Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos
Ilustraciones, ilustraciones, mapas, tablas
- Autores:
-
Morillo Garces, Jairo Alexander
- Tipo de recurso:
- Fecha de publicación:
- 2024
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/86299
- Palabra clave:
- 660 - Ingeniería química
Antibióticos
Péptidos antimicrobianos
Resistencia antimicrobiana
Proteomas
Virus
Bacterias
Hongos
Bioinformática
Inteligencia artificial
Proteomes
Antimicrobial peptides
Antimicrobial resistance
Viruses
Bacteria
Fungi
Bioinformatics
Artificial inteligence
Péptido antimicrobiano
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
| id |
UNACIONAL2_c545c2bf39145deee66e6da925b3ea52 |
|---|---|
| oai_identifier_str |
oai:repositorio.unal.edu.co:unal/86299 |
| network_acronym_str |
UNACIONAL2 |
| network_name_str |
Universidad Nacional de Colombia |
| repository_id_str |
|
| dc.title.spa.fl_str_mv |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos |
| dc.title.translated.eng.fl_str_mv |
Searching and design of antimicrobial peptides in silico through the analysis of proteomes of viruses, bacteria and fungi |
| title |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos |
| spellingShingle |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos 660 - Ingeniería química Antibióticos Péptidos antimicrobianos Resistencia antimicrobiana Proteomas Virus Bacterias Hongos Bioinformática Inteligencia artificial Proteomes Antimicrobial peptides Antimicrobial resistance Viruses Bacteria Fungi Bioinformatics Artificial inteligence Péptido antimicrobiano |
| title_short |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos |
| title_full |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos |
| title_fullStr |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos |
| title_full_unstemmed |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos |
| title_sort |
Búsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongos |
| dc.creator.fl_str_mv |
Morillo Garces, Jairo Alexander |
| dc.contributor.advisor.none.fl_str_mv |
Orduz Peralta, Sergio |
| dc.contributor.author.none.fl_str_mv |
Morillo Garces, Jairo Alexander |
| dc.contributor.researchgroup.spa.fl_str_mv |
Biología Funcional |
| dc.contributor.orcid.spa.fl_str_mv |
Morillo Garces, Jairo Alexander [0000000253151123] |
| dc.subject.ddc.spa.fl_str_mv |
660 - Ingeniería química |
| topic |
660 - Ingeniería química Antibióticos Péptidos antimicrobianos Resistencia antimicrobiana Proteomas Virus Bacterias Hongos Bioinformática Inteligencia artificial Proteomes Antimicrobial peptides Antimicrobial resistance Viruses Bacteria Fungi Bioinformatics Artificial inteligence Péptido antimicrobiano |
| dc.subject.lemb.none.fl_str_mv |
Antibióticos |
| dc.subject.proposal.spa.fl_str_mv |
Péptidos antimicrobianos Resistencia antimicrobiana Proteomas Virus Bacterias Hongos Bioinformática Inteligencia artificial Proteomes |
| dc.subject.proposal.eng.fl_str_mv |
Antimicrobial peptides Antimicrobial resistance Viruses Bacteria Fungi Bioinformatics Artificial inteligence |
| dc.subject.wikidata.none.fl_str_mv |
Péptido antimicrobiano |
| description |
Ilustraciones, ilustraciones, mapas, tablas |
| publishDate |
2024 |
| dc.date.accessioned.none.fl_str_mv |
2024-06-25T19:48:56Z |
| dc.date.available.none.fl_str_mv |
2024-06-25T19:48:56Z |
| dc.date.issued.none.fl_str_mv |
2024-06-24 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
| status_str |
acceptedVersion |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/86299 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/86299 https://repositorio.unal.edu.co/ |
| identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.relation.references.spa.fl_str_mv |
Agrawal, P., Bhagat, D., Mahalwal, M., Sharma, N., & Raghava, G. P. (2021). AntiCP 2.0: an updated model for predicting anticancer peptides. Briefings in Bioinformatics, 22(3), bbaa153. https://doi.org/10.1093/bib/bbaa153 Agrawal, P., Bhalla, S., Chaudhary, K., Kumar, R., Sharma, M., & Raghava, G. P. S. (2018). In silico approach for prediction of antifungal peptides. Frontiers in Microbiology, 9, 323. https://doi.org/10.3389/fmicb.2018.00323 Al-Khdhairawi, A., Sanuri, D., Akbar, R., Lam, S. D., Sugumar, S., Ibrahim, N., Chieng, S., & Sairi, F. (2023). Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database. Computational Biology and Chemistry, 102, 107800. https://doi.org/10.1016/j.compbiolchem Arora, R., Kumar, A., Singh, I. K., & Singh, A. (2020). Pathogenesis related proteins: A defensin for plants but an allergen for humans. International Journal of Biological Macromolecules, 157, 659–672. https://doi.org/10.1016/j.ijbiomac.2019.11.223 Belloso, W. H. (2009). Historia de los antibióticos. Revista Hospital Italiano. Buenos Aires, 29(2), 102-11. Benfield, A. H., & Henriques, S. T. (2020). Mode-of-action of antimicrobial peptides: Membrane disruption vs. intracellular mechanisms. Frontiers in Medical Technology, 2, 610997. https://doi.org/10.3389/fmedt.2020.610997 Bhullar, K., Waglechner, N., Pawlowski, A., Koteva, K., Banks, E., Johnston, M., Barton, H., & Wright, G. (2012). Antibiotic resistance is prevalent in an isolated cave microbiome. PLoS One, 7(4), e34953. https://doi.org/10.1371/journal.pone.0034953 Bignone, P. A., Krupa, R. A., West, M. D., & Larocca, D. (2016). Selection of phage display peptides targeting human pluripotent stem cell-derived progenitor cell lines. Induced Pluripotent Stem (iPS) Cells: Methods and Protocols, 269-283. https://doi.org/10.1007/7651_2014_144 Bisso, A. (2018). Resistencia a los antimicrobianos. Revista de la Sociedad Peruana de Medicina Interna. 31(2), 50-59. https://doi.org/10.36393/spmi.v31i2.32 Boman, H. G. (2003). Antibacterial peptides: basic facts and emerging concepts. Journal of internal medicine, 254(3), 197-215. https://doi. org/ 10. 1046/j. 1365- 2796. 2003. 01228.x Branch JW, Orduz S, Ceballos AM, Mera CA, Orrego A. PepMultiFinder 2.0. 2022. Un algoritmo para buscar péptidos bioactivos en proteomas o listas de secuencias de proteínas. Dirección Nacional de Derechos de Autor. Ministerio del Interior. Registro 13-91-434. Septiembre 12, 2022. Brogden, K. (2005). Antimicrobial peptides: Pore formers or metabolic inhibitors in bacteria?. Nature Reviews Microbiology, 3(3), 238–250. https://doi.org/10.1038/nrmicro1098 Cabello, E., Núñez, M., & Torres, V. (2016). Actividad biológica de proteínas y péptidos. En Rivas., C. Oranday., M. & Verde. M. (Eds.), Investigación en Plantas de Importancia Médica. (pp. 313-350). OmniaScience. Cardillo, A., Martínez, M., Romero, S., Cascone, O., Camperi, S., & Giudicessi, S. (2018). Péptidos antimicrobianos de plantas. Revista Farmacéutica, 160(1), 28-46. https://www.researchgate.net/publication/324596881_Peptidos_antimicrobianos_de_plantas Chaudhary, K., Kumar, R., Singh, S., Tuknait, A., Gautam, A., Mathur, D., Anand, P., Varshney, G., & Raghava, G. (2016). A web server and mobile app for computing hemolytic potency of peptides. Scientific Reports, 6, (1), 22843. https://doi.org/10.1038/srep22843 Chávez, V. (2020). La batalla contra las superbacterias: No más antimicrobianos, no hay ESKAPE. TIP Revista Especializada En Ciencias Químico-Biológicas, 23, 1-11. https://doi.org/10.22201/fesz.23958723e.2020.0.202 Chu-Kung, A., Nguyen, R., Bozzelli, K., & Tirrell, M. (2010). Chain length dependence of antimicrobial peptide-fatty acid conjugate activity. Journal of Colloid and Interface Science, 345(2), 160–167. https://doi.org/10.1016/j.jcis.2009.11.057 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 Contreras, G., Shirdel, I., Braun, M. S., & Wink, M. (2020). Defensins: Transcriptional regulation and function beyond antimicrobial activity. Developmental and Comparative Immunology, 104, 103556. https://doi.org/10.1016/j.dci.2019.103556 Contreras, R., Escorcia, A. & Velarde, J. (2021). Prevalencia e impacto de resistencias a antimicrobianos en infecciones gastrointestinales: una revisión. Revista de Gastroenterología de México, 86(3), 265-275. https://doi.org/10.1016/j.rgmx.2021.02.003 Cuperus, T., Dijk, A., Matthijs, M., Veldhuizen, E., & Haagsman, H. (2016). Protective effect of in ovo treatment with the chicken cathelicidin analog D-CATH-2 against avian pathogenic E. coli. Scientific Reports, 6(1), 26622. https://doi.org/10.1038/srep26622 D’Costa, V., King, C., Kalan, L., Morar, M., Sung, W., Schwarz, C., Froese, D., Zazula, G., Calmels, F., Debruyne, R., Golding, G., Poinar, H., & Wright, G. (2011) Antibiotic resistance is ancient. Nature. 477(7365), 457-461. https://doi.org/10.1038/nature10388 Da Cunha, N. B., Cobacho, N. B., Viana, J. F. C., Lima, L. A., Sampaio, K. B. O., Dohms, S. S. M., Ferreira, A. C. R., de la Fuente-Núñez, C., Costa, F. F., Franco, O. L., & Dias, S. C. (2017). The next generation of antimicrobial peptides (AMPs) as molecular therapeutic tools for the treatment of diseases with social and economic impacts. Drug Discovery Today, 22(2), 234-248. https://doi.org/10.1016/j.drudis.2016.10.017 Da Silva Jr, J. B., Espinal, M., & Ramón-Pardo, P. (2020). Resistencia a los antimicrobianos: tiempo para la acción. Revista Panamericana de Salud Pública, 44, 1-2. https://doi.org/10.26633/rpsp.2020.122 Dimitrov, I., Bangov, I., Flower, D. R., & Doytchinova, I. (2014). AllerTOP v.2 - A server for in silico prediction of allergens. Journal of Molecular Modeling, 20(6), 2278. https://doi.org/10.1007/s00894-014-2278-5 Duque, G., Mendez, E., Ceballos-, A., & Orduz, S. (2020). Design of antimicrobial and cytolytic peptides by computational analysis of bacterial, algal, and invertebrate proteomes. Amino Acids, 52(10), 1403-1412. https://doi.org/10.1007/s00726-020-02900-w Duquesne, S., Destoumieux-Garzón, D., Peduzzi, J., & Rebuffat, S. (2007). Microcins, gene-encoded antibacterial peptides from enterobacteria. Natural product reports, 24(4), 708-734. https://doi.org/10.1002/chin.200745258 Dutta, P., Sahu, R. K., Dey, T., Lahkar, M. D., Manna, P., and Kalita, J. (2019). Beneficial role of insect-derived bioactive components against inflammation and its associated complications (colitis and arthritis) and cancer. Chem. Biol. Interact. 313:108824. https://doi.org/10.1016/j.cbi.2019.108824 Ebrahimi, F., Dehghani, M., & Makkizadeh, F. (2023). Analysis of Persian bioinformatics research with topic modeling. BioMed Research International, 2023, 3728131. https://doi.org/10.1155/2023/3728131 Espinosa, I., Báez, M., Hernández, R., López, Y., Lobo, E., & Corona, B. (2019). Resistencia antimicrobiana en bacterias de origen animal: desafíos para su contención desde el laboratorio. Revista de Salud Animal,41(3), 1-20 Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein Analysis Tools on the ExPASy Server 571 571 From: The Proteomics Protocols Handbook Protein Identification and Analysis Tools on the ExPASy Server. http://www.expasy.org/tools/. Gautam, A., Chaudhary, K., Kumar, R., Sharma, A., Kapoor, P., Tyagi, A., & Raghava, G. (2013). In silico approaches for designing highly effective cell penetrating peptides. Journal of Translational Medicine, 11(1), 1-12. https://doi.org/10.1186/1479-5876-11-74 Gautier, R., Douguet, D., Antonny, B., & Drin, G. (2008). HELIQUEST: a web server to screen sequences with specific α-helical properties. Bioinformatics, 24(18), 2101-2102. https://doi.org/10.1093/bioinformatics/btn392 Greco, I., Molchanova, N., Holmedal, E., Jenssen, H., Hummel, B. D., Watts, J. L., Håkansson, J., Hansen, P. R., & Svenson, J. (2020). Correlation between hemolytic activity, cytotoxicity and systemic in vivo toxicity of synthetic antimicrobial peptides. Scientific Reports, 10(1), 13206. https://doi.org/10.1038/s41598-020-69995-9 Guevara, F., Muñoz, L., Navarrete, J., Salazar, L., & Pinilla, G. (2020). Innovaciones en la terapia antimicrobiana. NOVA,18(34), 9-25. https://doi.org/10.22490/24629448.3921 Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., & Raghava, G. P. S. (2013). In silico approach for predicting toxicity of peptides and proteins. PLoS ONE, 8(9), e73957. https://doi.org/10.1371/journal.pone.0073957 Guryanova, S. v., & Ovchinnikova, T. v. (2022). Immunomodulatory and allergenic properties of antimicrobial peptides. International Journal of Molecular Sciences, 23(5), 2499. https://doi.org/10.3390/ijms23052499 Han, Y., Zhang, M., Lai, R., & Zhang, Z. (2021). Chemical modifications to increase the therapeutic potential of antimicrobial peptides. Peptides, 146, 170666. https://doi.org/10.1016/j.peptides.2021.170666 Hancock, R., & Diamond, G. (2000). The role of cationic antimicrobial peptides in innate host defenses. Trends in Microbiology, 8(9), 402–410. https://doi.org/10.1016/s0966-842x(00)01823-0 Hawkey, P. M. (2015). Multidrug-resistant Gram-negative bacteria: A product of globalization. Journal of Hospital Infection, 89(4), 241–247. https://doi.org/10.1016/j.jhin.2015.01.008 Huan Y, Kong Q, Mou H and Yi H (2020) Antimicrobial Peptides: classification, design, application and research progress in multiple fields. Frontiers in Microbiology, 11, 582779. https://doi.org/10.3389/fmicb Informe Sector Farmacéutico. (2024, febrero). Biblioteca Digital Cámara de Comercio de Bogotá. https://bibliotecadigital.ccb.org.co/items/4af024fd-7871-4c3e-90ff-8c4c95bcf0f5/ Ji, S., An, F., Zhang, T., Lou, M., Guo, J., Liu, K., ... & Wu, R. (2023). Antimicrobial peptides: An alternative to traditional antibiotics. European Journal of Medicinal Chemistry, 265, 116072. https://doi.org/10.1016/j.ejmech.2023.116072 Khabbaz, H., Karimi-Jafari, M. H., Saboury, A. A., & BabaAli, B. (2021). Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques. BMC Bioinformatics, 22(1), 1-11. https://doi.org/10.1186/s12859-021-04468-y Kim, H., Jang, J. H., Kim, S. C., & Cho, J. H. (2020). Development of a novel hybrid antimicrobial peptide for targeted killing of Pseudomonas aeruginosa. European Journal of Medicinal Chemistry, 185, 111814. https://doi.org/10.1016/j.ejmech 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 Lei, J., Sun, L., Huang, S., Zhu, C., Li, P., He, J., Mackey, V., Coy, D., & He, Q. (2019). The antimicrobial peptides and their potential clinical applications. American Journal of Traslational Research, 11(7), 3919-3931. Letourneau, A. R., & Calderwood, S. B. (2019). Beta-lactam antibiotics: mechanisms of action and resistance and adverse effects. UptoDate. Waltham (MA): UptoDate, 1-12. Li, J., Koh, J.-J., Liu, S., Lakshminarayanan, R., Verma, C. S., and Beuerman, R. W. (2017). Membrane active antimicrobial peptides: translating mechanistic insights to design. Frontiers in Neurosciences. 11, 73. https://doi.org/10.3389/fnins.2017.00073 Lima, P., Oliveira, J., Amaral, J., Freitas, C., & Souza, P. (2021). Synthetic antimicrobial peptides: Characteristics, design, and potential as alternative molecules to overcome microbial resistance. Life Sciences, 278, 119647. https://doi.org/10.1016/j.lfs.2021.119647 Lin, T.-T., Yang, L.-Y., Lu, I.-H., Cheng, W.-C., Hsu, Z.-R., Chen, S.-H., & Lin, C.-Y. (2021). AI4AMP: an antimicrobial peptide predictor using physicochemical property-based encoding method and deep learning. mSystems, 6(6), e00299-21. https://doi.org/10.1128/msystems.00299-21 López, D., Torres, M., & Prada. C. (2016). Genes de resistencia en bacilos Gram negativos: Impacto en la salud pública en Colombia. Universidad y Salud, 18(1), 190-202. https://doi.org/10.22267/rus.161801.30 López, Y., Gamboa, Y., Rodríguez, Y., & Artega, Y. (2022). Resistencia microbiana a los antibióticos: Un problema de salud creciente. Revista Científica Hallazgos 21, 7(1), 103-114. Luong, H., Thanh, T., & Tran, T. (2020). Antimicrobial peptides – Advances in development of therapeutic applications. Life Sciences, 260, 118407. https://doi.org/10.1016/j.lfs.2020.118407 Madrazo, A. L., & Campos, M. R. S. (2022). In silico prediction of peptide variants from chia (S. hispanica L.) with antimicrobial, antibiofilm, and antioxidant potential. Computational Biology and Chemistry, 98, 107695. https://doi.org/10.1016/j.compbiolchem.2022.107695 Magana, M., Pushpanathan, M., Santos, A., Leanse, L., Fernandez, M., Ioannidis, A., Giulianotti, M., Apidianakis, Y., Bradfute, S., Ferguson, A., Cherkasov, A., Seleem, M., Pinilla, C., de la Fuente, C., Lazaridis, T., Dai, T., Houghten, R., Hancock, R., & Tegos, G. (2020). The value of antimicrobial peptides in the age of resistance. The Lancet Infectious Diseases, 20(9), e216–e230. https://doi.org/10.1016/S1473-3099(20)30327-3 Makhlynets, O., & Caputo, G. (2021). Characteristics and therapeutic applications of antimicrobial peptides. Biophysics Reviews, 2(1), 011301. https://doi.org/10.1063/5.0035731 Malik, E., Dennison, S. R., Harris, F., & Phoenix, D. A. (2016). pH dependent antimicrobial peptides and proteins, their mechanisms of action and potential as therapeutic agents. Pharmaceuticals, 9(4), 67. https://doi.org/10.3390/ph9040067 Manavalan, B., & Patra, M. C. (2022). MLCPP 2.0: an updated cell-penetrating peptides and their uptake efficiency predictor. Journal of Molecular Biology, 434(11), 167604. https://doi.org/10.1016/j.jmb.2022.167604 Martínez, M. (2020). Nuevos péptidos antimicrobianos como estrategia frente al problema de la resistencia a los antibióticos, evaluación in vitro e in vivo. Análisis de un mecanismo de protección mediado por NDM-1 en Galleria mellonella. [Tesis doctoral, Universidad Nacional de Quilmes]. Repositorio Institucional Digital de Acceso Abierto de la Universidad Nacional de Quilmes http://ridaa.unq.edu.ar/handle/20.500.11807/2583 Maturana, P., Gonçalves, S., Martinez, M., Espeche, J. C., Santos, N. C., Semorile, L., Maffia, P. C., & Hollmann, A. (2020). Interactions of “de novo” designed peptides with bacterial membranes: Implications in the antimicrobial activity. Biochimica et Biophysica Acta – Biomembranes, 1862(11), 183443. https://doi.org/10.1016/j.bbamem Medina, P., & Fernández, F. (2014). Observaciones sobre los mecanismos de defensa de los insectos. Acta Zoológica Lilloana, 58(1), 17-43. Mejía, E., Benítez, J., & Ortiz, M. (2020). Péptidos antimicrobianos, una alternativa para el combate de la resistencia bacteriana. Acta Biológica Colombiana, 2(2), 294–302. https://doi.org/10.15446/abc.v25n2.77407 Ministerio de Salud y Protección Social. (2018). Plan Nacional de Respuesta a la Resistencia a los Antimicrobianos.https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/MET/plan-respuesta-resistencia-antimicrobianos.pdf. Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2022). ColabFold: making protein folding accessible to all. Nature Methods, 19(6), 679–682. https://doi.org/10.1038/s41592-022-01488-1 Mishra, B., & Wang, G. (2012). The importance of amino acid composition in natural AMPs: an evolutional, structural, and functional perspective. Frontiers in Immunology, 3, 221. https://doi.org/10.3389/fimmu.2012.00221 Mookherjee, N., Anderson, M. A., Haagsman, H. P., & Davidson, D. J. (2020). Antimicrobial host defence peptides: functions and clinical potential. Nature Reviews Drug Discovery, 19(5), 311-332. doi.org/10.1038/s41573-019-0058-8 Monsalve, D., Mesa, A., Mira, L. M., Mera, C., Orduz, S., & Branch-Bedoya, J. W. (2024). Antimicrobial peptides designed by computational analysis of proteomes. Antonie van Leeuwenhoek, 117(1), 55. https://doi.org/10.1007/s10482-024-01946-0 Mulani, M., Kamble, E., Kumkar, S., Tawre, M., & Pardesi, K. (2019). Emerging strategies to combat ESKAPE pathogens in the era of antimicrobial resistance: A review. Frontiers in Microbiology, 10, 539. https://doi.org/10.3389/fmicb Muñoz, G., Sánchez, L., & Estrada-Tapia, G. (2020). Péptidos de defensa: una alternativa natural para el control de patógenos de plantas y humanos. Cicy, 93, 88–93. Nastro, M. (2019). What can we do to prevent multidrug-resistance? Revista Argentina de Microbiologia, 51(1), 1–2. https://doi.org/10.1016/j.ram.2019.02.001 Negash, A. W., & Tsehai, B. A. (2020). Current applications of bacteriocin. International Journal of Microbiology, 2020, 4374891. https://doi.org/10.1155/2020/4374891 Opal, S. M., & Pop-Vicas, A. (2015). Molecular mechanisms of antibiotic resistance in bacteria. In Mandell, Douglas, and Bennett's Principles and Practice of Infectious Diseases (pp. 235-251). WB Saunders. https://doi.org/10.1016/b978-0-443-06839-3.00019-9 Organización Panamericana de la Salud. (2019). Tratamiento de las enfermedades infecciosas 2020-2022. (8° ed). Autoedición. https://doi.org/10.37774/9789275321003 Organización Panamericana de la Salud. (2021). La resistencia antimicrobiana pone en riesgo la salud mundial. Recuperado de: https://www.paho.org/es/noticias/3-3-2021-resistencia-antimicrobiana-pone-riesgo-salud-mundial Orozco, S., & Arango, J. (2016) Aplicación de la inteligencia artificial en la bioinformática, avances, definiciones y herramientas. UGCiencia, 22(1), 159-171. https://doi.org/10.18634/ugcj.22v.1i.494 Ortiz, C. (2019). Diseño, síntesis, caracterización y evaluación in vitro de la actividad de los péptidos antimicrobianos contra bacterias patógenas resistentes a antibióticos. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 43(169), 614-627. https://doi.org/10.18257/raccefyn.864 Pasupuleti, M., Schmidtchen, A., & Malmsten, M. (2012). Antimicrobial peptides: key components of the innate immune system. Critical Reviews in Biotechnology, 32(2), 143-171. https://doi.org/10.3109/07388551.2011.594423 Patel, H., Bhatt, D., Shakhreliya, S., Lam, N. L., Maurya, R., & Singh, V. (2021). An Introduction and Applications of Bioinformatics. Advances in Bioinformatics, 1-14. Penesyan, A., Gillings, M., & Paulsen, I. T. (2015). Antibiotic discovery: combatting bacterial resistance in cells and in biofilm communities. Molecules, 20(4), 5286-5298. https://doi.org/10.3390/molecules20045286 Perron, G., Whyte, L., Turnbaugh, P., Goordial, J., Hanage, W., Dantas, G., & Michael, D. (2015). Functional characterization of bacteria isolated from ancient Arctic soil exposes diverse resistance mechanisms to modern antibiotics. PLoS One, 10(3), e0069533. https://doi.org/10.1371/journal.pone.0069533 Pfalzgraff, A., Brandenburg, K., & Weind, G. (2018). Antimicrobial peptides and their therapeutic potential for bacterial skin infections and wounds. Frontiers in Pharmacology, 9, 281. https://doi.org/10.3389/fphar.2018.00281 Phuong, P. T., Oliver, S., He, J., Wong, E. H., Mathers, R. T., & Boyer, C. (2020). Effect of hydrophobic groups on antimicrobial and hemolytic activity: Developing a predictive tool for ternary antimicrobial polymers. Biomacromolecules, 21(12), 5241-5255. https://doi.org/10.1021/acs.biomac.0c01320 Pirtskhalava, M., Amstrong, A. A., Grigolava, M., Chubinidze, M., Alimbarashvili, E., Vishnepolsky, B., Gabrielian, A., Rosenthal, A., Hurt, D. E., & Tartakovsky, M. (2021). DBAASP v3: Database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics. Nucleic Acids Research, 49(D1), D288–D297. https://doi.org/10.1093/nar/gkaa991 Quiñones, D. (2017). Resistencia antimicrobiana: evolución y perspectivas actuales ante el enfoque" Una salud". Revista Cubana de Medicina Tropical, 69(3), 1-17. Quintero, V. (2021). La próxima pandemia: Bacterias multirresistentes a antibióticos. Alianzas y Tendencias BUAP, 6(21), 1–7. Radusky, L. (2017). Herramientas bioinformáticas para el análisis estructural de proteínas a escala genómica. [Tesis Doctoral, Universidad de Buenos Aires]. Rivas-Santiago, B., Sada, E., Hernández-Pando, R., & Tsutsumi, V. (2006). Péptidos antimicrobianos en la inmunidad innata de enfermedades infecciosas. Salud Pública de México, 48, 62-71. https://doi.org/10.1590/s0036-36342006000100010 Rodríguez, E., & Méndez, D. (2021). Aspectos generales relacionados con los antibióticos y plaguicidas. En E. Rodríguez, D. Méndez, Marrugo, A y Márquez, J. (Eds.), Perspectiva analítica y proteómica de residuos de antimicrobianos y plaguicidas en alimentos de origen animal (19-58). Editorial Universitaria. Rončević, T., Puizina, J., & Tossi, A. (2019). Antimicrobial peptides as anti-infective agents in pre-post-antibiotic era?. International Journal of Molecular Sciences, 20(22), 5713. https://doi.org/10.3390/ijms20225713 Salem, M., Keshavarzi Arshadi, A., & Yuan, J. S. (2022). AMPDeep: hemolytic activity prediction of antimicrobial peptides using transfer learning. BMC Bioinformatics, 23(1), 1-17. https://doi.org/10.21203/rs.3.rs-1615895/v1 Sapay N, Guermeur Y, & Deléage G (2006). Prediction of amphipathic in-plane membrane anchors in monotopic proteins using a SVM classifier. BMC Bioinformatics, 7(1), 1-11. https://doi.org/10.1186/1471-2105-7-255 Schmidt, C. (2017). Living in a microbial world. Nature Biotechnology, 35, 401-403. https://doi.org/10.1038/nbt.3868 Scocchi, M., Mardirossian, M., Runti, G., & Benincasa, M. (2017). Non-membranolytic mechanisms of action of antimicrobial peptides–novel therapeutic opportunities. Antimicrobial Peptides: Discovery, Design, and Novel Therapeutic Strategies. CABI, Oxfordshire, 149-160. https://doi.org/10.1079/9781786390394.0149 Segev-Zarko, L. A., Mangoni, M. L., & Shai, Y. (2017). Antimicrobial peptides: multiple mechanisms against a variety of targets. Antimicrobial Peptides: Discovery, Design and Novel Therapeutic Strategies. UK: CAB Inhternational, 119-127. https://doi.org/10.1079/9781786390394.0119 Semreen, M., Gamal, M., Abdin, S., Alkhazraji, H., Kamal, L., Hammad, S., Awady, F., Waleed, D., & Kourbaj, L. (2018). Recent updates of marine antimicrobial peptides. Saudi Pharmaceutical Journal, 26(3), 396-409. https://doi.org/10.1016/j.jsps.2018.01.001 Serra, M. (2017). La resistencia microbiana en el contexto actual y la importancia del conocimiento y aplicación en la política antimicrobiana. Revista Habanera de Ciencias Médicas, 16(3), 402-419. Shelomi, M., Jacobs, C., Vilcinskas, A., and Vogel, H. (2020). The unique antimicrobial peptide repertoire of stick insects. Developmental and Comparative Immunology, 103, 103471. https://doi.org/10.1016/j.dci.2019.103471 Starr, C. G., & Wimley, W. C. (2017). Discovery of novel antimicrobial peptides using combinatorial chemistry and high-throughput screening. Antimicrobial peptides: Discovery, design and novel therapeutic strategies, (Ed. 2), 86-100. https://doi.org/10.1079/9781786390394.0086 Tamayo S, Castañeda CA, Orduz S. (2018). Type-Peptide 1.0. Herramientas computacionales pedagógicas para el estudio, diseño y optimización de péptidos antimicrobianas basada en sus propiedades fisicoquímicas. Dirección Nacional de Derechos de Autor. Ministerio del Interior. Registro 13-70-274. Diciembre 5, 2018. Téllez, G. y Castaño, J. (2010). Péptidos antimicrobianos. Infectio, 14(1), 55-67. https://doi.org/10.1016/s0123-9392(10)70093-x Thakur, N., Qureshi, A., & Kumar, M. (2012). AVPpred: Collection and prediction of highly effective antiviral peptides. Nucleic Acids Research, 40(W1), W199-W204. https://doi.org/10.1093/nar/gks450 Timmons, P., & Hewage, C. (2020). HAPPENN is a novel tool for hemolytic activity prediction for therapeutic peptides which employs neural networks. Scientific Reports, 10(1), 1–18. https://doi.org/10.1038/s41598-020-67701-3 Tonarelli, G., & Simonetta, A. (2013). Péptidos antimicrobianos de organismos procariotas y eucariotas como agentes terapéuticos y conservantes de alimentos. Revista FABICIB, 17, 137-177. https://doi.org/10.14409/fabicib.v17i0.4316 Tornesello, A., Borrelli, A., Buonaguro, L., Buonaguro, F., & Tornesello, M. (2020). Antimicrobial peptides as anticancer agents: Functional properties and biological activities. Molecules, 25(12), 1–25. https://doi.org/10.3390/molecules25122850 Torres, MDT, Sothiselvam, S., Lu, TK y de la Fuente-Nunez, C. (2019). Principios de diseño de péptidos para aplicaciones antimicrobianas. Journal of Molecular Biology. 431, 3547–3567. doi: 10.1016/j.jmb.2018.12.015 UniProt [Internet]. Available from: https://www.uniprot.org/ Vázquez, A., Perdomo-Morales, R., & Montero-Alejo, V. (2018). Natural antimicrobial peptides. Biotecnologia. Aplicada, 35, 4101-4107. Veltri, D., Kamath, U., & Shehu, A. (2018). Deep learning improves antimicrobial peptide recognition. Bioinformatics, 34(16), 2740–2747. https://doi.org/10.1093/bioinformatics/bty179 Vishnepolsky, B., Grigolava, M., Managadze, G., Gabrielian, A., Rosenthal, A., Hurt, D. E., Tartakovsky, M., & Pirtskhalava, M. (2022). Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction. Briefings in Bioinformatics, 23(4), bbac233. https://doi.org/10.1093/bib/bbac233 Waghu, F. H., & Idicula-Thomas, S. (2020). Collection of antimicrobial peptides database and its derivatives: Applications and beyond. Protein Science, 29(1), 36–42. https://doi.org/10.1002/pro.3714 Wang GuangShun. (2017). Structural insight into the mechanisms of action of antimicrobial peptides and structure-based design. In Antimicrobial peptides: discovery, design and novel therapeutic strategies (pp. 169-187). Wallingford UK: Cabi. https://doi.org/10.1079/9781786390394.0169 Wang, G. (2017). Discovery, classification and functional diversity of antimicrobia peptides. Antimicrobial peptides: Discovery, Design and Novel Therapeutic Strategies. CABI Publishing, 1-19. https://doi.org/10.1079/9781786390394.0001 Wang, G. S. (2010). Structural studies of antimicrobial peptides provide insight into their mechanisms of action. Antimicrobial peptides: discovery, design and novel therapeutic strategies, 141-168. https://doi.org/10.1079/9781845936570.0141 Wang, G. S., Li, X., & Zasloff, M. (2010). A database view of naturally occurring antimicrobial peptides: nomenclature, classification and amino acid sequence analysis. In Antimicrobial peptides: discovery, design and novel therapeutic strategies (pp. 1-21). Wallingford UK: Cabi. https://doi.org/10.1079/9781845936570.0001 Wang, G., Hanke, M.L., Mishra, B., Lushnikova, T., Heim, C.E., et al. (2014) Transformation of human cathelicidin LL-37 into selective, stable, and potent antimicrobial compounds. ACS Chemical Biology 9(9), 1997–2002. https://doi.org/10.1021/cb500475y Wang, G., Li, X., & Wang, Z. (2016). APD3: The antimicrobial peptide database as a tool for research and education. Nucleic Acids Research, 44(D1), D1087–D1093. https://doi.org/10.1093/nar/gkv1278 Wang, Y., Wang, Q., Wu, A., Hao, Z., & Liu, X. (2017). Isolation of a peptide from Ph.D.-C7C phage display library for detection of Cry1Ab. Analytical Biochemistry, 539, 29–32. https://doi.org/10.1016/j.ab.2017.03.004 Weeks, R., Algburi, A., & Chikindas, M. (2021). Antimicrobial peptides and peptidomimetics for the control of antimicrobial resistance. Sustainable Agriculture Reviews 49: Mitigation of Antimicrobial Resistance Vol 2. Natural and Synthetic Approaches, 205-249. https://doi.org/10.1007/978-3-030-58259-3_7 Wuerth, K. C., & Hancock, R. E. (2017). Immunomodulatory activities of cationic host defence peptides and novel therapeutic strategies. Antimicrobial peptides: discovery, design and novel therapeutic strategies, (Ed. 2), 238-259. https://doi.org/10.1079/9781786390394.0238 Xiao, H., Shao, F., Wu, M., Ren, W., Xiong, X., Tan, B., & Yin, Y. (2015). The application of antimicrobial peptides as growth and health promoters for swine. Journal of Animal Science and Biotechnology, 6(1), 1–6. https://doi.org/10.1186/s40104-015-0018-z Zahedifard, F., Lee, H., No, J. H., Salimi, M., Seyed, N., Asoodeh, A., et al. (2020). Comparative study of different forms of jellein antimicrobial peptide on leishmania parasite. Experimental Parasitology. 209:107823. https://doi.org/10.1016/j.exppara.2019.107823 Zhou, C., Kang, J., Wang, X., Wei, W., & Jiang, W. (2015). Phage display screening identifies a novel peptide to suppress ovarian cancer cells in vitro and in vivo in mouse models. BMC Cancer, 15(1). https://doi.org/10.1186/s12885-015-1891-8 |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional |
| dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.extent.spa.fl_str_mv |
136 páginas |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.publisher.program.spa.fl_str_mv |
Medellín - Ciencias - Maestría en Ciencias - Biotecnología |
| dc.publisher.faculty.spa.fl_str_mv |
Facultad de Ciencias |
| dc.publisher.place.spa.fl_str_mv |
Medellín, Colombia |
| dc.publisher.branch.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Medellín |
| institution |
Universidad Nacional de Colombia |
| bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/86299/1/license.txt https://repositorio.unal.edu.co/bitstream/unal/86299/3/1085272703.2024.pdf https://repositorio.unal.edu.co/bitstream/unal/86299/4/1085272703.2024.pdf.jpg |
| bitstream.checksum.fl_str_mv |
eb34b1cf90b7e1103fc9dfd26be24b4a aca3e2f1d02c460a7e8b9265b7443049 0de493f267ce12ecd67fe1428d8064b3 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| repository.mail.fl_str_mv |
repositorio_nal@unal.edu.co |
| _version_ |
1814089438885576704 |
| spelling |
Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Orduz Peralta, Sergiobfc3c74726167d38ddd831c691a9e32fMorillo Garces, Jairo Alexander054f12a8cc033f9a7285d968ead0c07f600Biología FuncionalMorillo Garces, Jairo Alexander [0000000253151123]2024-06-25T19:48:56Z2024-06-25T19:48:56Z2024-06-24https://repositorio.unal.edu.co/handle/unal/86299Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/Ilustraciones, ilustraciones, mapas, tablasDebido a la creciente resistencia que presentan algunos organismos patógenos a diferentes antimicrobianos se ha aumentado la necesidad de encontrar nuevos compuestos antimicrobianos como opciones de tratamiento. En respuesta, se han adoptado nuevos enfoques alternativos, entre los cuales se encuentran el uso de péptidos antimicrobianos (AMPs). Los AMPs son una parte natural del sistema inmunológico de todos los organismos, diversos estudios han demostrado que los AMPs presentan gran ventaja en comparación con los antibióticos habituales basados en su actividad de amplio espectro, mecanismos de acción, selectividad de las células huésped y menor probabilidad de generar resistencia. Por estas razones, esta investigación se enfocó en la identificación, selección, modificación y evaluación de AMPs in silico encontrados en el proteoma de virus, bacterias y hongos mediante el uso de herramientas bioinformáticas y de inteligencia artificial específicas que valoraron parámetros como estructura, capacidad hemolítica, toxicidad, capacidad de unión a membranas, su potencial como antimicrobianos y su posible efecto anticancerígeno y de penetración celular. Por consiguiente, se espera que los nuevos péptidos encontrados en este estudio sean candidatos a futuros ensayos in vitro e in vivo como una alternativa efectiva a los antibióticos tradicionales. (texto tomado de la fuente)Due to the increasing resistance of pathogenic organisms have developed to various antimicrobials, the need to find new antimicrobial compounds as treatment options has increased. In response, new alternative approaches have been adopted, among which are the use of antimicrobial peptides (AMPs). AMPs are a natural part of the immune system of all organisms, several studies have shown that AMPs have a great advantage compared to usual antibiotics based on their broad-spectrum activity, mechanisms of action, host cell selectivity, and are less likely to generate resistance. For these reasons, this research aimed to the identification, selection, modification, and evaluation about in silico AMPs found in the proteome of viruses, bacteria, and fungi through the use of specific bioinformatics and artificial intelligence tools that assessed parameters such as structure, hemolytic capacity, toxicity, membrane-binding capability, their potential as antimicrobials, and their possible anticancer and cell-penetration effects. Therefore, the novel peptides found in this research are expected to be candidates for future in vitro and in vivo trials as an effective alternative to traditional antibiotics.MaestríaMagíster en Ciencias - BiotecnologíaSustancias bioactivas para el control de patógenosÁrea curricular Biotecnología136 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Ciencias - Maestría en Ciencias - BiotecnologíaFacultad de CienciasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín660 - Ingeniería químicaAntibióticosPéptidos antimicrobianosResistencia antimicrobianaProteomasVirusBacteriasHongosBioinformáticaInteligencia artificialProteomesAntimicrobial peptidesAntimicrobial resistanceVirusesBacteriaFungiBioinformaticsArtificial inteligencePéptido antimicrobianoBúsqueda y diseño de péptidos antimicrobianos in silico mediante el análisis de proteomas de virus, bacterias y hongosSearching and design of antimicrobial peptides in silico through the analysis of proteomes of viruses, bacteria and fungiTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAgrawal, P., Bhagat, D., Mahalwal, M., Sharma, N., & Raghava, G. P. (2021). AntiCP 2.0: an updated model for predicting anticancer peptides. Briefings in Bioinformatics, 22(3), bbaa153. https://doi.org/10.1093/bib/bbaa153Agrawal, P., Bhalla, S., Chaudhary, K., Kumar, R., Sharma, M., & Raghava, G. P. S. (2018). In silico approach for prediction of antifungal peptides. Frontiers in Microbiology, 9, 323. https://doi.org/10.3389/fmicb.2018.00323Al-Khdhairawi, A., Sanuri, D., Akbar, R., Lam, S. D., Sugumar, S., Ibrahim, N., Chieng, S., & Sairi, F. (2023). Machine learning and molecular simulation ascertain antimicrobial peptide against Klebsiella pneumoniae from public database. Computational Biology and Chemistry, 102, 107800. https://doi.org/10.1016/j.compbiolchemArora, R., Kumar, A., Singh, I. K., & Singh, A. (2020). Pathogenesis related proteins: A defensin for plants but an allergen for humans. International Journal of Biological Macromolecules, 157, 659–672. https://doi.org/10.1016/j.ijbiomac.2019.11.223Belloso, W. H. (2009). Historia de los antibióticos. Revista Hospital Italiano. Buenos Aires, 29(2), 102-11.Benfield, A. H., & Henriques, S. T. (2020). Mode-of-action of antimicrobial peptides: Membrane disruption vs. intracellular mechanisms. Frontiers in Medical Technology, 2, 610997. https://doi.org/10.3389/fmedt.2020.610997Bhullar, K., Waglechner, N., Pawlowski, A., Koteva, K., Banks, E., Johnston, M., Barton, H., & Wright, G. (2012). Antibiotic resistance is prevalent in an isolated cave microbiome. PLoS One, 7(4), e34953. https://doi.org/10.1371/journal.pone.0034953Bignone, P. A., Krupa, R. A., West, M. D., & Larocca, D. (2016). Selection of phage display peptides targeting human pluripotent stem cell-derived progenitor cell lines. Induced Pluripotent Stem (iPS) Cells: Methods and Protocols, 269-283. https://doi.org/10.1007/7651_2014_144Bisso, A. (2018). Resistencia a los antimicrobianos. Revista de la Sociedad Peruana de Medicina Interna. 31(2), 50-59. https://doi.org/10.36393/spmi.v31i2.32Boman, H. G. (2003). Antibacterial peptides: basic facts and emerging concepts. Journal of internal medicine, 254(3), 197-215. https://doi. org/ 10. 1046/j. 1365- 2796. 2003. 01228.xBranch JW, Orduz S, Ceballos AM, Mera CA, Orrego A. PepMultiFinder 2.0. 2022. Un algoritmo para buscar péptidos bioactivos en proteomas o listas de secuencias de proteínas. Dirección Nacional de Derechos de Autor. Ministerio del Interior. Registro 13-91-434. Septiembre 12, 2022.Brogden, K. (2005). Antimicrobial peptides: Pore formers or metabolic inhibitors in bacteria?. Nature Reviews Microbiology, 3(3), 238–250. https://doi.org/10.1038/nrmicro1098Cabello, E., Núñez, M., & Torres, V. (2016). Actividad biológica de proteínas y péptidos. En Rivas., C. Oranday., M. & Verde. M. (Eds.), Investigación en Plantas de Importancia Médica. (pp. 313-350). OmniaScience.Cardillo, A., Martínez, M., Romero, S., Cascone, O., Camperi, S., & Giudicessi, S. (2018). Péptidos antimicrobianos de plantas. Revista Farmacéutica, 160(1), 28-46. https://www.researchgate.net/publication/324596881_Peptidos_antimicrobianos_de_plantasChaudhary, K., Kumar, R., Singh, S., Tuknait, A., Gautam, A., Mathur, D., Anand, P., Varshney, G., & Raghava, G. (2016). A web server and mobile app for computing hemolytic potency of peptides. Scientific Reports, 6, (1), 22843. https://doi.org/10.1038/srep22843Chávez, V. (2020). La batalla contra las superbacterias: No más antimicrobianos, no hay ESKAPE. TIP Revista Especializada En Ciencias Químico-Biológicas, 23, 1-11. https://doi.org/10.22201/fesz.23958723e.2020.0.202Chu-Kung, A., Nguyen, R., Bozzelli, K., & Tirrell, M. (2010). Chain length dependence of antimicrobial peptide-fatty acid conjugate activity. Journal of Colloid and Interface Science, 345(2), 160–167. https://doi.org/10.1016/j.jcis.2009.11.057Ciumac, 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.2018.10.103Contreras, G., Shirdel, I., Braun, M. S., & Wink, M. (2020). Defensins: Transcriptional regulation and function beyond antimicrobial activity. Developmental and Comparative Immunology, 104, 103556. https://doi.org/10.1016/j.dci.2019.103556Contreras, R., Escorcia, A. & Velarde, J. (2021). Prevalencia e impacto de resistencias a antimicrobianos en infecciones gastrointestinales: una revisión. Revista de Gastroenterología de México, 86(3), 265-275. https://doi.org/10.1016/j.rgmx.2021.02.003Cuperus, T., Dijk, A., Matthijs, M., Veldhuizen, E., & Haagsman, H. (2016). Protective effect of in ovo treatment with the chicken cathelicidin analog D-CATH-2 against avian pathogenic E. coli. Scientific Reports, 6(1), 26622. https://doi.org/10.1038/srep26622D’Costa, V., King, C., Kalan, L., Morar, M., Sung, W., Schwarz, C., Froese, D., Zazula, G., Calmels, F., Debruyne, R., Golding, G., Poinar, H., & Wright, G. (2011) Antibiotic resistance is ancient. Nature. 477(7365), 457-461. https://doi.org/10.1038/nature10388Da Cunha, N. B., Cobacho, N. B., Viana, J. F. C., Lima, L. A., Sampaio, K. B. O., Dohms, S. S. M., Ferreira, A. C. R., de la Fuente-Núñez, C., Costa, F. F., Franco, O. L., & Dias, S. C. (2017). The next generation of antimicrobial peptides (AMPs) as molecular therapeutic tools for the treatment of diseases with social and economic impacts. Drug Discovery Today, 22(2), 234-248. https://doi.org/10.1016/j.drudis.2016.10.017Da Silva Jr, J. B., Espinal, M., & Ramón-Pardo, P. (2020). Resistencia a los antimicrobianos: tiempo para la acción. Revista Panamericana de Salud Pública, 44, 1-2. https://doi.org/10.26633/rpsp.2020.122Dimitrov, I., Bangov, I., Flower, D. R., & Doytchinova, I. (2014). AllerTOP v.2 - A server for in silico prediction of allergens. Journal of Molecular Modeling, 20(6), 2278. https://doi.org/10.1007/s00894-014-2278-5Duque, G., Mendez, E., Ceballos-, A., & Orduz, S. (2020). Design of antimicrobial and cytolytic peptides by computational analysis of bacterial, algal, and invertebrate proteomes. Amino Acids, 52(10), 1403-1412. https://doi.org/10.1007/s00726-020-02900-wDuquesne, S., Destoumieux-Garzón, D., Peduzzi, J., & Rebuffat, S. (2007). Microcins, gene-encoded antibacterial peptides from enterobacteria. Natural product reports, 24(4), 708-734. https://doi.org/10.1002/chin.200745258Dutta, P., Sahu, R. K., Dey, T., Lahkar, M. D., Manna, P., and Kalita, J. (2019). Beneficial role of insect-derived bioactive components against inflammation and its associated complications (colitis and arthritis) and cancer. Chem. Biol. Interact. 313:108824. https://doi.org/10.1016/j.cbi.2019.108824Ebrahimi, F., Dehghani, M., & Makkizadeh, F. (2023). Analysis of Persian bioinformatics research with topic modeling. BioMed Research International, 2023, 3728131. https://doi.org/10.1155/2023/3728131Espinosa, I., Báez, M., Hernández, R., López, Y., Lobo, E., & Corona, B. (2019). Resistencia antimicrobiana en bacterias de origen animal: desafíos para su contención desde el laboratorio. Revista de Salud Animal,41(3), 1-20Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein Analysis Tools on the ExPASy Server 571 571 From: The Proteomics Protocols Handbook Protein Identification and Analysis Tools on the ExPASy Server. http://www.expasy.org/tools/.Gautam, A., Chaudhary, K., Kumar, R., Sharma, A., Kapoor, P., Tyagi, A., & Raghava, G. (2013). In silico approaches for designing highly effective cell penetrating peptides. Journal of Translational Medicine, 11(1), 1-12. https://doi.org/10.1186/1479-5876-11-74Gautier, R., Douguet, D., Antonny, B., & Drin, G. (2008). HELIQUEST: a web server to screen sequences with specific α-helical properties. Bioinformatics, 24(18), 2101-2102. https://doi.org/10.1093/bioinformatics/btn392Greco, I., Molchanova, N., Holmedal, E., Jenssen, H., Hummel, B. D., Watts, J. L., Håkansson, J., Hansen, P. R., & Svenson, J. (2020). Correlation between hemolytic activity, cytotoxicity and systemic in vivo toxicity of synthetic antimicrobial peptides. Scientific Reports, 10(1), 13206. https://doi.org/10.1038/s41598-020-69995-9Guevara, F., Muñoz, L., Navarrete, J., Salazar, L., & Pinilla, G. (2020). Innovaciones en la terapia antimicrobiana. NOVA,18(34), 9-25. https://doi.org/10.22490/24629448.3921Gupta, S., Kapoor, P., Chaudhary, K., Gautam, A., Kumar, R., & Raghava, G. P. S. (2013). In silico approach for predicting toxicity of peptides and proteins. PLoS ONE, 8(9), e73957. https://doi.org/10.1371/journal.pone.0073957Guryanova, S. v., & Ovchinnikova, T. v. (2022). Immunomodulatory and allergenic properties of antimicrobial peptides. International Journal of Molecular Sciences, 23(5), 2499. https://doi.org/10.3390/ijms23052499Han, Y., Zhang, M., Lai, R., & Zhang, Z. (2021). Chemical modifications to increase the therapeutic potential of antimicrobial peptides. Peptides, 146, 170666. https://doi.org/10.1016/j.peptides.2021.170666Hancock, R., & Diamond, G. (2000). The role of cationic antimicrobial peptides in innate host defenses. Trends in Microbiology, 8(9), 402–410. https://doi.org/10.1016/s0966-842x(00)01823-0Hawkey, P. M. (2015). Multidrug-resistant Gram-negative bacteria: A product of globalization. Journal of Hospital Infection, 89(4), 241–247. https://doi.org/10.1016/j.jhin.2015.01.008Huan Y, Kong Q, Mou H and Yi H (2020) Antimicrobial Peptides: classification, design, application and research progress in multiple fields. Frontiers in Microbiology, 11, 582779. https://doi.org/10.3389/fmicbInforme Sector Farmacéutico. (2024, febrero). Biblioteca Digital Cámara de Comercio de Bogotá. https://bibliotecadigital.ccb.org.co/items/4af024fd-7871-4c3e-90ff-8c4c95bcf0f5/Ji, S., An, F., Zhang, T., Lou, M., Guo, J., Liu, K., ... & Wu, R. (2023). Antimicrobial peptides: An alternative to traditional antibiotics. European Journal of Medicinal Chemistry, 265, 116072. https://doi.org/10.1016/j.ejmech.2023.116072Khabbaz, H., Karimi-Jafari, M. H., Saboury, A. A., & BabaAli, B. (2021). Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques. BMC Bioinformatics, 22(1), 1-11. https://doi.org/10.1186/s12859-021-04468-yKim, H., Jang, J. H., Kim, S. C., & Cho, J. H. (2020). Development of a novel hybrid antimicrobial peptide for targeted killing of Pseudomonas aeruginosa. European Journal of Medicinal Chemistry, 185, 111814. https://doi.org/10.1016/j.ejmechKumar, 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/biom8010004Lei, J., Sun, L., Huang, S., Zhu, C., Li, P., He, J., Mackey, V., Coy, D., & He, Q. (2019). The antimicrobial peptides and their potential clinical applications. American Journal of Traslational Research, 11(7), 3919-3931.Letourneau, A. R., & Calderwood, S. B. (2019). Beta-lactam antibiotics: mechanisms of action and resistance and adverse effects. UptoDate. Waltham (MA): UptoDate, 1-12.Li, J., Koh, J.-J., Liu, S., Lakshminarayanan, R., Verma, C. S., and Beuerman, R. W. (2017). Membrane active antimicrobial peptides: translating mechanistic insights to design. Frontiers in Neurosciences. 11, 73. https://doi.org/10.3389/fnins.2017.00073Lima, P., Oliveira, J., Amaral, J., Freitas, C., & Souza, P. (2021). Synthetic antimicrobial peptides: Characteristics, design, and potential as alternative molecules to overcome microbial resistance. Life Sciences, 278, 119647. https://doi.org/10.1016/j.lfs.2021.119647Lin, T.-T., Yang, L.-Y., Lu, I.-H., Cheng, W.-C., Hsu, Z.-R., Chen, S.-H., & Lin, C.-Y. (2021). AI4AMP: an antimicrobial peptide predictor using physicochemical property-based encoding method and deep learning. mSystems, 6(6), e00299-21. https://doi.org/10.1128/msystems.00299-21López, D., Torres, M., & Prada. C. (2016). Genes de resistencia en bacilos Gram negativos: Impacto en la salud pública en Colombia. Universidad y Salud, 18(1), 190-202. https://doi.org/10.22267/rus.161801.30López, Y., Gamboa, Y., Rodríguez, Y., & Artega, Y. (2022). Resistencia microbiana a los antibióticos: Un problema de salud creciente. Revista Científica Hallazgos 21, 7(1), 103-114.Luong, H., Thanh, T., & Tran, T. (2020). Antimicrobial peptides – Advances in development of therapeutic applications. Life Sciences, 260, 118407. https://doi.org/10.1016/j.lfs.2020.118407Madrazo, A. L., & Campos, M. R. S. (2022). In silico prediction of peptide variants from chia (S. hispanica L.) with antimicrobial, antibiofilm, and antioxidant potential. Computational Biology and Chemistry, 98, 107695. https://doi.org/10.1016/j.compbiolchem.2022.107695Magana, M., Pushpanathan, M., Santos, A., Leanse, L., Fernandez, M., Ioannidis, A., Giulianotti, M., Apidianakis, Y., Bradfute, S., Ferguson, A., Cherkasov, A., Seleem, M., Pinilla, C., de la Fuente, C., Lazaridis, T., Dai, T., Houghten, R., Hancock, R., & Tegos, G. (2020). The value of antimicrobial peptides in the age of resistance. The Lancet Infectious Diseases, 20(9), e216–e230. https://doi.org/10.1016/S1473-3099(20)30327-3Makhlynets, O., & Caputo, G. (2021). Characteristics and therapeutic applications of antimicrobial peptides. Biophysics Reviews, 2(1), 011301. https://doi.org/10.1063/5.0035731Malik, E., Dennison, S. R., Harris, F., & Phoenix, D. A. (2016). pH dependent antimicrobial peptides and proteins, their mechanisms of action and potential as therapeutic agents. Pharmaceuticals, 9(4), 67. https://doi.org/10.3390/ph9040067Manavalan, B., & Patra, M. C. (2022). MLCPP 2.0: an updated cell-penetrating peptides and their uptake efficiency predictor. Journal of Molecular Biology, 434(11), 167604. https://doi.org/10.1016/j.jmb.2022.167604Martínez, M. (2020). Nuevos péptidos antimicrobianos como estrategia frente al problema de la resistencia a los antibióticos, evaluación in vitro e in vivo. Análisis de un mecanismo de protección mediado por NDM-1 en Galleria mellonella. [Tesis doctoral, Universidad Nacional de Quilmes]. Repositorio Institucional Digital de Acceso Abierto de la Universidad Nacional de Quilmes http://ridaa.unq.edu.ar/handle/20.500.11807/2583Maturana, P., Gonçalves, S., Martinez, M., Espeche, J. C., Santos, N. C., Semorile, L., Maffia, P. C., & Hollmann, A. (2020). Interactions of “de novo” designed peptides with bacterial membranes: Implications in the antimicrobial activity. Biochimica et Biophysica Acta – Biomembranes, 1862(11), 183443. https://doi.org/10.1016/j.bbamemMedina, P., & Fernández, F. (2014). Observaciones sobre los mecanismos de defensa de los insectos. Acta Zoológica Lilloana, 58(1), 17-43.Mejía, E., Benítez, J., & Ortiz, M. (2020). Péptidos antimicrobianos, una alternativa para el combate de la resistencia bacteriana. Acta Biológica Colombiana, 2(2), 294–302. https://doi.org/10.15446/abc.v25n2.77407Ministerio de Salud y Protección Social. (2018). Plan Nacional de Respuesta a la Resistencia a los Antimicrobianos.https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/MET/plan-respuesta-resistencia-antimicrobianos.pdf.Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2022). ColabFold: making protein folding accessible to all. Nature Methods, 19(6), 679–682. https://doi.org/10.1038/s41592-022-01488-1Mishra, B., & Wang, G. (2012). The importance of amino acid composition in natural AMPs: an evolutional, structural, and functional perspective. Frontiers in Immunology, 3, 221. https://doi.org/10.3389/fimmu.2012.00221Mookherjee, N., Anderson, M. A., Haagsman, H. P., & Davidson, D. J. (2020). Antimicrobial host defence peptides: functions and clinical potential. Nature Reviews Drug Discovery, 19(5), 311-332. doi.org/10.1038/s41573-019-0058-8Monsalve, D., Mesa, A., Mira, L. M., Mera, C., Orduz, S., & Branch-Bedoya, J. W. (2024). Antimicrobial peptides designed by computational analysis of proteomes. Antonie van Leeuwenhoek, 117(1), 55. https://doi.org/10.1007/s10482-024-01946-0Mulani, M., Kamble, E., Kumkar, S., Tawre, M., & Pardesi, K. (2019). Emerging strategies to combat ESKAPE pathogens in the era of antimicrobial resistance: A review. Frontiers in Microbiology, 10, 539. https://doi.org/10.3389/fmicbMuñoz, G., Sánchez, L., & Estrada-Tapia, G. (2020). Péptidos de defensa: una alternativa natural para el control de patógenos de plantas y humanos. Cicy, 93, 88–93.Nastro, M. (2019). What can we do to prevent multidrug-resistance? Revista Argentina de Microbiologia, 51(1), 1–2. https://doi.org/10.1016/j.ram.2019.02.001Negash, A. W., & Tsehai, B. A. (2020). Current applications of bacteriocin. International Journal of Microbiology, 2020, 4374891. https://doi.org/10.1155/2020/4374891Opal, S. M., & Pop-Vicas, A. (2015). Molecular mechanisms of antibiotic resistance in bacteria. In Mandell, Douglas, and Bennett's Principles and Practice of Infectious Diseases (pp. 235-251). WB Saunders. https://doi.org/10.1016/b978-0-443-06839-3.00019-9Organización Panamericana de la Salud. (2019). Tratamiento de las enfermedades infecciosas 2020-2022. (8° ed). Autoedición. https://doi.org/10.37774/9789275321003Organización Panamericana de la Salud. (2021). La resistencia antimicrobiana pone en riesgo la salud mundial. Recuperado de: https://www.paho.org/es/noticias/3-3-2021-resistencia-antimicrobiana-pone-riesgo-salud-mundialOrozco, S., & Arango, J. (2016) Aplicación de la inteligencia artificial en la bioinformática, avances, definiciones y herramientas. UGCiencia, 22(1), 159-171. https://doi.org/10.18634/ugcj.22v.1i.494Ortiz, C. (2019). Diseño, síntesis, caracterización y evaluación in vitro de la actividad de los péptidos antimicrobianos contra bacterias patógenas resistentes a antibióticos. Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales, 43(169), 614-627. https://doi.org/10.18257/raccefyn.864Pasupuleti, M., Schmidtchen, A., & Malmsten, M. (2012). Antimicrobial peptides: key components of the innate immune system. Critical Reviews in Biotechnology, 32(2), 143-171. https://doi.org/10.3109/07388551.2011.594423Patel, H., Bhatt, D., Shakhreliya, S., Lam, N. L., Maurya, R., & Singh, V. (2021). An Introduction and Applications of Bioinformatics. Advances in Bioinformatics, 1-14.Penesyan, A., Gillings, M., & Paulsen, I. T. (2015). Antibiotic discovery: combatting bacterial resistance in cells and in biofilm communities. Molecules, 20(4), 5286-5298. https://doi.org/10.3390/molecules20045286Perron, G., Whyte, L., Turnbaugh, P., Goordial, J., Hanage, W., Dantas, G., & Michael, D. (2015). Functional characterization of bacteria isolated from ancient Arctic soil exposes diverse resistance mechanisms to modern antibiotics. PLoS One, 10(3), e0069533. https://doi.org/10.1371/journal.pone.0069533Pfalzgraff, A., Brandenburg, K., & Weind, G. (2018). Antimicrobial peptides and their therapeutic potential for bacterial skin infections and wounds. Frontiers in Pharmacology, 9, 281. https://doi.org/10.3389/fphar.2018.00281Phuong, P. T., Oliver, S., He, J., Wong, E. H., Mathers, R. T., & Boyer, C. (2020). Effect of hydrophobic groups on antimicrobial and hemolytic activity: Developing a predictive tool for ternary antimicrobial polymers. Biomacromolecules, 21(12), 5241-5255. https://doi.org/10.1021/acs.biomac.0c01320Pirtskhalava, M., Amstrong, A. A., Grigolava, M., Chubinidze, M., Alimbarashvili, E., Vishnepolsky, B., Gabrielian, A., Rosenthal, A., Hurt, D. E., & Tartakovsky, M. (2021). DBAASP v3: Database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics. Nucleic Acids Research, 49(D1), D288–D297. https://doi.org/10.1093/nar/gkaa991Quiñones, D. (2017). Resistencia antimicrobiana: evolución y perspectivas actuales ante el enfoque" Una salud". Revista Cubana de Medicina Tropical, 69(3), 1-17.Quintero, V. (2021). La próxima pandemia: Bacterias multirresistentes a antibióticos. Alianzas y Tendencias BUAP, 6(21), 1–7.Radusky, L. (2017). Herramientas bioinformáticas para el análisis estructural de proteínas a escala genómica. [Tesis Doctoral, Universidad de Buenos Aires].Rivas-Santiago, B., Sada, E., Hernández-Pando, R., & Tsutsumi, V. (2006). Péptidos antimicrobianos en la inmunidad innata de enfermedades infecciosas. Salud Pública de México, 48, 62-71. https://doi.org/10.1590/s0036-36342006000100010Rodríguez, E., & Méndez, D. (2021). Aspectos generales relacionados con los antibióticos y plaguicidas. En E. Rodríguez, D. Méndez, Marrugo, A y Márquez, J. (Eds.), Perspectiva analítica y proteómica de residuos de antimicrobianos y plaguicidas en alimentos de origen animal (19-58). Editorial Universitaria.Rončević, T., Puizina, J., & Tossi, A. (2019). Antimicrobial peptides as anti-infective agents in pre-post-antibiotic era?. International Journal of Molecular Sciences, 20(22), 5713. https://doi.org/10.3390/ijms20225713Salem, M., Keshavarzi Arshadi, A., & Yuan, J. S. (2022). AMPDeep: hemolytic activity prediction of antimicrobial peptides using transfer learning. BMC Bioinformatics, 23(1), 1-17. https://doi.org/10.21203/rs.3.rs-1615895/v1Sapay N, Guermeur Y, & Deléage G (2006). Prediction of amphipathic in-plane membrane anchors in monotopic proteins using a SVM classifier. BMC Bioinformatics, 7(1), 1-11. https://doi.org/10.1186/1471-2105-7-255Schmidt, C. (2017). Living in a microbial world. Nature Biotechnology, 35, 401-403. https://doi.org/10.1038/nbt.3868Scocchi, M., Mardirossian, M., Runti, G., & Benincasa, M. (2017). Non-membranolytic mechanisms of action of antimicrobial peptides–novel therapeutic opportunities. Antimicrobial Peptides: Discovery, Design, and Novel Therapeutic Strategies. CABI, Oxfordshire, 149-160. https://doi.org/10.1079/9781786390394.0149Segev-Zarko, L. A., Mangoni, M. L., & Shai, Y. (2017). Antimicrobial peptides: multiple mechanisms against a variety of targets. Antimicrobial Peptides: Discovery, Design and Novel Therapeutic Strategies. UK: CAB Inhternational, 119-127. https://doi.org/10.1079/9781786390394.0119Semreen, M., Gamal, M., Abdin, S., Alkhazraji, H., Kamal, L., Hammad, S., Awady, F., Waleed, D., & Kourbaj, L. (2018). Recent updates of marine antimicrobial peptides. Saudi Pharmaceutical Journal, 26(3), 396-409. https://doi.org/10.1016/j.jsps.2018.01.001Serra, M. (2017). La resistencia microbiana en el contexto actual y la importancia del conocimiento y aplicación en la política antimicrobiana. Revista Habanera de Ciencias Médicas, 16(3), 402-419.Shelomi, M., Jacobs, C., Vilcinskas, A., and Vogel, H. (2020). The unique antimicrobial peptide repertoire of stick insects. Developmental and Comparative Immunology, 103, 103471. https://doi.org/10.1016/j.dci.2019.103471Starr, C. G., & Wimley, W. C. (2017). Discovery of novel antimicrobial peptides using combinatorial chemistry and high-throughput screening. Antimicrobial peptides: Discovery, design and novel therapeutic strategies, (Ed. 2), 86-100. https://doi.org/10.1079/9781786390394.0086Tamayo S, Castañeda CA, Orduz S. (2018). Type-Peptide 1.0. Herramientas computacionales pedagógicas para el estudio, diseño y optimización de péptidos antimicrobianas basada en sus propiedades fisicoquímicas. Dirección Nacional de Derechos de Autor. Ministerio del Interior. Registro 13-70-274. Diciembre 5, 2018.Téllez, G. y Castaño, J. (2010). Péptidos antimicrobianos. Infectio, 14(1), 55-67. https://doi.org/10.1016/s0123-9392(10)70093-xThakur, N., Qureshi, A., & Kumar, M. (2012). AVPpred: Collection and prediction of highly effective antiviral peptides. Nucleic Acids Research, 40(W1), W199-W204. https://doi.org/10.1093/nar/gks450Timmons, P., & Hewage, C. (2020). HAPPENN is a novel tool for hemolytic activity prediction for therapeutic peptides which employs neural networks. Scientific Reports, 10(1), 1–18. https://doi.org/10.1038/s41598-020-67701-3Tonarelli, G., & Simonetta, A. (2013). Péptidos antimicrobianos de organismos procariotas y eucariotas como agentes terapéuticos y conservantes de alimentos. Revista FABICIB, 17, 137-177. https://doi.org/10.14409/fabicib.v17i0.4316Tornesello, A., Borrelli, A., Buonaguro, L., Buonaguro, F., & Tornesello, M. (2020). Antimicrobial peptides as anticancer agents: Functional properties and biological activities. Molecules, 25(12), 1–25. https://doi.org/10.3390/molecules25122850Torres, MDT, Sothiselvam, S., Lu, TK y de la Fuente-Nunez, C. (2019). Principios de diseño de péptidos para aplicaciones antimicrobianas. Journal of Molecular Biology. 431, 3547–3567. doi: 10.1016/j.jmb.2018.12.015UniProt [Internet]. Available from: https://www.uniprot.org/Vázquez, A., Perdomo-Morales, R., & Montero-Alejo, V. (2018). Natural antimicrobial peptides. Biotecnologia. Aplicada, 35, 4101-4107.Veltri, D., Kamath, U., & Shehu, A. (2018). Deep learning improves antimicrobial peptide recognition. Bioinformatics, 34(16), 2740–2747. https://doi.org/10.1093/bioinformatics/bty179Vishnepolsky, B., Grigolava, M., Managadze, G., Gabrielian, A., Rosenthal, A., Hurt, D. E., Tartakovsky, M., & Pirtskhalava, M. (2022). Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction. Briefings in Bioinformatics, 23(4), bbac233. https://doi.org/10.1093/bib/bbac233Waghu, F. H., & Idicula-Thomas, S. (2020). Collection of antimicrobial peptides database and its derivatives: Applications and beyond. Protein Science, 29(1), 36–42. https://doi.org/10.1002/pro.3714Wang GuangShun. (2017). Structural insight into the mechanisms of action of antimicrobial peptides and structure-based design. In Antimicrobial peptides: discovery, design and novel therapeutic strategies (pp. 169-187). Wallingford UK: Cabi. https://doi.org/10.1079/9781786390394.0169Wang, G. (2017). Discovery, classification and functional diversity of antimicrobia peptides. Antimicrobial peptides: Discovery, Design and Novel Therapeutic Strategies. CABI Publishing, 1-19. https://doi.org/10.1079/9781786390394.0001Wang, G. S. (2010). Structural studies of antimicrobial peptides provide insight into their mechanisms of action. Antimicrobial peptides: discovery, design and novel therapeutic strategies, 141-168. https://doi.org/10.1079/9781845936570.0141Wang, G. S., Li, X., & Zasloff, M. (2010). A database view of naturally occurring antimicrobial peptides: nomenclature, classification and amino acid sequence analysis. In Antimicrobial peptides: discovery, design and novel therapeutic strategies (pp. 1-21). Wallingford UK: Cabi. https://doi.org/10.1079/9781845936570.0001Wang, G., Hanke, M.L., Mishra, B., Lushnikova, T., Heim, C.E., et al. (2014) Transformation of human cathelicidin LL-37 into selective, stable, and potent antimicrobial compounds. ACS Chemical Biology 9(9), 1997–2002. https://doi.org/10.1021/cb500475yWang, G., Li, X., & Wang, Z. (2016). APD3: The antimicrobial peptide database as a tool for research and education. Nucleic Acids Research, 44(D1), D1087–D1093. https://doi.org/10.1093/nar/gkv1278Wang, Y., Wang, Q., Wu, A., Hao, Z., & Liu, X. (2017). Isolation of a peptide from Ph.D.-C7C phage display library for detection of Cry1Ab. Analytical Biochemistry, 539, 29–32. https://doi.org/10.1016/j.ab.2017.03.004Weeks, R., Algburi, A., & Chikindas, M. (2021). Antimicrobial peptides and peptidomimetics for the control of antimicrobial resistance. Sustainable Agriculture Reviews 49: Mitigation of Antimicrobial Resistance Vol 2. Natural and Synthetic Approaches, 205-249. https://doi.org/10.1007/978-3-030-58259-3_7Wuerth, K. C., & Hancock, R. E. (2017). Immunomodulatory activities of cationic host defence peptides and novel therapeutic strategies. Antimicrobial peptides: discovery, design and novel therapeutic strategies, (Ed. 2), 238-259. https://doi.org/10.1079/9781786390394.0238Xiao, H., Shao, F., Wu, M., Ren, W., Xiong, X., Tan, B., & Yin, Y. (2015). The application of antimicrobial peptides as growth and health promoters for swine. Journal of Animal Science and Biotechnology, 6(1), 1–6. https://doi.org/10.1186/s40104-015-0018-zZahedifard, F., Lee, H., No, J. H., Salimi, M., Seyed, N., Asoodeh, A., et al. (2020). Comparative study of different forms of jellein antimicrobial peptide on leishmania parasite. Experimental Parasitology. 209:107823. https://doi.org/10.1016/j.exppara.2019.107823Zhou, C., Kang, J., Wang, X., Wei, W., & Jiang, W. (2015). Phage display screening identifies a novel peptide to suppress ovarian cancer cells in vitro and in vivo in mouse models. BMC Cancer, 15(1). https://doi.org/10.1186/s12885-015-1891-8BibliotecariosEstudiantesInvestigadoresMaestrosProveedores de ayuda financiera para estudiantesPúblico generalLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/86299/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1085272703.2024.pdf1085272703.2024.pdfTesis de Maestría en Ciencias - Biotecnologíaapplication/pdf2368617https://repositorio.unal.edu.co/bitstream/unal/86299/3/1085272703.2024.pdfaca3e2f1d02c460a7e8b9265b7443049MD53THUMBNAIL1085272703.2024.pdf.jpg1085272703.2024.pdf.jpgGenerated Thumbnailimage/jpeg4796https://repositorio.unal.edu.co/bitstream/unal/86299/4/1085272703.2024.pdf.jpg0de493f267ce12ecd67fe1428d8064b3MD54unal/86299oai:repositorio.unal.edu.co:unal/862992024-08-25 23:11:59.405Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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 |