Evaluación in – silico de la estructura y función de la proteína hipotética B7FQK1 de phaeodactylum tricornutum
| dc.contributor.advisor | Sánchez Calderón, Juan David | |
| dc.contributor.author | Navarro Gómez, Sirlhey | |
| dc.contributor.author | Suárez Gómez, Ana Milena | |
| dc.coverage.spatial | Barranquilla | spa |
| dc.creator.email | navarrogomez09@hotmail.com | spa |
| dc.creator.email | any.suarez1@hotmail.com | spa |
| dc.date.accessioned | 2020-01-22T20:48:52Z | |
| dc.date.available | 2020-01-22T20:48:52Z | |
| dc.date.created | 2019 | |
| dc.description.abstract | Phaeodactylum tricornutum es una diatomea marina objeto de estudio durante los últimos años gracias a sus propiedades biológicas y su potencial biotecnológico. A partir de P. tricornutum se pueden obtener distintos componentes de alto valor como nutracéuticos, biocombustibles, cosméticos, productos farmacéuticos, etc. Esta microalga se encuentra dentro de las principales especies productoras de PUFAs (EPA y DHA), importantes en la industria farmacéutica y alimentaria debido a sus efectos positivos en la salud humana. P. tricornutum posee un genoma de aproximadamente 27. 4 megabases (Mb) y se estima que contiene 10, 402 genes. No obstante, existen regiones génicas con funcionalidad desconocida, lo que genera la necesidad de llevar a cabo análisis bioinformáticos que faciliten la comprensión del flujo de información desde los genes a las estructuras moleculares. Es por esto que, se buscó predecir computacionalmente la estructura de la proteína hipotética B7FQK1 de Phaeodactylum tricornutum y comprobar la función descrita, relacionada con la biosíntesis de ácidos grasos. La investigación se desarrolló en cuatro fases, la primera consistió en la evaluación in – silico de la estructura primaria, utilizando servidores y algoritmos como TMHMM, ConSurf, PROSITE, Pfam y BLAST. Posteriormente, se analizaron las características físico – químicas y perfiles de la secuencia de aminoácidos con las herramientas EXPASY – PROTPARAM y ProtScale respectivamente. En la tercera fase se predijo la estructura secundaria a partir de los resultados obtenidos de los servidores NPS@ y PSIPRED. Por último, se obtuvo la construcción del modelo 3D de la proteína mediante el servidor I – TASSER y se validó con la herramienta STRUCTURE ASSESSMENT de SWISS – MODEL. Se identificó un dominio FA_desaturasa 2 directamente relacionado con la función predicha. Con base en la evaluación computacional, se obtuvo la estructura secundaria y el modelo 3D, este último con un C – score de 1. 75 que indica un modelo de buena calidad. La predicción estructural y funcional de la proteína hipotética B7FQK1 permite profundizar en los conocimientos de las propiedades biológicas de la microalga y contribuye en la optimización de los procesos biotecnológicos. | spa |
| dc.description.abstract | Phaeodactylum tricornutum is a marine diatom that has been studied in recent years due to its biological properties and its biotechnological potential. From P. tricornutum different high value components can be obtained such as nutraceuticals, biofuels, cosmetics, pharmaceutical products, etc. This microalga is among the main producer species of PUFAs (EPA and DHA) important in the pharmaceutical and food industry due to its positive effects on human health. P. tricornutum has its sequenced genome, it has approximately 27.4 megabases (Mb) and it is estimated that it contains 10,402 genes. However, there are gene regions with unknown functionality, which generates the need to carry out bioinformatics analysis that facilitates the understanding of the flow of information from genes to molecular structures. That is why, we sought computationally to predict the structure of the hypothetical protein B7FQK1 of Phaeodactylum tricornutum and verify the function described, related to the biosynthesis of fatty acids. The research was developed in four phases, the first consisted in the in-silico evaluation of the primary structure, using servers and algorithms such as TMHMM, ConSurf, PROSITE, Pfam and BLAST. Subsequently, the physicochemical characteristics and profiles of the amino acids sequence were analyzed with the EXPASY - PROTPARAM and ProtScale tools respectively. In the third phase the secondary structure was predicted from the results obtained from the NPS @ and PSIPRED servers. Finally, the construction of the 3D model of the protein was obtained through the I - TASSER server and validated with the STRUCTURE ASSESSMENT of SWISS - MODEL tool. A FA_desaturase 2 domain directly related to the predicted function was identified. Based on the computational evaluation, the secondary structure and the 3D model were obtained, the latter with a C - score of 1.75 indicating a good quality model. The structural and functional prediction of the hypothetical protein B7FQK1 allows deepening the knowledge of the biological properties of the microalga and contributes in the optimization of biotechnological processes. | Eng |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/10901/17781 | |
| dc.language.iso | spa | spa |
| dc.relation.references | Adl, S. M., Simpson, A. G. B., Farmer, M. A., Andersen, R. A., Anderson, O. R., Barta, J. R., … Taylor, M. F. J. R. (2005). The new higher level classification of eukaryotes with emphasis on the taxonomy of protists. Journal of Eukaryotic Microbiology, 52(5), 399–451. https://doi.org/10.1111/j.15507408.2005.00053.x | spa |
| dc.relation.references | Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D. J. (1990). Basic local alignment search tool. J. Mol. Biol., 215, 403–410 | spa |
| dc.relation.references | Ambati, R. R., Gogisetty, D., Aswathanarayana, R. G., Ravi, S., Bikkina, P. N., Bo, L., & Yuepeng, S. (2018). Industrial potential of carotenoid pigments from microalgae: Current trends and future prospects. Critical Reviews in Food Science and Nutrition, 8398, 1–22. https://doi.org/10.1080/10408398.2018.1432561 | spa |
| dc.relation.references | Atiku, H., Rmsr, M., Aa, A., & Aa, W. (2016). Harvesting of microalgae biomass from the phycoremediation process of greywater. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-016-7456-9 | spa |
| dc.relation.references | Ayodhya D. (2014). Bioremediation of wastewater by using microalgae : an experimental study, (August). | spa |
| dc.relation.references | Baker, D., & Sali, A. (2001). Protein structure prediction and structural genomics. Science, 294(5540), 93–96. https://doi.org/10.1126/science.1065659 | spa |
| dc.relation.references | Baudouin-cornu, P., Schuerer, K., Marlie, P., & Thomas, D. (2004). Intimate Evolution of Proteins, 279(7), 5421–5428. https://doi.org/10.1074/jbc.M306415200 | spa |
| dc.relation.references | Benkert, P., Biasini, M., & Schwede, T. (2011). Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics, 27(3), 343–350. https://doi.org/10.1093/bioinformatics/btq662 | spa |
| dc.relation.references | Bente Edvarsen, Wenche Eikrem, J.C Green, Robert A. Andersen, S. Y. M.-V. S. and L. K. (2000). Phylogenetic reconstructions of the Haptophyta inferred from 18s ribosomal DNA sequences and available morphological data. Phycologia | spa |
| dc.relation.references | Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., … Bourne, P. E. (2000). The Protein Data Bank Helen. Nucleic Acids Research, 28(1), 235–242. https://doi.org/10.1093/nar/28.1.235 | spa |
| dc.relation.references | Borowitzka, M. A. (2013). High-value products from microalgae — their development and commercialisation. https://doi.org/10.1007/s10811-0139983-9 | spa |
| dc.relation.references | Bowler, C., Allen, A. E., Badger, J. H., Grimwood, J., Jabbari, K., Kuo, A., … Grigoriev, I. V. (2008). The Phaeodactylum genome reveals the evolutionary history of diatom genomes. Nature, 456(7219), 239–244. https://doi.org/10.1038/nature07410 | spa |
| dc.relation.references | Bowler, C., Vardi, A., & Allen, A. E. (2010). Oceanographic and Biogeochemical Insights from Diatom Genomes, 333–367. https://doi.org/10.1146/annurevmarine-120308-081051 | spa |
| dc.relation.references | Branco-Vieira, M., San Martin, S., Agurto, C., Freitas, M. A. V., Mata, T. M., Martins, A. A., & Caetano, N. (2018). Biochemical characterization of Phaeodactylum tricornutum for microalgae-based biorefinery. Energy Procedia, 153, 466–470. https://doi.org/10.1016/j.egypro.2018.10.079 | spa |
| dc.relation.references | Brosnan, J. T., & Brosnan, M. E. (2012). Glutamate : a truly functional amino acid. https://doi.org/10.1007/s00726-012-1280-4 | spa |
| dc.relation.references | Bruce, A., Alexander, J., Julian, L., Martin, R., Keith, R., & Peter, W. (2002). Molecular Biology of the Cell (4th editio). New York. | spa |
| dc.relation.references | Cañedo R, & J, A. (2004). Bioinformatica: en busca de los secreos moleculares de la vida, 12, 1–30 | spa |
| dc.relation.references | Canto, R., & Baquero, F. (2008). Antibiotics and antibiotic resistance in water environments, 260–265. https://doi.org/10.1016/j.copbio.2008.05.006 | spa |
| dc.relation.references | Cardozo, K. H. M., Guaratini, T., Barros, M. P., Falcão, V. R., Tonon, A. P., Lopes, N. P., … Pinto, E. (2007). Metabolites from algae with economical impact. Comparative Biochemistry and Physiology - C Toxicology and Pharmacology, 146(1–2 SPEC. ISS.), 60–78. https://doi.org/10.1016/j.cbpc.2006.05.007 | spa |
| dc.relation.references | Chauton, M. S., Reitan, K. I., Norsker, N. H., Tveterås, R., & Kleivdal, H. T. (2015). A techno-economic analysis of industrial production of marine microalgae as a source of EPA and DHA-rich raw material for aquafeed: Research challenges and possibilities. Aquaculture, 436, 95–103. https://doi.org/10.1016/j.aquaculture.2014.10.038 | spa |
| dc.relation.references | Chen, C., & Evans, L. B. (1989). Phase Partitioning of Biomolecules : Solubilities of Amino Acids, 5(3), 111–118. | spa |
| dc.relation.references | Cherubini, F. (2010). The biorefinery concept: Using biomass instead of oil for producing energy and chemicals. Energy Conversion and Management, 51(7), 1412–1421. https://doi.org/10.1016/j.enconman.2010.01.015 | spa |
| dc.relation.references | Combet, C., Blanchet, C., Geourjon, C., & Deléage, G. (2000). NPS@: Network protein sequence analysis. Trends in Biochemical Sciences, 25(3), 147–150. https://doi.org/10.1016/S0968-0004(99)01540-6 | spa |
| dc.relation.references | Davydov, R., Behrouzian, B., Smoukov, S., Stubbe, J., & Hoffman, B. M. (2005). Effect of Substrate on the Diiron ( III ) Site in Stearoyl Acyl Carrier Protein ∆ 9 Desaturase as Disclosed by Cryoreduction Electron Paramagnetic Resonance / Electron Nuclear Double Resonance Spectroscopy †, (Iii), 1309–1315. | spa |
| dc.relation.references | Deng, M., Zhang, K. U. I., Mehta, S., & Chen, T. (2003). Prediction of Protein Function Using Protein – Protein Interaction Data, 10(6), 947–960. | spa |
| dc.relation.references | Desbois, A. P., Lebl, T., Yan, L., & Smith, V. J. (2008). Isolation and structural characterisation of two antibacterial free fatty acids from the marine diatom , Phaeodactylum tricornutum, 755–764. https://doi.org/10.1007/s00253-0081714-9 | spa |
| dc.relation.references | Dolch, L. J., & Maréchal, E. (2015). Inventory of fatty acid desaturases in the pennate diatom Phaeodactylum tricornutum. Marine Drugs, 13(3), 1317–1339. https://doi.org/10.3390/md13031317 | spa |
| dc.relation.references | Domergue, F., Abbadi, A., Ott, C., Zank, T. K., Zähringer, U., & Heinz, E. (2003). Acyl carriers used as substrates by the desaturases and elongases involved in very long-chain polyunsaturated fatty acids biosynthesis reconstituted in yeast. Journal of Biological Chemistry, 278(37), 35115–35126 | spa |
| dc.relation.references | Domínguez, H. (2013). Algae as a source of biologically active ingredients for the formulation of functional foods and nutraceuticals. Functional Ingredients from Algae for Foods and Nutraceuticals, 1–19. https://doi.org/10.1533/9780857098689.1 | spa |
| dc.relation.references | Figueiredo, P. S., Inada, A. C., Marcelino, G., Cardozo, C. M. L., Freitas, K. de C., Guimarães, R. de C. A., … Hiane, P. A. (2017). Fatty acids consumption: The role metabolic aspects involved in obesity and its associated disorders. Nutrients, 9(10), 1–32. https://doi.org/10.3390/nu9101158 | spa |
| dc.relation.references | Galperin, M. Y., & Koonin, E. V. (2004). ―Conserved hypothetical‖ proteins: Prioritization of targets for experimental study. Nucleic Acids Research, 32(18), 5452–5463. https://doi.org/10.1093/nar/gkh885 | spa |
| dc.relation.references | Gantt E, C. S. (1965). The ultrastructure of Porphyridium cruentum. Journal of Experimental Psychology: General, 136(1), 23–42. | spa |
| dc.relation.references | Gasteiger, E., Bairoch, A., Sanchez, J., Williams, K. L., Wilkins, M. R., Appel, R. D., & Hochstrasser, D. F. (2005). Protein Identification and Analysis Tools in the ExPASy Server, 112, 531–552. | spa |
| dc.relation.references | German-Báez, L. J., Valdez-Flores, M. A., Félix-Medina, J. V., NorzagarayValenzuela, C. D., Santos-Ballardo, D. U., Reyes-Moreno, C., … Valdez-Ortiz, A. (2017). Chemical composition and physicochemical properties of Phaeodactylum tricornutum microalgal residual biomass. Food Science and Technology International, 23(8), 681–689. https://doi.org/10.1177/1082013217717611 | spa |
| dc.relation.references | Gibbs, sarah p. (1992). The Evolution of Algal Chloroplasts. (Ralph A Lewin, Ed.) (Chapman &). new York and Londom | spa |
| dc.relation.references | Glaser, F., Pupko, T., Paz, I., Bell, R. E., Bechor-Shental, D., Martz, E., & Ben-Tal, N. (2003). ConSurf: Identification of Functional Regions in Proteins by Surface-Mapping of Phylogenetic Information Downloaded from. Bioinformatics Applications Note, 19(1), 163–164. https://doi.org/10.1093/bioinformatics/19.1.163 | spa |
| dc.relation.references | Golding, G. B. (2003). DNA and the revolutions of molecular evolution, computational biology, and bioinformatics. Genome, 46(6), 930–935. https://doi.org/10.1139/g03-108 | spa |
| dc.relation.references | Hamilton, M. L., Warwick, J., Terry, A., Allen, M. J., Napier, A., & Sayanova, O. (2015). Towards the Industrial Production of Omega- 3 Long Chain Polyunsaturated Fatty Acids from a Genetically Modified Diatom Phaeodactylum tricornutum, 1–15. https://doi.org/10.1371/journal.pone.0144054 | spa |
| dc.relation.references | Hoffmann, M., Hornung, E., Busch, S., Kassner, N., Ternes, P., & Braus, G. H. (2007). A Small Membrane-peripheral Region Close to the Active Center Determines Regioselectivity of Membrane-bound Fatty Acid Desaturases from Aspergillus nidulans *, 282(37), 26666–26674. https://doi.org/10.1074/jbc.M705068200 | spa |
| dc.relation.references | Huang, A., He, L., & Wang, G. (2011). Identification and characterization of microRNAs from Phaeodactylum tricornutum by high- throughput sequencing and bioinformatics analysis. BMC Genomics, 12(1), 337. https://doi.org/10.1186/1471-2164-12-337 | spa |
| dc.relation.references | Jabeen, A., Mohamedali, A., & Ranganathan, S. (2018a). Protocol for Protein Structure Modelling. Encyclopedia of Bioinformatics and Computational Biology, (September 2017), 252–272. https://doi.org/10.1016/B978-0-12809633-8.20477-9 | spa |
| dc.relation.references | Jabeen, A., Mohamedali, A., & Ranganathan, S. (2018b). Protocol for Protein Structure Modelling. Encyclopedia of Bioinformatics and Computational Biology, (September 2017), 252–272. https://doi.org/10.1016/B978-0-12809633-8.20477-9 | spa |
| dc.relation.references | Kamm, B., & Kamm, M. (2004). Principles of biorefineries. Applied Microbiology and Biotechnology, 64(2), 137–145. https://doi.org/10.1007/s00253-003-15377 | spa |
| dc.relation.references | Kent, M., Welladsen, H. M., Mangott, A., & Li, Y. (2015). Nutritional evaluation of Australian microalgae as potential human health supplements. PLoS ONE, 83 10(2), 1–14. https://doi.org/10.1371/journal.pone.0118985 | spa |
| dc.relation.references | Khan, M. I., Shin, J. H., & Kim, J. D. (2018). The promising future of microalgae: Current status, challenges, and optimization of a sustainable and renewable industry for biofuels, feed, and other products. Microbial Cell Factories, 17(1), 1–21. https://doi.org/10.1186/s12934-018-0879-x | spa |
| dc.relation.references | Kim, S. M., Jung, Y. J., Kwon, O. N., Cha, K. H., Um, B. H., Chung, D., & Pan, C. H. (2012). A potential commercial source of fucoxanthin extracted from the microalga Phaeodactylum tricornutum. Applied Biochemistry and Biotechnology, 166(7), 1843–1855. https://doi.org/10.1007/s12010-012-9602-2 | spa |
| dc.relation.references | Koonin, E.V., Galperin, M. . (2003). Protein sequence motifs and domain databases In: Koonin, E.V., Galperin, M.Y. (Eds.), Sequence-evolution function: Computational Approaches in Comparative Genomics. Kluwer Academic Publishers. | spa |
| dc.relation.references | Krogh, A., Larsson, B., von Heijne, G., Sonnhammer, E. L. (2001). Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol., 305, 567–580. | spa |
| dc.relation.references | L. Tao, P. Zhang, C. Qin, S.Y. Chen, C. Zhang, Z. Chen, F. Zhu, S. Y., & Yang, Y.Q. Wei, Y. Z. C. (2015). Recent progresses in the exploration of machine learning methods as in-silico ADME prediction tool. Advanced Drug Delivery Reviews. https://doi.org/10.1016/j.addr.2015.03.01 | spa |
| dc.relation.references | Lacapere, J. J. (2017). Membrane Protein Structure and Function Characterization. (Jean-Jacques Lacapere, Ed.). Humana Press. https://doi.org/10.1007/978-14939-7151-0 | spa |
| dc.relation.references | Lebeau, M. T., & Robert, J. (2003). Diatom cultivation and biotechnologically relevant products . Part I : Cultivation at various scales, 612–623. https://doi.org/10.1007/s00253-002-1176-4 | spa |
| dc.relation.references | Lee, S. Y., Cho, J. M., Chang, Y. K., & Oh, Y. K. (2017). Cell disruption and lipid extraction for microalgal biorefineries: A review. Bioresource Technology, 244, 1317–1328. https://doi.org/10.1016/j.biortech.2017.06.038 | spa |
| dc.relation.references | Leliaert, F., Smith, D. R., Herron, M. D., Verbruggen, H., Delwiche, C. F., & Clerck, 84 O. De. (2012). Phylogeny and Molecular Evolution of the Green Algae, 1–46. https://doi.org/10.1080/07352689.2011.615705 | spa |
| dc.relation.references | Levitan, O., Dinamarca, J., Zelzion, E., Lun, D. S., Guerra, L. T., Kyung, M., & Kim, J. (2015). Remodeling of intermediate metabolism in the diatom Phaeodactylum tricornutum under nitrogen stress, 112(2). https://doi.org/10.1073/pnas.1419818112 | spa |
| dc.relation.references | Li, D., Xie, W., Hao, T., Cai, J., Zhou, T., & Balamurugan, S. (2018). Constitutive and Chloroplast Targeted Expression of Acetyl-CoA Carboxylase in Oleaginous Microalgae Elevates Fatty Acid Biosynthesis. | spa |
| dc.relation.references | Ligeya Perezleo Solórzano, Ricardo Arencibia Jorge, Clara Conill González, Gudelia Achón Veloz, J. A. A. R. (2003). Impacto de la Bioinformática en las ciencias biomédicas, 11(ISSN 1024-9435). | spa |
| dc.relation.references | Liu, J., Sun, Z., Gerken, H., & Huang, J. (2014). Genetic engineering of the green alga Chlorella zofingiensis : a modified norflurazon-resistant phytoene desaturase gene as a dominant selectable marker. https://doi.org/10.1007/s00253-014-5593-y | spa |
| dc.relation.references | Lu, J., & Deutsch, C. (2009). Electrostatics in the Ribosomal Tunnel Modulate Chain Elongation Rates Jianli. J Mol Biol, 384(1), 73–86. https://doi.org/10.1016/j.jmb.2008.08.089.Electrostatics | spa |
| dc.relation.references | Lubec, G., Afjehi-Sadat, L., Yang, J. W., & John, J. P. P. (2005). Searching for hypothetical proteins: Theory and practice based upon original data and literature. Progress in Neurobiology, 77(1–2), 90–127. https://doi.org/10.1016/j.pneurobio.2005.10.001 | spa |
| dc.relation.references | Martino, A. De, Meichenin, A., Shi, J., Pan, K., & Bowler, C. (2007). Genetic and phenotypic characterization of Phaeodactylum tricornutum (Bacillariophyceae) accessions. Journal of Phycology, 43(5), 992–1009. https://doi.org/10.1111/j.1529-8817.2007.00384.x | spa |
| dc.relation.references | McGuffin, L. J., Bryson, K., & Jones, D. T. (2000). The PSIPRED protein structure prediction server. Bioinformatics, 16(4), 404–405. https://doi.org/10.1093/bioinformatics/16.4.404 | spa |
| dc.relation.references | Medipally, S. R., Yusoff, F. M., Banerjee, S., & Shariff, M. (2015). Microalgae as sustainable renewable energy feedstock for biofuel production. BioMed Research International, 2015. https://doi.org/10.1155/2015/519513 | spa |
| dc.relation.references | Mendes, A., Reis, A., & Vasconcelos, R. (2009). Crypthecodinium cohnii with emphasis on DHA production : a review, 199–214. https://doi.org/10.1007/s10811-008-9351-3 | spa |
| dc.relation.references | Miao, X., Wu, Q., & Yang, C. (2004). Fast pyrolysis of microalgae to produce renewable fuels, 71, 855–863. https://doi.org/10.1016/j.jaap.2003.11.004 | spa |
| dc.relation.references | Monroig, Ó., Llanos, R. De, Var, I., & Hontoria, F. (n.d.). Biosynthesis of Polyunsaturated Fatty Acids in Octopus vulgaris : Molecular Cloning and Functional Characterisation of a Stearoyl-CoA Desaturase and an Elongation of Very Long-Chain Fatty Acid 4 Protein. https://doi.org/10.3390/md15030082 | spa |
| dc.relation.references | Chen, C., & Evans, L. B. (1989). Phase Partitioning of Biomolecules : Solubilities of Amino Acids, 5(3), 111–118. | Eng |
| dc.relation.references | Murakami, Y., Tripathi, L. P., & Prathipati, P. (2017). ScienceDirect Network analysis and in silico prediction of protein – protein interactions with applications in drug discovery. Current Opinion in Structural Biology, 44, 134– 142. https://doi.org/10.1016/j.sbi.2017.02.005 | Eng |
| dc.relation.references | Najmanovich, R. J. (2017). Evolutionary studies of ligand binding sites in proteins. Current Opinion in Structural Biology, 45, 85–90. https://doi.org/10.1016/j.sbi.2016.11.024 | Eng |
| dc.relation.references | Neira, J. L., Florencio, F. J., & Muro-pastor, M. I. (2017). Biophysical Chemistry The isolated , twenty-three-residue-long , N-terminal region of the glutamine synthetase inactivating factor binds to its target. Biophysical Chemistry, 228(June), 1–9. https://doi.org/10.1016/j.bpc.2017.05.017 | Eng |
| dc.relation.references | Nicoletti, M. (2016). Microalgae Nutraceuticals. Foods, 5(3), 54. https://doi.org/10.3390/foods5030054 | Eng |
| dc.relation.references | Norton, T. A., Melkonian, M., & Andersen, R. A. (1996). Algal biodiversity*. Phycologia, 35(4), 308–326. https://doi.org/10.2216/i0031-8884-35-4-308.1 | Eng |
| dc.relation.references | Obermayer, P. S. and B. (2005). Manufacturing Microalgae for Skin care, (16295351), 99–106. | Eng |
| dc.relation.references | Open, A. A., Bryant, F. M., Munoz-azcarate, O., Kelly, A. A., Beaudoin, F., Kurup, S., & Eastmond, P. J. (2016). ACYL-ACYL CARRIER PROTEIN DESATURASE2 and 3 Are Responsible for Making Omega-7 Fatty Acids in the, 172(September), 154–162. https://doi.org/10.1104/pp.16.00836 | Eng |
| dc.relation.references | Papers, J. (2003). Azide and Acetate Complexes plus two Iron-depleted Crystal Structures of the Di-iron Enzyme, 1–30. | Eng |
| dc.relation.references | Peng, K., Zheng, C., Xue, J., & Chen, X. (2014). Delta 5 fatty acid desaturase upregulates the synthesis of polyunsaturated fatty acids in marine diatom Phaeodactylum tricornutum Delta 5 Fatty Acid Desaturase Upregulates the Synthesis of Polyunsaturated Fatty Acids in the Marine Diatom Phaeodactylum tricornutum. https://doi.org/10.1021/jf5031086 | Eng |
| dc.relation.references | Plane, P., Rotation, B., Angles, D., Plot, R., Prediction, A., Plot, H., & Prediction, P. (2014). Additional Bioinformatic Analyses Involving Protein Sequences (pp. 183–207). https://doi.org/10.1016/B978-0-12-410471-6.00008-6 | Eng |
| dc.relation.references | Pollastri, G., Martin, A. J. M., Mooney, C., & Vullo, A. (2007). Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information. BMC Bioinformatics, 8, 1–12. https://doi.org/10.1186/1471-2105-8-201 | Eng |
| dc.relation.references | Prabowo, D. A., Hiraishi, O., & Suda, S. (2013). Diversity of Crypthecodinium SPP. (Dinophyceae) from Okinawa prefecture, Japan. Journal of Marine Science and Technology (Taiwan), 21(SUPPL), 181–191. https://doi.org/10.6119/JMST-013-1220-8 | Eng |
| dc.relation.references | Pulz, O., & Gross, W. (2004). Valuable products from biotechnology of microalgae. Applied Microbiology and Biotechnology, 65(6), 635–648. https://doi.org/10.1007/s00253-004-1647-x | Eng |
| dc.relation.references | Punta, M., Coggill, P. C., Eberhardt, R. Y., Mistry, J., Tate, J., Boursnell, C., … Finn, R. D. (2012). The Pfam protein families database. Nucleic Acids Research, 40(D1), 290–301. https://doi.org/10.1093/nar/gkr1065 | Eng |
| dc.relation.references | Raja, A., Vipin, C., & Aiyappan, A. (2013). Review Article Biological importance of Marine Algae- An overview, 2(5), 222–227. | Eng |
| dc.relation.references | Raposo, M. F. D. J., & De Morais, A. M. M. B. (2015a). Microalgae for the prevention of cardiovascular disease and stroke. Life Sciences, 125, 32–41. https://doi.org/10.1016/j.lfs.2014.09.018 | Eng |
| dc.relation.references | Raposo, M. F. D. J., & De Morais, A. M. M. B. (2015b). Microalgae for the prevention of cardiovascular disease and stroke. Life Sciences, 125, 32–41. https://doi.org/10.1016/j.lfs.2014.09.018 | Eng |
| dc.relation.references | Rebolloso-Fuentes M.M , Navarro-Perez A, R.-M. J. . and G.-G. (2000). Biomass Nutrient Profiles of the Microalga. Journal of Food Biochemistry, 25(2001), 57– 76. | Eng |
| dc.relation.references | Reijnders, M. J. M. F., van Heck, R. G. A., Lam, C. M. C., Scaife, M. A., dos Santos, V. A. P. M., Smith, A. G., & Schaap, P. J. (2014). Green genes: Bioinformatics and systems-biology innovations drive algal biotechnology. Trends in Biotechnology, 32(12), 617–626. https://doi.org/10.1016/j.tibtech.2014.10.003 | Eng |
| dc.relation.references | Roberts, R. J. (2004). Identifying protein function - A call for community action. PLoS Biology, 2(3), 293–294. https://doi.org/10.1371/journal.pbio.0020042 | Eng |
| dc.relation.references | Rodolfi, L., Zittelli, G. C., Bassi, N., Padovani, G., Biondi, N., Bonini, G., & Tredici, M. R. (2009). Microalgae for oil: Strain selection, induction of lipid synthesis and outdoor mass cultivation in a low-cost photobioreactor. Biotechnology and Bioengineering, 102(1), 100–112. https://doi.org/10.1002/bit.22033 | Eng |
| dc.relation.references | Rost, B., & Liu, J. (2003). The Predict Protein server. Nucleic Acids Research, 31(13), 3300–3304. https://doi.org/10.1093/nar/gkg508 | Eng |
| dc.relation.references | Rost, B., Liu, J., Nair, R., Wrzeszczynski, K. O., & Ofran, Y. (2003). Automatic prediction of protein function. Cellular and Molecular Life Sciences, 60(12), 2637–2650. https://doi.org/10.1007/s00018-003-3114-8 | Eng |
| dc.relation.references | Roy, A., Kucukural, A., & Zhang, Y. (2010). I-TASSER: A unified platform for automated protein structure and function prediction. Nature Protocols, 5(4), 725–738. https://doi.org/10.1038/nprot.2010.5 | Eng |
| dc.relation.references | Roy, S., Chakraborty, H., Kumar, V., Behera, B. K., & Rana, R. S. (2018). In Silico Structural Studies and Molecular Docking Analysis of Delta6-desaturase in HUFA Biosynthetic Pathway. Animal Biotechnology, 29(3), 161–173. https://doi.org/10.1080/10495398.2017.1332639 | Eng |
| dc.relation.references | Rubin, G. M., Sheahan, L. C., Kenyon, G. L., DeMarini, D. M., Fuchs, E., Galas, D. J., … Ringe, D. (2002). Defining the mandate of proteomics in the postgenomics era: workshop report. Mol Cell Proteomics, 1(10), 763–780. | Eng |
| dc.relation.references | Sathasivam, R., & Ki, J. S. (2018). A review of the biological activities of microalgal carotenoids and their potential use in healthcare and cosmetic industries. Marine Drugs, 16(1). https://doi.org/10.3390/md16010026 | Eng |
| dc.relation.references | Schlessinger, A., Yachdav, G., & Rost, B. (2006). PROFbval : predict flexible and rigid residues in proteins, 22(7), 891–893. https://doi.org/10.1093/bioinformatics/btl032 | Eng |
| dc.relation.references | Schwede, T., Kopp, J., Guex, N., & Peitsch, M. C. (2003). SWISS-MODEL: An automated protein homology-modeling server. Nucleic Acids Research, 31(13), 3381–3385. https://doi.org/10.1093/nar/gkg520 | Eng |
| dc.relation.references | Scientific, T. (2012). Extinction Coefficients: A guide to understanding extinction coefficients, with emphasis on spectrophotometric determination of protein concentration (Vol. 0747, pp. 4–6). | Eng |
| dc.relation.references | Serif, M., Dubois, G., Finoux, A., Teste, M., Jallet, D., & Daboussi, F. (n.d.). Onestep generation of multiple gene knock-outs in genome editing. Nature Communications, (2018), 1–10. https://doi.org/10.1038/s41467-018-06378-9 | Eng |
| dc.relation.references | Shapiro, L., & Harris, T. (2008). The rough guide to in silico function prediction, or how to use sequence and structure information to predict protein function. PLoS Computational Biology, 4(10). https://doi.org/10.1371/journal.pcbi.1000160 | Eng |
| dc.relation.references | Shen, P., Wang, H., Pan, Y., Meng, Y., & Wu, P. (2016). Identification of Characteristic Fatty Acids to Quantify Triacylglycerols in Microalgae, 7(February). https://doi.org/10.3389/fpls.2016.00162 | Eng |
| dc.relation.references | Sigrist, C. J. A., Cerutti, L., De Castro, E., Langendijk-Genevaux, P. S., Bulliard, V., Bairoch, A., & Hulo, N. (2009). PROSITE, a protein domain database for functional characterization and annotation. Nucleic Acids Research, 38(SUPPL.1), 161–166. https://doi.org/10.1093/nar/gkp885 | Eng |
| dc.relation.references | Silva Benavides, A. M., Torzillo, G., Kopecký, J., & Masojídek, J. (2013). Productivity and biochemical composition of Phaeodactylum tricornutum (Bacillariophyceae) cultures grown outdoors in tubular photobioreactors and open ponds. Biomass and Bioenergy, 54(0), 115–122. https://doi.org/10.1016/j.biombioe.2013.03.016 | Spa |
| dc.relation.references | Singh, D., Carlson, R., Fell, D., & Poolman, M. (2015). Modelling metabolism of the diatom Phaeodactylum tricornutum. Biochemical Society Transactions, 43(6), 1182–1186. https://doi.org/10.1042/BST20150152 | Eng |
| dc.relation.references | Singh, S., Arora, R. R., Singh, M., & Khosla, S. (2016). Eicosapentaenoic acid versus docosahexaenoic acid as options for vascular risk prevention: A fish story. American Journal of Therapeutics, 23(3), e905–e910. https://doi.org/10.1097/MJT.0000000000000165 | Eng |
| dc.relation.references | Souza, A. De, Requi, R. D., Fernandes, L., Jose, H., Rossetto, S., Domitrovic, T., & Palhano, F. L. (2017). Protein charge distribution in proteomes and its impact on translation, 1–21. | Eng |
| dc.relation.references | Spolaore, P., Joannis-cassan, C., Duran, E., Isambert, A., Génie, L. De, & Paris, E. C. (2006). Commercial Applications of Microalgae, 101(2), 87–96. https://doi.org/10.1263/jbb.101.87 | Eng |
| dc.relation.references | Srinuanpan, S., Chawpraknoi, A., Chantarit, S., & Prasertsan, P. (2018). A rapid method for harvesting and immobilization of oleaginous microalgae using pellet-forming filamentous fungi and the application in phytoremediation of secondary effluent. International Journal of Phytoremediation, 20(10), 1017– 1024. https://doi.org/10.1080/15226514.2018.1452187 | Eng |
| dc.relation.references | Starr C., Taggart R ., Evers C., S. L. (2011). Biology: The Unity and Diversity of Life. (CENGAGE Learning Custom Publishing, Ed.) (12th ed.). | Eng |
| dc.relation.references | Stone, T. A., Schiller, N., Workewych, N., Heijne, G. Von, & Deber, C. M. (2016). Hydrophobic clusters raise the threshold hydrophilicity for insertion of transmembrane sequences in vivo Hydrophobic clusters raise the threshold hydrophilicity for insertion of transmembrane sequences in vivo. Biochemistry, 1–33. https://doi.org/10.1021/acs.biochem.6b00650 90 Suda, S., At | Eng |
| dc.relation.references | Suda, S., Atsumi, M., & Miyashita, H. (2002). Taxonomic characterization of a marine Nannochloropsis species, N. oceanica sp. nov. (Eustigmatophyceae). Phycologia, 41(3), 273–279. https://doi.org/10.2216/i0031-8884-41-3-273.1 | Eng |
| dc.relation.references | Tonon, T., Harvey, D., Larson, T. R., & Graham, I. A. (2002). Long chain polyunsaturated fatty acid production and partitioning to triacylglycerols in four microalgae, 61, 15–24. | Eng |
| dc.relation.references | Tsui, C. K. M., Marshall, W., Yokoyama, R., Honda, D., Lippmeier, J. C., Craven, K. D., … Berbee, M. L. (2009). Labyrinthulomycetes phylogeny and its implications for the evolutionary loss of chloroplasts and gain of ectoplasmic gliding. Molecular Phylogenetics and Evolution, 50(1), 129–140. https://doi.org/10.1016/j.ympev.2008.09.027 | Eng |
| dc.relation.references | Tusnady, G.E., Simon, I. (2001). The HMMTOP transmembrane topology prediction server. Bioinformatics, 17, 849–850. | Eng |
| dc.relation.references | Ur Rehman Hafeez , BariInam, Ali Anwar, and M. H. (2017). A Bayesian Approach for Estimating Protein-Protein Interactions by Integrating Structural and NonStructural Biological Data. Molecular BioSystems, 1, 1–11. https://doi.org/10.1039/C7MB00484B | Eng |
| dc.relation.references | Via, A., & Helmer-citterich, M. (2004). A structural study for the optimisation of functional motifs encoded in protein sequences, 12, 1–12. | Eng |
| dc.relation.references | Villanova, V., Fortunato, A. E., Singh, D., Bo, D. D., Conte, M., Obata, T., … Finazzi, G. (2017). Investigating mixotrophic metabolism in the model diatom Phaeodactylum tricornutum. | Eng |
| dc.relation.references | Vrieling, E. G., Beelen, T. P. M., van Santen, R. A., & Gieskes, W. W. C. (1999). Diatom silicon biomineralization as an inspirational source of new approaches to silica production. Progress in Industrial Microbiology, 35(C), 39–51. https://doi.org/10.1016/S0079-6352(99)80096-4 | Eng |
| dc.relation.references | Wainright PO, Hinkle G, Sogin ML, S. S. (2000). Monophyletic Origins of the Metazoa : An Evolutionary Link with Fungi. | Eng |
| dc.relation.references | Wang, X., Liu, Y., Wei, W., Zhou, X., & Yuan, W. (2017). Enrichment of long-chain polyunsaturated fatty acids by coordinated expression of multiple metabolic nodes in the oleaginous microalga Phaeodactylum tricornutum. https://doi.org/10.1021/acs.jafc.7b02397 | Eng |
| dc.relation.references | Wilkins, M. R., Gasteiger, E., Bairoch, A., Sanchez, J., Williams, K. L., Appel, R. D., & Hochstrasser, D. F. (2005). Protein Identification and Analysis Tools in the ExPASy Server, 112, 531–552. | Eng |
| dc.relation.references | Wilson, C. A., Kreychman, J., & Gerstein, M. (2000). Assessing annotation transfer for genomics: Quantifying the relations between protein sequence, structure and function through traditional and probabilistic scores. Journal of Molecular Biology, 297(1), 233–249. https://doi.org/10.1006/jmbi.2000.3550 | Eng |
| dc.relation.references | Xue, W., Liu, F., Sun, Z., & Zhou, Z. (2016). A ∆ -9 Fatty Acid Desaturase Gene in the Microalga Myrmecia incisa Reisigl : Cloning and Functional Analysis. https://doi.org/10.3390/ijms17071143 | Eng |
| dc.relation.references | Yang, J., Wang, Y., Zhang, Y., Arbor, A., & Arbor, A. (2017). ResQ: An approach to unified estimation of B-factor and residue-specific error in protein structure prediction. J Mol Biol, 428(4), 693–701. https://doi.org/10.1016/j.jmb.2015.09.024.ResQ | Eng |
| dc.relation.references | Yang, M., Lin, X., Liu, X., Zhang, J., & Ge, F. (2018). Genome Annotation of a Model Diatom Phaeodactylum tricornutum Using an Integrated Proteogenomic Pipeline. Molecular Plant, 11(10), 1292–1307. https://doi.org/10.1016/j.molp.2018.08.005 | Eng |
| dc.relation.references | Yang, Y., Du, L., Hosokawa, M., Miyashita, K., Kokubun, Y., Arai, H., & Taroda, H. (2017). Fatty Acid and Lipid Class Composition of the Microalga Phaeodactylum tricornutum, 368(4), 363–368. | Eng |
| dc.relation.references | Zaslavskaia, L. A., Casey Lippmeier, J., Kroth, P. G., Grossman, A. R., & Apt, K. E. (2000). Transformation of the diatom Phaeodactylum tricornutum (Bacillariophyceae) with a variety of selectable marker and reporter genes. Journal of Phycology, 36(2), 379–386. https://doi.org/10.1046/j.1529- 8817.2000.99164.x | Eng |
| dc.relation.references | Zhang, Y. (2008). I-TASSER server for protein 3D structure prediction. BMC Bioinformatics, 9, 1–8. https://doi.org/10.1186/1471-2105-9-40 | Eng |
| dc.relation.references | Zhang, Y., & Skolnick, J. (2005). TM-align: A protein structure alignment algorithm based on the TM-score. Nucleic Acids Research, 33(7), 2302–2309. https://doi.org/10.1093/nar/gki524 | Eng |
| dc.relation.references | Zou, L. G., Chen, J. W., Zheng, D. L., Balamurugan, S., Li, D. W., Yang, W. D., & Liu, J. S. (2018). High ‑ efficiency promoter ‑ driven coordinated regulation of multiple metabolic nodes elevates lipid accumulation in the model microalga Phaeodactylum tricornutum. Microbial Cell Factories, 1–8. https://doi.org/10.1186/s12934-018-0906-y | Eng |
| dc.relation.references | Zulu N.N., Zienkiewicz K., Vollheyde K., F. I. . (2018). Current trends to comprehend lipid metabolism in diatoms. Progress in Lipid Research, 70(December 2017), 1–16. https://doi.org/10.1016/j.plipres.2018.03.001 | Eng |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | spa |
| dc.rights.license | Atribución-NoComercial-SinDerivadas 2.5 Colombia | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | * |
| dc.subject | Ácidos grasos | spa |
| dc.subject | Energía biomasica | spa |
| dc.subject | Microalgas | spa |
| dc.subject.lemb | Biotecnología -- Investigaciones | spa |
| dc.subject.lemb | Ácidos grasos -- Investigaciones | spa |
| dc.subject.lemb | Phaeodactylum tricornutum | spa |
| dc.subject.proposal | In – silico | spa |
| dc.subject.proposal | Ácidos grasos | spa |
| dc.subject.proposal | PUFAs | spa |
| dc.subject.proposal | Phaeodactylum tricornutum | spa |
| dc.subject.subjectenglish | In - silico | spa |
| dc.subject.subjectenglish | fatty acids | spa |
| dc.subject.subjectenglish | PUFAs | spa |
| dc.subject.subjectenglish | Phaeodactylum tricornutum | spa |
| dc.title | Evaluación in – silico de la estructura y función de la proteína hipotética B7FQK1 de phaeodactylum tricornutum | spa |
| dc.type.driver | info:eu-repo/semantics/masterThesis | spa |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | spa |
| dc.type.local | Tesis de Maestría | spa |
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