myosin-XIX motor domain." Cytoskeleton 70, no. 5 (May 2013): 281–95. http://dx.doi.org/10.1002/cm.21110.

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22

Schwarz, Jana Marie, Richard Lüpken, Dominik Seelow, and Birte Kehr. "Novel sequencing technologies and bioinformatic tools for deciphering the non-coding genome." Medizinische Genetik 33, no. 2 (June 1, 2021): 133–45. http://dx.doi.org/10.1515/medgen-2021-2072.

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Abstract High-throughput sequencing techniques have significantly increased the molecular diagnosis rate for patients with monogenic disorders. This is primarily due to a substantially increased identification rate of disease mutations in the coding sequence, primarily SNVs and indels. Further progress is hampered by difficulties in the detection of structural variants and the interpretation of variants outside the coding sequence. In this review, we provide an overview about how novel sequencing techniques and state-of-the-art algorithms can be used to discover small and structural variants across the whole genome and introduce bioinformatic tools for the prediction of effects variants may have in the non-coding part of the genome.

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23

Memon, Abdulrezzak, and Nuriye Meraklı. "Comparative Structural Analysis of Heavy Metal ATPases in Arabidopsis thaliana, Arabidopsis halleri, Brassica rapa, and Brassica juncea." Turkish Journal of Agriculture - Food Science and Technology 10, sp2 (December 30, 2022): 2988–95. http://dx.doi.org/10.24925/turjaf.v10isp2.2988-2995.5692.

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Arabidopsis thaliana has eight genes encoding members of the type P1B heavy metal–transporting ATPase, subfamily of the P-type ATPases. We focused our study on four ATPases, mainly HMA1, HMA2, HMA3, and HMA4, which are closely related and most similar in their sequences. We carried out the bioinformatics analysis of these metal ATPases and obtained their structure in A. thaliana, A. halleri, and the other heavy metal accumulators in Brassica spp. A. thaliana is a model plant for research because of the duplications and other evolutionary events. These evolutionary events provided a chance to elucidate their regulation and function in the cell. All previous bioinformatics analyses have given some information about their structure, but not much work has been done on their structural components and interactome analysis. Experimental determination of 3D structures is essential to understand better these proteins’ function, which is crucial for the proper functioning of all plant cellular processes. Especially, docking sites and domains need to be worked out to understand the role of these transporter proteins and their interaction in plant cells. These bioinformatic analyses will help the researcher understand these ATPases’ role in detoxifying the toxic metals from the cells of accumulator plants. Further research on gene cloning, gene expression, and generating new accumulator plants for phytoremediation is needed to reclamation polluted soils from toxic heavy metals.

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Schiefner, André, Fabian Rodewald, Irmgard Neumaier, and Arne Skerra. "The dimeric crystal structure of the human fertility lipocalin glycodelin reveals a protein scaffold for the presentation of complex glycans." Biochemical Journal 466, no. 1 (February 6, 2015): 95–104. http://dx.doi.org/10.1042/bj20141003.

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Structural study of human glycodelin, which is involved in reproduction, reveals a homodimeric structure ideally suited as scaffold for the presentation of distinct glycans, whereas bioinformatic analysis indicated exclusive occurrence in suborders of primates that have a menstrual cycle.

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Ostuni, Angela, Magnus Monné, Maria Antonietta Crudele, Pier Luigi Cristinziano, Stefano Cecchini, Mario Amati, Jolanda De Vendel, et al. "Design and structural bioinformatic analysis of polypeptide antigens useful for the SRLV serodiagnosis." Journal of Virological Methods 297 (November 2021): 114266. http://dx.doi.org/10.1016/j.jviromet.2021.114266.

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Hynst, Jakub, Karla Plevova, Lenka Radova, Vojtech Bystry, Karol Pal, and Sarka Pospisilova. "Bioinformatic pipelines for whole transcriptome sequencing data exploitation in leukemia patients with complex structural variants." PeerJ 7 (June 12, 2019): e7071. http://dx.doi.org/10.7717/peerj.7071.

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Background Extensive genome rearrangements, known as chromothripsis, have been recently identified in several cancer types. Chromothripsis leads to complex structural variants (cSVs) causing aberrant gene expression and the formation of de novo fusion genes, which can trigger cancer development, or worsen its clinical course. The functional impact of cSVs can be studied at the RNA level using whole transcriptome sequencing (total RNA-Seq). It represents a powerful tool for discovering, profiling, and quantifying changes of gene expression in the overall genomic context. However, bioinformatic analysis of transcriptomic data, especially in cases with cSVs, is a complex and challenging task, and the development of proper bioinformatic tools for transcriptome studies is necessary. Methods We designed a bioinformatic workflow for the analysis of total RNA-Seq data consisting of two separate parts (pipelines): The first pipeline incorporates a statistical solution for differential gene expression analysis in a biologically heterogeneous sample set. We utilized results from transcriptomic arrays which were carried out in parallel to increase the precision of the analysis. The second pipeline is used for the identification of de novo fusion genes. Special attention was given to the filtering of false positives (FPs), which was achieved through consensus fusion calling with several fusion gene callers. We applied the workflow to the data obtained from ten patients with chronic lymphocytic leukemia (CLL) to describe the consequences of their cSVs in detail. The fusion genes identified by our pipeline were correlated with genomic break-points detected by genomic arrays. Results We set up a novel solution for differential gene expression analysis of individual samples and de novo fusion gene detection from total RNA-Seq data. The results of the differential gene expression analysis were concordant with results obtained by transcriptomic arrays, which demonstrates the analytical capabilities of our method. We also showed that the consensus fusion gene detection approach was able to identify true positives (TPs) efficiently. Detected coordinates of fusion gene junctions were in concordance with genomic breakpoints assessed using genomic arrays. Discussion Byapplying our methods to real clinical samples, we proved that our approach for total RNA-Seq data analysis generates results consistent with other genomic analytical techniques. The data obtained by our analyses provided clues for the study of the biological consequences of cSVs with far-reaching implications for clinical outcome and management of cancer patients. The bioinformatic workflow is also widely applicable for addressing other research questions in different contexts, for which transcriptomic data are generated.

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Yamasaki, Satoshi, and Kazuhiko Fukui. "2P266 Tertiary structure prediction of RNA-RNA complex structures using secondary structure information(22A. Bioinformatics: Structural genomics,Poster)." Seibutsu Butsuri 53, supplement1-2 (2013): S203. http://dx.doi.org/10.2142/biophys.53.s203_1.

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Alam, Asrar. "Bioinformatic Identification of Peptidomimetic-Based Inhibitors against Plasmodium falciparum Antigen AMA1." Malaria Research and Treatment 2014 (December 18, 2014): 1–8. http://dx.doi.org/10.1155/2014/642391.

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Plasmodium falciparum apical membrane antigen 1 (PfAMA1) is a valuable vaccine candidate and exported on the merozoite surface at the time of erythrocyte invasion. PfAMA1 interacts with rhoptry neck protein PfRON2, a component of the rhoptry protein complex, which forms the tight junction at the time of invasion. Phage display studies have identified a 15-residue (F1) and a 20-residue (R1) peptide that bind to PfAMA1 and block the invasion of erythrocytes. Cocrystal structures of central region of PfAMA1 containing disulfide-linked clusters (domains I and II) with R1 peptide and a peptide derived from PfRON2 showed strong structural similarity in binding. The peptides bound to a hydrophobic groove surrounded by domain I and II loops. In this study, peptidomimetics based on the crucial PfAMA1-binding residues of PfRON2 peptide have been identified. Top 5 peptidomimetics when checked for their docking on the region of PfAMA1 encompassing the hydrophobic groove were found to dock on the groove. Drug-like molecules having structural similarity to the top 5 peptidomimetics were identified based on their binding ability to PfAMA1 hydrophobic groove in blind docking. These inhibitors provide potential lead compounds, which could be used in the development of antimalarials targeting PfAMA1.

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Valli S, Abiraami, and Mythili T. "BIOINFORMATIC STUDY OF AN ANTITUMOR PROTEIN, AZURIN." Asian Journal of Pharmaceutical and Clinical Research 11, no. 6 (June 7, 2018): 169. http://dx.doi.org/10.22159/ajpcr.2018.v11i6.23339.

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Objective: The main objective of this study is to analyze the structure and function of an antitumor protein, azurin, thereby giving validation to the protein structure and existing physicochemical properties in the anticancer protein which are responsible for the anticancer activity.Methods: Protein sequence analysis was done using Basic Local Alignment Search Tool (BLAST) with ten different randomly selected species of Pseudomonas obtained from GenBank. The physicochemical properties, prediction of secondary structure, identification of motifs and domains, three-dimensional (3-D) structure of the antitumor protein, validation through Ramachandran plot, multiple sequence alignment (MSA), and phylogenetic analysis were studied and functional property was confirmed through in silico docking.Results: The similarity search (BLAST-P analysis) for the primary sequence from GenBank carried out showed 86% similarity to the second sequence, azurin (Pseudomonas nitroreducens). The ProtParam, ExPASy tool server indicated the presence of essential physicochemical properties in azurin. Secondary structure prediction revealed random coil, extended strand, alpha helix, and beta turn. The study on domains indicated the presence of one domain in azurin responsible for the anticancer activity. The 3-D structural analysis revealed azurin as metalloprotein, of length-128, and polymer-1 with α-helices, β-sheets, and β-barrels. The validation carried out through Ramachandran plot showed the presence of two outliers (phi and psi). The biological relationship between the input sequences was studied through MSA and phylogenetic analysis. Further, azurin docked against the target protein (p53 tumor suppressor) showed the maximum binding affinity confirming its functional property of causing apoptosis.Conclusion: All the properties analyzed in the present study revealed that the azurin protein can act as a very good anticancer agent, and through the phylogenetic analysis, it was identified that Pseudomonas nitroreducens was closely related to the test organism Pseudomonas aeruginosa.

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Lupas, Andrei N., and Kristin K. Koretke. "Bioinformatic analysis of ClpS, a protein module involved in prokaryotic and eukaryotic protein degradation." Journal of Structural Biology 141, no. 1 (January 2003): 77–83. http://dx.doi.org/10.1016/s1047-8477(02)00582-8.

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Vyas, Sachin, Maurizio Bettiga, Ulrika Rova, Paul Christakopoulos, Leonidas Matsakas, and Alok Patel. "Structural and Molecular Characterization of Squalene Synthase Belonging to the Marine Thraustochytrid Species Aurantiochytrium limacinum Using Bioinformatics Approach." Marine Drugs 20, no. 3 (February 28, 2022): 180. http://dx.doi.org/10.3390/md20030180.

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The marine microorganisms thraustochytrids have been explored for their potential in the production of various bioactive compounds, such as DHA, carotenoids, and squalene. Squalene is a secondary metabolite of the triterpenoid class and is known for its importance in various industrial applications. The bioinformatic analysis for squalene synthase (SQS) gene (the first key enzyme in the tri-terpenoid synthesis pathway), that is prevailing among thraustochytrids, is poorly investigated. In-silico studies combining sequence alignments and bioinformatic tools helped in the preliminary characterization of squalene synthases found in Aurantiochytrium limacinum. The sequence contained highly conserved regions for SQS found among different species indicated the enzyme had all the regions for its functionality. The signal peptide sequence and transmembrane regions were absent, indicating an important aspect of the subcellular localization. Secondary and 3-D models generated using appropriate templates demonstrated the similarities with SQS of the other species. The 3-D model also provided important insights into possible active, binding, phosphorylation, and glycosylation sites.

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Minocha, Ranjeet, Keith Studley, and Milton H. Saier, Jr. "The Urea Transporter (UT) Family: Bioinformatic Analyses Leading to Structural, Functional, and Evolutionary Predictions." Receptors and Channels 9, no. 6 (January 2003): 345–52. http://dx.doi.org/10.3109/714041015.

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Barone, Amalia, Maria Luisa Chiusano, Maria Raffaella Ercolano, Giovanni Giuliano, Silvana Grandillo, and Luigi Frusciante. "Structural and Functional Genomics of Tomato." International Journal of Plant Genomics 2008 (January 31, 2008): 1–12. http://dx.doi.org/10.1155/2008/820274.

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Tomato (Solanum lycopersicum L.) is the most intensively investigated Solanaceous species both in genetic and genomics studies. It is a diploid species with a haploid set of 12 chromosomes and a small genome (950 Mb). Based on the detailed knowledge on tomato structural genomics, the sequencing of the euchromatic regions started in the year 2005 as a common effort of different countries. The manuscript focuses on markers used for tomato, on mapping efforts mainly based on exploitation of natural biodiversity, and it gives an updated report on the international sequencing activities. The principal tools developed to explore the function of tomato genes are also summarized, including mutagenesis, genetic transformation, and transcriptome analysis. The current progress in bioinformatic strategies available to manage the overwhelming amount of data generated from different tomato “omics” approaches is reported, and emphasis is given to the effort of producing a computational workbench for the analysis of the organization, as well as the functionality and evolution of the Solanaceae family.

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Swietnicki, Wieslaw, and Ron Caspi. "Prediction of Selected Biosynthetic Pathways for the Lipopolysaccharide Components in Porphyromonas gingivalis." Pathogens 10, no. 3 (March 20, 2021): 374. http://dx.doi.org/10.3390/pathogens10030374.

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Porphyromonas gingivalis is an oral human pathogen. The bacterium destroys dental tissue and is a serious health problem worldwide. Experimental data and bioinformatic analysis revealed that the pathogen produces three types of lipopolysaccharides (LPS): normal (O-type), anionic (A-type), and capsular (K-type). The enzymes involved in the production of all three types of lipopolysaccharide have been largely identified for the first two and partially for the third type. In the current work, we use bioinformatics tools to predict biosynthetic pathways for the production of the normal (O-type) lipopolysaccharide in the W50 strain Porphyromonas gingivalis and compare the pathway with other putative pathways in fully sequenced and completed genomes of other pathogenic strains. Selected enzymes from the pathway have been modeled and putative structures are presented. The pathway for the A-type antigen could not be predicted at this time due to two mutually exclusive structures proposed in the literature. The pathway for K-type antigen biosynthesis could not be predicted either due to the lack of structural data for the antigen. However, pathways for the synthesis of lipid A, its core components, and the O-type antigen ligase reaction have been proposed based on a combination of experimental data and bioinformatic analyses. The predicted pathways are compared with known pathways in other systems and discussed. It is the first report in the literature showing, in detail, predicted pathways for the synthesis of selected LPS components for the model W50 strain of P. gingivalis.

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Weber, Christoph, Angela Pickl-Herk, Abdul Ghafoor Khan, Sascha Strauss, Oliviero Carugo, and Dieter Blaas. "Predictive bioinformatic identification of minor receptor group human rhinoviruses." FEBS Letters 583, no. 15 (July 16, 2009): 2547–51. http://dx.doi.org/10.1016/j.febslet.2009.07.015.

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Zhang, Jinghui. "Decoding the Cancer Genome: Insights from Bioinformatic Studies." Blood 124, no. 21 (December 6, 2014): SCI—5—SCI—5. http://dx.doi.org/10.1182/blood.v124.21.sci-5.sci-5.

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The characterization of the landscape of genetic lesions that underlie cancer has been significantly advanced with the recent application of next-generation sequencing (NGS) technology. To define the genomic landscapes of 21 different pediatric cancer subtypes of brain tumors, solid tumors and leukemias, we analyzed >1,000 pediatric cancers and matched control tissue by whole-genome, whole-exome or transcriptome sequencing as part of the St Jude Children’s Research Hospital – Washington University Pediatric Cancer Genome Project (PCGP). Novel bioinformatics methods for integrative analysis of single-nucleotide variation (SNV), small insertion/deletion (indel), copy number alteration (CNA) and structural variation (SV) have been developed to ensure high sensitivity and accuracy, which is critical for the discovery of highly recurrent somatic lesions that have the potential for developing new cancer therapy. For example, our fusion transcript detection method CICERO has played a key role in identifying recurrent kinase fusions in 90% of Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL), a subgroup characterized by a gene expression profile similar to BCR-ABL1-positive ALL. To evaluate whether NGS is able to identify germline and somatic lesions reported by molecular diagnostic assay, we carried out a pilot clinical sequencing study that employed whole-genome, whole-exome and transcriptome sequencing of matched tumor/normal samples from 78 pediatric cancer patients. We implemented an analysis pipeline that integrates the genetic lesions from all three NGS platforms as well as a data portal that supports classification of somatic and germline lesions. We present a comparison of the sensitivity and accuracy of single-platform analysis with that of integrative multi-platform analysis in identifying somatic and germline SNVs/indels, translocation, gene fusion, CNAs, karyotype, and loss of heterozygosity. Our experience provides informative insight for the design of clinical sequencing of pediatric cancer. Disclosures No relevant conflicts of interest to declare.

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Rajczewski, Andrew T., Qiyuan Han, Subina Mehta, Praveen Kumar, Pratik D. Jagtap, Charles G. Knutson, James G. Fox, Natalia Y. Tretyakova, and Timothy J. Griffin. "Quantitative Proteogenomic Characterization of Inflamed Murine Colon Tissue Using an Integrated Discovery, Verification, and Validation Proteogenomic Workflow." Proteomes 10, no. 2 (April 14, 2022): 11. http://dx.doi.org/10.3390/proteomes10020011.

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Chronic inflammation of the colon causes genomic and/or transcriptomic events, which can lead to expression of non-canonical protein sequences contributing to oncogenesis. To better understand these mechanisms, Rag2−/−Il10−/− mice were infected with Helicobacter hepaticus to induce chronic inflammation of the cecum and the colon. Transcriptomic data from harvested proximal colon samples were used to generate a customized FASTA database containing non-canonical protein sequences. Using a proteogenomic approach, mass spectrometry data for proximal colon proteins were searched against this custom FASTA database using the Galaxy for Proteomics (Galaxy-P) platform. In addition to the increased abundance in inflammatory response proteins, we also discovered several non-canonical peptide sequences derived from unique proteoforms. We confirmed the veracity of these novel sequences using an automated bioinformatics verification workflow with targeted MS-based assays for peptide validation. Our bioinformatics discovery workflow identified 235 putative non-canonical peptide sequences, of which 58 were verified with high confidence and 39 were validated in targeted proteomics assays. This study provides insights into challenges faced when identifying non-canonical peptides using a proteogenomics approach and demonstrates an integrated workflow addressing these challenges. Our bioinformatic discovery and verification workflow is publicly available and accessible via the Galaxy platform and should be valuable in non-canonical peptide identification using proteogenomics.

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Suplatov, Dmitry, Evgeny Kirilin, Vakil Takhaveev, and Vytas Švedas. "Zebra: a web server for bioinformatic analysis of diverse protein families." Journal of Biomolecular Structure and Dynamics 32, no. 11 (September 13, 2013): 1752–58. http://dx.doi.org/10.1080/07391102.2013.834514.

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Carrillo-Vazquez, Jonathan P., José Correa-Basurto, Jazmin García-Machorro, Rafael Campos-Rodríguez, Violaine Moreau, Jorge L. Rosas-Trigueros, Cesar A. Reyes-López, Marlon Rojas-López, and Absalom Zamorano-Carrillo. "A continuous peptide epitope reacting with pandemic influenza AH1N1 predicted by bioinformatic approaches." Journal of Molecular Recognition 28, no. 9 (March 18, 2015): 553–64. http://dx.doi.org/10.1002/jmr.2470.

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Danko, Charles G., Vera A. McIlvain, Maochun Qin, Barry E. Knox, and Arkady M. Pertsov. "Bioinformatic identification of novel putative photoreceptor specific cis-elements." BMC Bioinformatics 8, no. 1 (2007): 407. http://dx.doi.org/10.1186/1471-2105-8-407.

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Jambon, Martin, Anne Imberty, Gilbert Deléage, and Christophe Geourjon. "A new bioinformatic approach to detect common 3D sites in protein structures." Proteins: Structure, Function, and Bioinformatics 52, no. 2 (June 3, 2003): 137–45. http://dx.doi.org/10.1002/prot.10339.

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Zarzycki, Jan, Onur Erbilgin, and Cheryl A. Kerfeld. "Bioinformatic Characterization of Glycyl Radical Enzyme-Associated Bacterial Microcompartments." Applied and Environmental Microbiology 81, no. 24 (September 25, 2015): 8315–29. http://dx.doi.org/10.1128/aem.02587-15.

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ABSTRACTBacterial microcompartments (BMCs) are proteinaceous organelles encapsulating enzymes that catalyze sequential reactions of metabolic pathways. BMCs are phylogenetically widespread; however, only a few BMCs have been experimentally characterized. Among them are the carboxysomes and the propanediol- and ethanolamine-utilizing microcompartments, which play diverse metabolic and ecological roles. The substrate of a BMC is defined by its signature enzyme. In catabolic BMCs, this enzyme typically generates an aldehyde. Recently, it was shown that the most prevalent signature enzymes encoded by BMC loci are glycyl radical enzymes, yet little is known about the function of these BMCs. Here we characterize the glycyl radical enzyme-associated microcompartment (GRM) loci using a combination of bioinformatic analyses and active-site and structural modeling to show that the GRMs comprise five subtypes. We predict distinct functions for the GRMs, including the degradation of choline, propanediol, and fuculose phosphate. This is the first family of BMCs for which identification of the signature enzyme is insufficient for predicting function. The distinct GRM functions are also reflected in differences in shell composition and apparently different assembly pathways. The GRMs are the counterparts of the vitamin B12-dependent propanediol- and ethanolamine-utilizing BMCs, which are frequently associated with virulence. This study provides a comprehensive foundation for experimental investigations of the diverse roles of GRMs. Understanding this plasticity of function within a single BMC family, including characterization of differences in permeability and assembly, can inform approaches to BMC bioengineering and the design of therapeutics.

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Ben Halima, Nihed. "New insights into phospholipases in oat (Avena sativa) from bioinformatic analysis." International Journal of Biological Macromolecules 133 (July 2019): 804–10. http://dx.doi.org/10.1016/j.ijbiomac.2019.04.161.

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Bakli, Mahfoud, Noureddine Bouras, Raul Paşcalău, and Laura Șmuleac. "Bioinformatic Characterization of a Kappa-Carrageenase from Pseudomonas fluorescens." Advanced Research in Life Sciences 6, no. 1 (January 1, 2022): 33–39. http://dx.doi.org/10.2478/arls-2022-0036.

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Abstract Kappa-carrageenase (EC 3.2.1.83) is a glycoside hydrolase family 16 (GH16) member that could specifically hydrolyse kappa-carrageenans to kappa-carrageenan oligosaccharides. Kappa-carrageenase enzymes have attracted much interest due to their numerous potential applications in biomedical and physiological fields, bioethanol production, and textile industry. In the present study, physicochemical, secondary structure, structural properties including homology modeling, refinement, and model quality validation, and functional analyses of the kappacarrageenanse from Pseudomonas fluorescens using various bioinformatic tools were conducted. The protein was found to be stable and acidic in nature. Secondary structure prediction revealed that the presence of random coil is more dominated in the protein sequence followed by extended strand, α-helix, and β-turn. Protein-protein interaction prediction revealed ten potential functional partners. This bioinformatic characterization provides for the first time insights into fundamental characteristics of the predicted Kappa-carrageenase of P. fluorescens, which may be useful for elucidating its applications and for further expression and characterization studies.

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Zhang, Linyi, Radka Reifová, Zuzana Halenková, and Zachariah Gompert. "How Important Are Structural Variants for Speciation?" Genes 12, no. 7 (July 17, 2021): 1084. http://dx.doi.org/10.3390/genes12071084.

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Understanding the genetic basis of reproductive isolation is a central issue in the study of speciation. Structural variants (SVs); that is, structural changes in DNA, including inversions, translocations, insertions, deletions, and duplications, are common in a broad range of organisms and have been hypothesized to play a central role in speciation. Recent advances in molecular and statistical methods have identified structural variants, especially inversions, underlying ecologically important traits; thus, suggesting these mutations contribute to adaptation. However, the contribution of structural variants to reproductive isolation between species—and the underlying mechanism by which structural variants most often contribute to speciation—remain unclear. Here, we review (i) different mechanisms by which structural variants can generate or maintain reproductive isolation; (ii) patterns expected with these different mechanisms; and (iii) relevant empirical examples of each. We also summarize the available sequencing and bioinformatic methods to detect structural variants. Lastly, we suggest empirical approaches and new research directions to help obtain a more complete assessment of the role of structural variants in speciation.

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Kovalev, K., D. Volkov, R. Astashkin, A. Alekseev, I. Gushchin, J. M. Haro-Moreno, I. Chizhov, et al. "High-resolution structural insights into the heliorhodopsin family." Proceedings of the National Academy of Sciences 117, no. 8 (February 7, 2020): 4131–41. http://dx.doi.org/10.1073/pnas.1915888117.

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Rhodopsins are the most abundant light-harvesting proteins. A new family of rhodopsins, heliorhodopsins (HeRs), has recently been discovered. Unlike in the known rhodopsins, in HeRs the N termini face the cytoplasm. The function of HeRs remains unknown. We present the structures of the bacterial HeR-48C12 in two states at the resolution of 1.5 Å, which highlight its remarkable difference from all known rhodopsins. The interior of HeR’s extracellular part is completely hydrophobic, while the cytoplasmic part comprises a cavity (Schiff base cavity [SBC]) surrounded by charged amino acids and containing a cluster of water molecules, presumably being a primary proton acceptor from the Schiff base. At acidic pH, a planar triangular molecule (acetate) is present in the SBC. Structure-based bioinformatic analysis identified 10 subfamilies of HeRs, suggesting their diverse biological functions. The structures and available data suggest an enzymatic activity of HeR-48C12 subfamily and their possible involvement in fundamental redox biological processes.

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Diettrich, Jan, Hirokazu Kage, and Markus Nett. "Genomics-inspired discovery of massiliachelin, an agrochelin epimer from Massilia sp. NR 4-1." Beilstein Journal of Organic Chemistry 15 (June 13, 2019): 1298–303. http://dx.doi.org/10.3762/bjoc.15.128.

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A putative siderophore locus was detected in the genome of the violacein-producing bacterium Massilia sp. NR 4-1 and predicted to direct the biosynthesis of a molecule that is structurally related to the thiazoline-containing siderophore micacocidin. In order to track this compound, we analyzed the metabolic profiles of Massilia cultures grown under different iron concentrations. A compound which was found to be predominantly produced under iron deficiency was subsequently isolated. Its structural characterization by spectroscopic and bioinformatic analyses revealed a previously not known diastereomer of the cytotoxic alkaloid agrochelin. The structure of this natural product, which was named massiliachelin, corresponds to the assembly line encoded by the identified siderophore locus.

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Errami, Mounir, Christophe Geourjon, and Gilbert Deléage. "Conservation of Amino Acids into Multiple Alignments Involved in Pairwise Interactions in Three-Dimensional Protein Structures." Journal of Bioinformatics and Computational Biology 01, no. 03 (October 2003): 505–20. http://dx.doi.org/10.1142/s0219720003000228.

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We present an original strategy, that involves a bioinformatic software structure, in order to perform an exhaustive and objective statistical analysis of three-dimensional structures of proteins. We establish the relationship between multiple sequences alignments and various structural features of proteins. We show that amino acids implied in disulfide bonds, salt bridges and hydrophobic interactions are particularly conserved. Effects of identity, global similarity within alignments, and accessibility of interactions have been studied. Furthermore, we point out that the more variable the sequences within a multiple alignment, the more informative the multiple alignment. The results support multiple alignments usefulness for predictions of structural features.

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Ding, Wenping, Yanqun Li, Xinpeng Tian, Min Chen, Zhihui Xiao, Rouwen Chen, Hao Yin, and Si Zhang. "Investigation on Metabolites in Structural Diversity from The Deep-Sea Sediment-Derived Bacterium Agrococcus sp. SCSIO 52902 and Their Biosynthesis." Marine Drugs 20, no. 7 (June 29, 2022): 431. http://dx.doi.org/10.3390/md20070431.

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Deep-sea sediment-derived bacterium may make full use of self-genes to produce more bioactive metabolites to adapt to extreme environment, resulting in the discovery of novel metabolites with unique structures and metabolic mechanisms. In the paper, we systematically investigated the metabolites in structurally diversity and their biosynthesis from the deep-sea sediment-derived bacterium Agrococcus sp. SCSIO 52902 based on OSMAC strategy, Molecular Networking tool, in combination with bioinformatic analysis. As a result, three new compounds and one new natural product, including 3R-OH-1,6-diene-cyclohexylacetic acid (1), linear tetradepsipeptide (2), N1,N5-di-p-(EE)-coumaroyl-N10-acetylspermidine (3) and furan fatty acid (4), together with nineteen known compounds (5–23) were isolated from the ethyl acetate extract of SCSIO 52902. Their structures were elucidated by comprehensive spectroscopic analysis, single-crystal X-ray diffraction, Marfey’s method and chiral-phase HPLC analysis. Bioinformatic analysis revealed that compounds 1, 3, 9 and 13–22 were closely related to the shikimate pathway, and compound 5 was putatively produced by the OSB pathway instead of the PKS pathway. In addition, the result of cytotoxicity assay showed that compound 5 exhibited weak cytotoxic activity against the HL-60 cell line.

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Wicaksono, Adhityo, Viol Dhea Kharisma, and Arli Aditya Parikesit. "New Perspectives on Reverse Translation: Brief History and Updates." Universitas Scientiarum 28, no. 1 (January 15, 2023): 1–20. http://dx.doi.org/10.11144/javeriana.sc281.npor.

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Since the 1950s, reverse translation has been an enigmatic part of Crick’s central dogma of molecular biology. It might be described as the possibility to back-translate information from proteins to nucleic acids (or codons). A few studies have attempted to theorize and/or conduct in vitro experiments to test the likelihood of reverse translation, with ideas often involving the creation of peptide recognition sites that bridge the peptide and the codon. However, due to many constraints including an asymmetrical informational transfer, the stability of protein-peptide bonds, the structural non-uniformity of protein R-groups, and the informational loss in post-translational protein modifications, this concept requires follow-up studies. On the other hand, current bioinformatic tools that rely on computational programs and biological databases represent a growing branch of biology. Bioinformatics-based reverse translationcan utilize codon usage tables to predict codons from their peptide counterparts. In addition, the development of machine learning tools may allow for the exploration of biological reverse translation in vitro. Thus, while in vivo reverse translation appears to be nearly impossible (due to biological complexity), related biological and bioinformatics studies might be useful to understand better thecentral dogma’s informational transfer and to develop more complex biological machinery.

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