MODELAMIENTO MOLECULAR DE LA CRUZIOSEPTINA CC-16 EXTRAÍDA DE LA RANA Cruziohyla calcarifer
Contenido principal del artículo
Resumen
El creciente desarrollo de resistencia a antibióticos por parte de mundo microbiano es un problema cada vez mayor y en respuesta nuevas moléculas con potencial antimicrobiano están siendo estudiadas, entre ellas los péptidos antimicrobianos como las Cruzioseptinas. Este trabajo presenta un estudio computacional preliminar de la Cruzioseptina CC-16 extraída del exudado de la piel de la rana Cruziohyla calcarifer. Con base en la secuencia de aminoácidos del péptido se llevaron a cabo diferentes estudios computacionales, entre ellos, la predicción de las propiedades fisicoquímicas y la estructura secundaria. Además de esto se efectuó el acoplamiento molecular de la Cruzioseptina CC-16 con diferentes enzimas de importancia biológica para microrganismos como Escherechia coli, Staphylococcus aureus y Candida albicans, y con moléculas presentes en la membrana celular bacteriana. Los resultados mostraron que la Cruzioseptina CC-16 es un péptido de 23 residuos de largo con una conformación alfa helicoidal predominante, un punto isoeléctrico de 10,73, una carga de +3 de carácter básica y una carga neta a pH 7 de +3,1, además de tener más del 50 % de su estructura conformada por aminoácidos hidrofóbicos, clasificando como un péptido antimicrobiano catiónico. Los estudios preliminares de acoplamiento molecular muestran que un mecanismo de acción basado en inhibición enzimática no es posible, debido principalmente al tamaño del péptido, mientras que un mecanismo con base en un ataque concentrado en la membrana microbiana puede ser viable, debido a las interacciones electrostáticas de la Cruzioseptina CC-16 con diferentes componentes de la membrana.
Descargas
Detalles del artículo
- Los autores se comprometen a respetar la información académica de otros autores, y a ceder los derechos de autor a la Revista infoANALÍTICA, para que el artículo pueda ser editado, publicado y distribuido.
- El contenido de los artículos científicos y de las publicaciones que aparecen en la revista es responsabilidad exclusiva de sus autores. La distribución de los artículos publicados en la Revista infoANALÍTICA se realiza bajo una licencia Creative Commons Reconocimiento-CompartirIgual 4.0 Internacional License.
Citas
Bastos, M. C., Santos, D. R. dos, Aubertheau, É., Lima, J. A. M. de C., Guet, T. L., Caner, L., Mondamert, L., & Labanowski, J. (2018). Antibiotics and microbial resistance in Brazilian soils under manure application. Land Degradation & Development, 29(8), 2472–2484. https://doi.org/10.1002/ldr.2964
Bechinger, B., & Gorr, S.-U. (2017). Antimicrobial Peptides: Mechanisms of Action and Resistance. Journal of Dental Research, 96(3), 254–260. https://doi.org/10.1177/0022034516679973
Berman, H. M., Battistuz, T., Bhat, T. N., Bluhm, W. F., Bourne, P. E., Burkhardt, K., Feng, Z., Gilliland, G. L., Iype, L., Jain, S., Fagan, P., Marvin, J., Padilla, D., Ravichandran, V., Schneider, B., Thanki, N., Weissig, H., Westbrook, J. D., & Zardecki, C. (2002). The Protein Data Bank. Acta Crystallographica. Section D, Biological Crystallography, 58(Pt 6 No 1), 899–907. https://doi.org/10.1107/s0907444902003451
Bio-Synthesis. (2010). Peptide Calculator. https://www.biosyn.com/peptidepropertycalculatorlanding.aspx
Caltabiano, G., Gonzalez, A., Cordomí, A., Campillo, M., & Pardo, L. (2013). The role of hydrophobic amino acids in the structure and function of the rhodopsin family of G protein-coupled receptors. Methods in Enzymology, 520, 99–115. https://doi.org/10.1016/B978-0-12-391861-1.00005-8
Candido, E., de Barros, E., Cardoso, M., & Franco, O. (2019). Bacterial cross-resistance to anti-infective compounds. Is it a real problem? Current Opinion in Pharmacology, 48, 76–81. https://doi.org/10.1016/j.coph.2019.05.004
Celis, J. E., Carter, N., Simons, K., Small, J. V., Hunter, T., & Shotton, D. (2005). Cell Biology: A Laboratory Handbook. Elsevier.
Ciemny, M., Kurcinski, M., Kamel, K., Kolinski, A., Alam, N., Schueler-Furman, O., & Kmiecik, S. (2018). Protein–peptide docking: Opportunities and challenges. Drug Discovery Today, 23(8), 1530–1537. https://doi.org/10.1016/j.drudis.2018.05.006
Ciumac, D., Gong, H., Hu, X., & Lu, J. R. (2019). Membrane targeting cationic antimicrobial peptides. Journal of Colloid and Interface Science, 537, 163–185. https://doi.org/10.1016/j.jcis.2018.10.103
Conlon, J. M., Mechkarska, M., & Leprince, J. (2019). Peptidomic analysis in the discovery of therapeutically valuable peptides in amphibian skin secretions. Expert Review of Proteomics, 16(11–12), 897–908. https://doi.org/10.1080/14789450.2019.1693894
Craveur, P., Joseph, A. P., Esque, J., Narwani, T. J., Noël, F., Shinada, N., Goguet, M., Leonard, S., Poulain, P., Bertrand, O., Faure, G., Rebehmed, J., Ghozlane, A., Swapna, L. S., Bhaskara, R. M., Barnoud, J., Téletchéa, S., Jallu, V., Cerny, J., … de Brevern, A. G. (2015). Protein flexibility in the light of structural alphabets. Frontiers in Molecular Biosciences, 2. https://doi.org/10.3389/fmolb.2015.00020
Cuesta, S., Arias, J., Gallegos, F., Proaño-Bolaños, C., Blasco-Zúñiga, A., Rivera, M., & Meneses, L. (2019). Modelamiento molecular de la dermaseptina SP2 extraída de Agalychnis spurrelli. infoANALÍTICA, 7(1), 41–56. https://doi.org/10.26807/ia.v7i1.95
Cuesta, S., Gallegos, F., Arias, J., Pilaquinga, F., Blasco-Zúñiga, A., Proaño-Bolaños, C., Rivera, M., & Meneses, L. (2019). Molecular modeling of four Dermaseptin-related peptides of the gliding tree frog Agalychnis spurrelli. Journal of Molecular Modeling, 25(9), 260. https://doi.org/10.1007/s00894-019-4141-1
Cui, D., Liu, X., Hawkey, P., Li, H., Wang, Q., Mao, Z., & Sun, J. (2017). Use of and microbial resistance to antibiotics in China: A path to reducing antimicrobial resistance. Journal of International Medical Research, 45(6), 1768–1778. https://doi.org/10.1177/0300060516686230
Demori, I., El Rashed, Z., Corradino, V., Catalano, A., Rovegno, L., Queirolo, L., Salvidio, S., Biggi, E., Zanotti-Russo, M., Canesi, L., Catenazzi, A., & Grasselli, E. (2019). Peptides for Skin Protection and Healing in Amphibians. Molecules, 24(2), 347. https://doi.org/10.3390/molecules24020347
Drozdetskiy, A., Cole, C., & Procter, J. (2015). JPred4: A protein secondary structure prediction server. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489285/
Fieser, T. M., Tainer, J. A., Geysen, H. M., Houghten, R. A., & Lerner, R. A. (1987). Influence of protein flexibility and peptide conformation on reactivity of monoclonal anti-peptide antibodies with a protein alpha-helix. Proceedings of the National Academy of Sciences of the United States of America, 84(23), 8568–8572. https://doi.org/10.1073/pnas.84.23.8568
Frisch, M. J., Trucks, G. W., Schlegel, H. B., Scuseria, G. E., Robb, M. A., Cheeseman, J. R., Scalmani, G., Barone, V., & Petersson, G. A. (2009). Gaussian 09, Revision C.01. Gaussian, Inc.
Gorr, S.-U., & Abdolhosseini, M. (2011). Antimicrobial peptides and periodontal disease. Journal of Clinical Periodontology, 38(s11), 126–141. https://doi.org/10.1111/j.1600-051X.2010.01664.x
Haney, E. F., Mansour, S. C., & Hancock, R. E. W. (2017). Antimicrobial Peptides: An Introduction. En P. R. Hansen (Ed.), Antimicrobial Peptides (Vol. 1548, pp. 3–22). Springer New York. https://doi.org/10.1007/978-1-4939-6737-7_1
Hoagland, P. D., Unruh, J. J., Wickham, E. D., & Farrell, H. M. (2001). Secondary Structure of Bovine αS2-Casein: Theoretical and Experimental Approaches1. Journal of Dairy Science, 84(9), 1944–1949. https://doi.org/10.3168/jds.S0022-0302(01)74636-X
Hughes, A. (2013). Amino Acids, Peptides and Proteins in Organic Chemistry, Analysis and Function of Amino Acids and Peptides. John Wiley & Sons.
Innovagen AB. (2015). PepCalc.com—Peptide calculator. https://pepcalc.com/
Jacobs, D. J., Rader, A. J., Kuhn, L. A., & Thorpe, M. F. (2001). Protein flexibility predictions using graph theory. Proteins, 44(2), 150–165. https://doi.org/10.1002/prot.1081
Kim, B. Y., & Jin, B. R. (2019). Antimicrobial activity of the C-terminal of the major royal jelly protein 4 in a honeybee (Apis cerana). https://pubag.nal.usda.gov/catalog/6367364
Kumar, P., Kizhakkedathu, J., & Straus, S. (2018). Antimicrobial Peptides: Diversity, Mechanism of Action and Strategies to Improve the Activity and Biocompatibility In Vivo. Biomolecules, 8(1), 4. https://doi.org/10.3390/biom8010004
Kwon, J. Y., Kim, M. K., Mereuta, L., Seo, C. H., Luchian, T., & Park, Y. (2019). Mechanism of action of antimicrobial peptide P5 truncations against Pseudomonas aeruginosa and Staphylococcus aureus. AMB Express, 9. https://doi.org/10.1186/s13568-019-0843-0
Lamont, R. J., Hajishengallis, G. N., & Jenkinson, H. F. (2015). Microbiología e inmunología oral. Editorial El Manual Moderno.
Latendorf, T., Gerstel, U., Wu, Z., Bartels, J., Becker, A., Tholey, A., & Schröder, J.-M. (2019). Cationic Intrinsically Disordered Antimicrobial Peptides (CIDAMPs) Represent a New Paradigm of Innate Defense with a Potential for Novel Anti-Infectives. Scientific Reports, 9(1), 3331. https://doi.org/10.1038/s41598-019-39219-w
Lewin, A. C., Hausmann, J. C., & Miller, P. E. (2017). Intraocular pressure and examination findings in three species of central and south american tree frogs (Cruziohyla craspedopus, Cruziohyla calcarifer, and Anotheca spinosa). Journal of Zoo and Wildlife Medicine: Official Publication of the American Association of Zoo Veterinarians, 48(3), 688–693. https://doi.org/10.1638/2016-0243.1
Lexa, K. W., & Carlson, H. A. (2012). Protein Flexibility in Docking and Surface Mapping. Quarterly reviews of biophysics, 45(3), 301–343. https://doi.org/10.1017/S0033583512000066
Li, J., Koh, J.-J., Liu, S., Lakshminarayanan, R., Verma, C. S., & Beuerman, R. W. (2017). Membrane Active Antimicrobial Peptides: Translating Mechanistic Insights to Design. Frontiers in Neuroscience, 11. https://doi.org/10.3389/fnins.2017.00073
Martinez, J. L. (2014). General principles of antibiotic resistance in bacteria. Drug Discovery Today: Technologies, 11, 33–39. https://doi.org/10.1016/j.ddtec.2014.02.001
Meng, F., & Kurgan, L. (2016). Computational Prediction of Protein Secondary Structure from Sequence. Current Protocols in Protein Science, 86(1), 2.3.1-2.3.10. https://doi.org/10.1002/cpps.19
Mingqiang, R., Jie, L., Qiong, L., Zhilong, L., Bo, W., Yan, R., & Ren, L. (2018). The defensive system of tree frog skin identified by peptidomics and RNA sequencing analysis. Amino Acids, 51(2), 345–353. https://doi.org/10.1007/s00726-018-2670-z
Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009). AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785–2791. https://doi.org/10.1002/jcc.21256
Nikolaieva, I., Yu, D., Oliinyk, D., Oskyrko, O., Marushchak, O., Halenova, T., & Savchuk, O. (2018). Amphibian skin secretions: A potential source of proteolytic enzymes. Biotechnologia Acta, 11(5), Article 5. https://cyberleninka.ru/article/n/amphibian-skin-secretions-a-potential-source-of-proteolytic-enzymes
Peters, B. M., Shirtliff, M. E., & Jabra-Rizk, M. A. (2010). Antimicrobial Peptides: Primeval Molecules or Future Drugs? PLoS Pathogens, 6(10), e1001067. https://doi.org/10.1371/journal.ppat.1001067
Piotrowski, J. S., Okada, H., Lu, F., Li, S. C., Hinchman, L., Ranjan, A., Smith, D. L., Higbee, A. J., Ulbrich, A., Coon, J. J., Deshpande, R., Bukhman, Y. V., McIlwain, S., Ong, I. M., Myers, C. L., Boone, C., Landick, R., Ralph, J., Kabbage, M., & Ohya, Y. (2015). Plant-derived antifungal agent poacic acid targets β-1,3-glucan. Proceedings of the National Academy of Sciences, 112(12), E1490–E1497. https://doi.org/10.1073/pnas.1410400112
Proaño-Bolaños, C. (2016). Peptidomic approach identifies cruzioseptins, a new family of potent antimicrobial peptides in the splendid leaf frog, Cruziohyla calcarifer. Journal of Proteomics, 13.
Proaño-Bolaños, C., Blasco-Zúñiga, A., De Almeida, J., Wang, L., Llumiquinga, M., Rivera, M., Zhou, M., Chen, T., & Shaw, C. (2019). Unravelling the Skin Secretion Peptides of the Gliding Leaf Frog, Agalychnis spurrelli (Hylidae). Biomolecules, 9, 1–20. https://doi.org/10.3390/biom9110667
Rhouma, M., Beaudry, F., Thériault, W., & Letellier, A. (2016). Colistin in Pig Production: Chemistry, Mechanism of Antibacterial Action, Microbial Resistance Emergence, and One Health Perspectives. Frontiers in Microbiology, 7. https://doi.org/10.3389/fmicb.2016.01789
Roca, I., Akova, M., Baquero, F., Carlet, J., Cavaleri, M., Coenen, S., Cohen, J., Findlay, D., Gyssens, I., Heure, O. E., Kahlmeter, G., Kruse, H., Laxminarayan, R., Liébana, E., López-Cerero, L., MacGowan, A., Martins, M., Rodríguez-Baño, J., Rolain, J.-M., … Vila, J. (2015). The global threat of antimicrobial resistance: Science for intervention. New Microbes and New Infections, 6, 22–29. https://doi.org/10.1016/j.nmni.2015.02.007
Rudi, J. M., Müller, D. M., Siano, A., Simonetta, A. C., & Tonarelli, G. G. (2010). Péptido Antimicrobiano Quimérico de Dermaseptina-S1 y Tigerinina-1: Estructura Secundaria y Selectividad hacia Membranas. FABICIB, 14, 148–161. https://doi.org/10.14409/fabicib.v14i1.859
Rydberg, H. A., Carlsson, N., & Nordén, B. (2012). Membrane interaction and secondary structure of de novo designed arginine-and tryptophan peptides with dual function. Biochemical and Biophysical Research Communications, 427(2), 261–265. https://doi.org/10.1016/j.bbrc.2012.09.030
Schrödinger. (2017). The PyMOL Molecular Graphics System (Versión 2.0) [Python]. Schrödinger,LLC.
Soreq, H. (2012). Human Cholinesterases and Anticholinesterases. Academic Press.
Swoboda, J. G., Campbell, J., Meredith, T. C., & Walker, S. (2010). Wall Teichoic Acid Function, Biosynthesis, and Inhibition. ChemBioChem, 11(1), 35–45. https://doi.org/10.1002/cbic.200900557
Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
Vishnepolsky, B., & Pirtskhalava, M. (2014). Prediction of linear cationic antimicrobial peptides based on characteristics responsible for their interaction with the membranes. Journal of Chemical Information and Modeling, 54(5), 1512–1523. https://doi.org/10.1021/ci4007003
Walsh, C. T., & Wencewicz, T. A. (2014). Prospects for new antibiotics: A molecule-centered perspective. The Journal of Antibiotics, 67(1), 7–22. https://doi.org/10.1038/ja.2013.49
Yachdav, G., & Rost, B. (2013). PredictProtein—Protein Sequence Analysis, Prediction of Structural and Functional Features. https://predictprotein.org/
Yang, M., Zhang, C., Zhang, M. Z., & Zhang, S. (2018). Beta-defensin derived cationic antimicrobial peptides with potent killing activity against gram negative and gram positive bacteria. BMC Microbiology, 18(1), 54. https://doi.org/10.1186/s12866-018-1190-z
Yasir, M., Dutta, D., & Willcox, M. D. P. (2019). Comparative mode of action of the antimicrobial peptide melimine and its derivative Mel4 against Pseudomonas aeruginosa. Scientific Reports, 9(1), 7063. https://doi.org/10.1038/s41598-019-42440-2