Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)García Contreras, German AntonioMendoza López, Angie Bibiana2021-02-182021-02-182020-11-18http://repositorio.uan.edu.co/handle/123456789/1495PropiaProstate cancer is the malignant growth of the prostate gland; It occurs when the cells of the prostate mutate and multiply uncontrollably. Fibroblast growth factor 8b (FGF8b) is expressed in a large percentage of patients with prostate cancer and plays a key role in the appearance and development of this cancer. Various studies have shown that the synthetic peptide 8b-13, derived from the gN helix domain of FGF8b, blocks the interaction of FGF8b with the fibroblast growth factor receptor (FGFR), inhibiting the proliferation of prostate cancer cell lines . To identify the affinity towards the FGF8b/FGFR complex of peptides derived from 8b-13, a peptide library was proposed by making cuts at the amino and carboxyl termini of the 8b-13 sequence. The affinity towards the FGF8b/FGFR complex was evaluated and the key amino acids for the interaction were identified by means of molecular docking tests, using the algorithm of AutoDock Vina, Chimera and Discovery Studio. The results propose viable peptides to be candidates in experimental trials that could demonstrate the inhibition of cancer cell proliferation, developing tools for the possible treatment of prostate cancer.El cáncer de próstata es el crecimiento maligno de la glándula prostática; se produce cuando las células de la próstata mutan y se multiplican descontroladamente. El factor de crecimiento de fibroblastos 8b (FGF8b) se encuentra expresado en un gran porcentaje de pacientes con cáncer de próstata y desempeña un papel clave en la aparición y desarrollo de este cáncer. Diversos estudios han demostrado que el péptido sintético denominado 8b13, procedente del dominio de hélice gN del FGF8b, bloquea la interacción del FGF8b con el receptor de factor de crecimiento de fibroblastos (FGFR), inhibiendo la proliferación de líneas celulares del cáncer de próstata. Para identificar la afinidad hacía el complejo FGF8b/FGFR de péptidos derivados del 8b 13, se propuso una librería peptídica realizando cortes en los extremos amino y carboxilo terminal de la secuencia del 8b-13. Se evaluó la afinidad hacía el complejo FGF8b/FGFR y se identificó los aminoácidos claves para la interacción por medio de pruebas de docking molecular, utilizando el algoritmo de AutoDock Vina, Chimera y Discovery Studio. Los resultados proponen péptidos viables para ser candidatos en ensayos experimentales que podrían demostrar la inhibición de la proliferación de células cancerígenas, desarrollando herramientas para el posible tratamiento del cáncer de próstata.spaAcceso abiertoDiseño de péptidosPéptidos sintéticosFactor de crecimiento de fibroblastosCáncer de próstataDocking molecularEvaluación in silico de péptidos derivados de la secuencia peptídica 8b-13 hacia el complejo FGF8b/FGFRTrabajo de grado (Pregrado y/o Especialización)Peptide designSynthetic peptidesFibroblast growth factorProstate cancerDocking molecularinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Siegel, R. L., Miller, K. D., & Jemal, A. (2019). Cancer statistics, 2019. CA: a cancer journal for clinicians, 69(1), 7-34.Acuña, L. (11 de Julio de 2019). Cuenta de Alto Costo. Obtenido de https://www.cuentadealtocosto.org/site/images/Reporte_Especial_Dia_mundial_del_cancer_de_prostata_2019.pdf.Coughlin, S. S. (2019). A Review of Social Determinants of Prostate Cancer Risk,Stage, and Survival. Prostate International.Bidwell III, G. L., & Raucher, D. (2009). Therapeutic peptides for cancer therapy. Part I–peptide inhibitors of signal transduction cascades. Expert opinion on drug delivery,6(10), 1033-1047.Li, T., Luo, W., He, D., Wang, R., Huang, Y., Zeng, X., ... & Li, X. (2013). A short peptide derived from the gN helix domain of FGF8b suppresses the growth of human prostate cancer cells. Cancer letters, 339(2), 226-236.Valta, M. P., Tuomela, J., Bjartell, A., Valve, E., Väänänen, H. K., & Härkönen, P.(2008). FGF‐8 is involved in bone metastasis of prostate cancer. International journal of cancer, 123(1), 22-31.Gnanapragasam, V. J., Robinson, M. C., Marsh, C., Robson, C. N., Hamdy, F. C., & Leung, H. Y. (2003). FGF8 isoform b expression in human prostate cancer. British journal of cancer, 88(9), 1432-1438.Dorkin, T. J., Robinson, M. C., Marsh, C., Bjartell, A., Neal, D. E., & Leung, H. Y. (1999). FGF8 over-expression in prostate cancer is associated with decreased patient survival and persists in androgen independent disease. Oncogene, 18(17),2755.Drake, J. M., Graham, N. A., Lee, J. K., Stoyanova, T., Faltermeier, C. M., Sud, S., ... & Witte, O. N. (2013). Metastatic castration-resistant prostate cancer reveals intrapatient similarity and interpatient heterogeneity of therapeutic kinase targets.Proceedings of the National Academy of Sciences, 110(49), E4762-E4769.Gdowski, A. S., Ranjan, A., & Vishwanatha, J. K. (2017). Current concepts in bone metastasis, contemporary therapeutic strategies and ongoing clinical trials. Journal of Experimental & Clinical Cancer Research, 36(1), 108.Liu, H., Lin, X., Huang, T., Song, L., Zhu, C., Ma, H., ... & Huang, Y. (2018). A short peptide reverses the aggressive phenotype of prostate cancer cells. European journal of pharmacology, 838, 129-137.Rentzsch, R., & Renard, B. Y. (2015). Docking small peptides remains a great challenge: an assessment using AutoDock Vina. Briefings in Bioinformatics, 16(6), 1045-1056.Shen Y, Maupetit J, Derreumaux P, Tufféry P. Improved PEP-FOLD approach for peptide and miniprotein structure prediction J. Chem. Theor. Comput. 2014; 10:4745-4758Morris, 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.O. Trott, A. J. Olson, AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading, Journal of Computational Chemistry 31 (2010) 455-46. DOI 10.1002/jcc.21334.Seeliger, D., & de Groot, B. L. (2010). Ligand docking and binding site analysis with PyMOL and Autodock/Vina. Journal of computer-aided molecular design, 24(5), 417-422.Raschka, S. (2014). Molecular docking, estimating free energies of binding, andAutoDock's semi‐empirical force field.BIOVIA, Discovery Studio Modeling Environment, Release 2017, San Diego: Dassault Systèmes, 2016.Chang, K. Y., & Yang, J. R. (2013). Analysis and prediction of highly effective antiviral peptides based on random forests. PloS one, 8(8), e70166.