Desarrollo y síntesis de un análogo de los quimioterapéuticos inhibidores de la topoisomerasa I, por metodologías de cribado virtual basadas en cambios bioisostéricos y QSAR

dc.contributor.advisorGuevara Pulido, James Oswaldo
dc.contributor.authorRodriguez Velandia , Sara Daniela
dc.contributor.authorMoreno Tranchita, Juan Pablo
dc.date.accessioned2024-05-16T02:45:06Z
dc.date.available2024-05-16T02:45:06Z
dc.date.issued2024-04-30
dc.description.abstractLa incidencia del cáncer colorrectal ha aumentado considerablemente, convirtiéndolo en un problema de salud pública global. Su complejidad genera diagnósticos tardíos y tratamientos con baja eficacia, lo que conlleva a una alta carga de efectos adversos para los pacientes. En respuesta a esta problemática, se diseñó y sintetizó un nuevo análogo inhibidor de la ADN topoisomerasa 1. Este proceso se basó en el diseño racional de fármacos, utilizando cambios bioisostéricos y metodologías de SBVS y LBVS con machine learning. Se desarrollaron tres modelos predictivos validados en líneas celulares de cáncer colorrectal HCT-116, HCT-8 y HT-29. Entre 59 análogos diseñados, el A12 se destaca por sus mejoras en comparación con Irinotecan, Topotecan y Doxorubicina. A12 presenta una buena afinidad por la ADN topoisomerasa 1 (6,8 Kcal/mol) y un menor IC50 (0,23 μM en HCT- 116). Además, presenta mejoras farmacocinéticas (PPB 89,6%, Log P 3,22) y un perfil de toxicidad similar a los fármacos comerciales. El desarrollo del análogo A12 representa un avance significativo en la búsqueda de nuevas opciones terapéuticas para el cáncer colorrectal. Sus propiedades farmacológicas y de seguridad lo convierten en un candidato prometedor para futuras investigaciones preclínicas
dc.description.abstractenglishThe incidence of colorectal cancer has significantly increased, turning it into a global public health issue. Its complexity leads to late diagnoses and treatments with low efficacy, resulting in a high burden of adverse effects for patients. In response to this challenge, a new analog inhibitor of DNA topoisomerase 1 was designed and synthesized. This process was based on rational drug design, utilizing bioisosteric changes and SBVS and LBVS methodologies with machine learning. Three predictive models were developed and validated in colorectal cancer cell lines HCT-116, HCT-8, and HT-29. Among 59 designed analogs, A12 stands out for its improvements compared to Irinotecan, Topotecan, and Doxorubicin. A12 shows good affinity for DNA topoisomerase 1 (6.8 Kcal/mol) and a lower IC50 (0.23 μM in HCT-116). Additionally, it exhibits improved pharmacokinetics (PPB 89.6%, Log P 3.22) and a toxicity profile similar to commercial drugs. The development of the A12 analog represents a significant advancement in the search for new therapeutic options for colorectal cancer. Its pharmacological properties and safety profile make it a promising candidate for future preclinical research.
dc.description.degreelevelPregradospa
dc.description.degreelevelQuímico Farmacéuticospa
dc.format.mimetypeapplication/pdf
dc.identifier.instnameUniversidad El Bosquespa
dc.identifier.reponamereponame:Repositorio Institucional Universidad El Bosquespa
dc.identifier.repourlrepourl:https://repositorio.unbosque.edu.co
dc.identifier.urihttps://hdl.handle.net/20.500.12495/12133
dc.language.isoes
dc.publisher.facultyFacultad de Cienciasspa
dc.publisher.grantorUniversidad El Bosquespa
dc.publisher.programQuímica Farmacéuticaspa
dc.relation.referencesCáncer colorrectal.” Accessed: Mar. 31, 2024. [Online]. Available: https://www.who.int/es/news-room/fact- sheets/detail/colorectal-cancer
dc.relation.referencesA. Goel et al., “Citation: Hossain, M Colorectal Cancer: A Review of Carcinogenesis, Global Epidemiology, Current Challenges, Risk Factors, Preventive and Treatment Strategies,” Cancers, vol. 2022, p. 1732, 1732, doi: 10.3390/cancers14071732.
dc.relation.referencesC. Luo, S. Cen, G. Ding, and W. Wu, “Mucinous colorectal adenocarcinoma: Clinical pathology and treatment options,” Cancer Communications, vol. 39, no. 1, Mar. 2019, doi: 10.1186/S40880-019-0361-0.
dc.relation.referencesV. K. Morris et al., “Treatment of Metastatic Colorectal Cancer: ASCO Guideline,” J Clin Oncol, vol. 41, pp. 678–700, 2022, doi: 10.1200/JCO.22.
dc.relation.referencesY. Pommier, A. Nussenzweig, S. Takeda, and C. Austin, “Human topoisomerases and their roles in genome stability and organization”, doi: 10.1038/s41580-022-00452-3.
dc.relation.referencesY. Sun et al., “Targeting neddylation sensitizes colorectal cancer to topoisomerase I inhibitors by inactivating the DCAF13-CRL4 ubiquitin ligase complex”, doi: 10.1038/s41467-023-39374-9.
dc.relation.referencesA. Talukdar, B. Kundu, D. Sarkar, S. Goon, and M. A. Mondal, “Topoisomerase I inhibitors: Challenges, progress and the road ahead,” European Journal of Medicinal Chemistry, vol. 236, p. 114304, Jun. 2022, doi: 10.1016/J.EJMECH.2022.114304.
dc.relation.referencesB. L. Staker et al., “Structures of Three Classes of Anticancer Agents Bound to the Human Topoisomerase I−DNA Covalent Complex,” Journal of Medicinal Chemistry, vol. 48, no. 7, pp. 2336–2345, 2005, doi: 10.1021/jm049146p
dc.relation.referencesG. F. Weber, “2 DNA Damaging Drugs,” 2015, doi: 10.1007/978-3-319-13278-5_2.
dc.relation.referencesJ. Marinello et al., “ARTICLE OPEN Cellular and Molecular Biology Topoisomerase I poison-triggered immune gene activation is markedly reduced in human small-cell lung cancers by impairment of the cGAS/STING pathway,” British Journal of Cancer, vol. 127, pp. 1214–1225, 2022, doi: 10.1038/s41416-022-01894
dc.relation.referencesY. Pommier, “DNA Topoisomerase I Inhibitors: Chemistry, Biology and Interfacial Inhibition”, doi: 10.1021/cr900097c.
dc.relation.referencesA. Thomas and Y. Pommier, “Targeting Topoisomerase I in the Era of Precision Medicine”, doi: 10.1158/1078- 0432.CCR-19-1089.
dc.relation.referencesH. Soufi, · Mohammed Salah, · Said Belaaouad, and · Mohammed Moutaabbid, “An Insightful Evaluation of Evodiamine Analogs Effect as DNA Topoisomerase I Inhibitors Using QSAR Method,” India, Sect. B Biol. Sci, vol. 93, no. 3, pp. 639–657, doi: 10.1007/s40011-023-01450-x.
dc.relation.referencesS. Pal et al., “Ligand-based Pharmacophore Modeling, Virtual Screening and Molecular Docking Studies for Discovery of Potential Topoisomerase I Inhibitors,” Computational and Structural Biotechnology Journal, vol. 17, pp. 291–310, Jan. 2019, doi: 10.1016/J.CSBJ.2019.02.006.
dc.relation.referencesD. M. Khaled, M. E. Elshakre, M. A. Noamaan, H. Butt, M. M. A. Fattah, and D. A. Gaber, “A Computational QSAR, Molecular Docking and In Vitro Cytotoxicity Study of Novel Thiouracil-Based Drugs with Anticancer Activity against Human-DNA Topoisomerase II,” 2022, doi: 10.3390/ijms231911799
dc.relation.referencesN. Berdigaliyev and M. Aljofan, “An overview of drug discovery and development,” https://doi.org/10.4155/fmc-2019-0307, vol. 12, no. 10, pp. 939–947, Apr. 2020, doi: 10.4155/FMC-2019-0307.
dc.relation.referencesY. Kochnev, E. Hellemann, K. C. Cassidy, and J. D. Durrant, “Webina: an open-source library and web app that runs AutoDock Vina entirely in the web browser”, doi: 10.1093/bioinformatics/btaa
dc.relation.referencesS. Murail, S. J. de Vries, J. Rey, G. Moroy, and P. Tufféry, “SeamDock: An Interactive and Collaborative Online Docking Resource to Assist Small Compound Molecular Docking”, doi: 10.3389/fmolb.2021.716466.
dc.relation.referencesF. Grisoni, D. Ballabio, R. Todeschini, and V. Consonni, “Molecular Descriptors for Structure–Activity Applications: A Hands-On Approach,” Methods in Molecular Biology, vol. 1800, pp. 3–53, 2018, doi: 10.1007/978-1- 4939-7899-1_1.
dc.relation.referencesD. N. Jaramillo, D. Millán, and J. Guevara-Pulido, “Design, synthesis and cytotoxic evaluation of a selective serotonin reuptake inhibitor (SSRI) by virtual screening,” European Journal of Pharmaceutical Sciences, vol. 183, p. 106403, Apr. 2023, doi: 10.1016/J.EJPS.2023.106403.
dc.relation.referencesM. Prieto, A. Niño, P. Acosta-Guzmán, and J. Guevara-Pulido, “Design and synthesis of a potential selective JAK-3 inhibitor for the treatment of rheumatoid arthritis using predictive QSAR models,” Informatics in Med icine Unlocked, vol. 45, p. 101464, Jan. 2024, doi: 10.1016/J.IMU.2024.101464.
dc.relation.referencesJ. Guevara-Pulido, R. A. Jiménez, S. J. Morantes, D. N. Jaramillo, and P. Acosta-Guzmán, “Design, Synthesis, and Development of 4-[(7-Chloroquinoline-4-yl)amino]phenol as a Potential SARS-CoV-2 Mpro Inhibitor,” 2022, doi: 10.1002/slct.202200125.
dc.relation.referencesA.Daina, O. Michielin, and V. Zoete, “SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules OPEN,” 2017, doi: 10.1038/srep42717
dc.relation.referencesG. Xiong et al., “ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties,” Nucleic Acids Research, vol. 49, 2021, doi: 10.1093/nar/gkab255.
dc.relation.referencesN. Brown, P. Ertl, R. Lewis, T. Luksch, D. Reker, and N. Schneider, “Artificial intelligence in chemistry and drug design,” Journal of Computer-Aided Molecular Design, vol. 34, no. 7, pp. 709–715, Jul. 2020, doi: 10.1007/S10822-020-00317-X/METRICS.
dc.relation.referencesS. Koosha, Z. Mohamed, A. Sinniah, and M. A. Alshawsh, “Investigation into the Molecular Mechanisms underlying the Anti-proliferative and Anti-tumorigenesis activities of Diosmetin against HCT-116 Human Colorectal Cancer”, doi: 10.1038/s41598-019-41685-1.
dc.relation.referencesT. J. Med Sci et al., “Turkish Journal of Medical Sciences Carvacrol alters soluble factors in HCT-116 and HT-29 cell lines”, doi: 10.3906/sag-1907-173.
dc.relation.referencesJ. Dong et al., “ChemDes: An integrated web-based platform for molecular descriptor and fingerprint computation,” Journal of Cheminformatics, vol. 7, no. 1, pp. 1–10, Dec. 2015, doi: 10.1186/S13321-015-0109-Z/FIG- URES/2.
dc.relation.referencesA. Golbraikh and A. Tropsha, “Beware of q2!,” Journal of Molecular Graphics and Modelling, vol. 20, no. 4,pp. 269–276, Jan. 2002, doi: 10.1016/S1093-3263(01)00123-1.
dc.relation.referencesN. A. Meanwell, “The Influence of Bioisosteres in Drug Design: Tactical Applications to Address Developability Problems,” Top Med Chem, vol. 9, pp. 283–382, 2015, doi: 10.1007/7355_2013_29.
dc.relation.referencesA. Dick and S. Cocklin, “pharmaceuticals Bioisosteric Replacement as a Tool in Anti-HIV Drug Design”, doi: 10.3390/ph13030036.
dc.relation.referencesM. Coelho Santos Junior et al., “Structure-Based Virtual Screening: From Classical to Artificial Intelligence,” Frontiers in Chemistry | www.frontiersin.org, vol. 1, p. 343, 2020, doi: 10.3389/fchem.2020.00343.
dc.relation.referencesH. Zhu, Y. Zhang, W. Li, and N. Huang, “A Comprehensive Survey of Prospective Structure-Based Virtual Screening for Early Drug Discovery in the Past Fifteen Years,” 2022, doi: 10.3390/ijms232415961.
dc.relation.referencesH. M. Berman et al., “The Protein Data Bank,” 2000. [Online]. Available: http://www.rcsb.org/pdb/status.html
dc.relation.referencesC. Metallinos, S. Nerdinger, and V. Snieckus, “N-cumyl benzamide, sulfonamide, and aryl O-carbamate directed metalation groups. Mild hydrolytic lability for facile manipulation of directed ortho metalation derived aromatics,” Organic Letters, vol. 1, no. 8, pp. 1183–1186, Oct. 1999, doi: 10.1021/OL990846B/SUPPL_FILE/OL990846B_S.PDF.
dc.relation.referencesP. Acosta-Guzmán, A. Rodríguez-López, and D. Gamba-Sánchez, “Pummerer Synthesis of Chromanes Reveals a Competition between Cyclization and Reductive Chlorination,” Organic Letters, vol. 21, no. 17, pp. 6903–6908, Sep. 2019, doi: 10.1021/ACS.ORGLETT.9B02520/SUPPL_FILE/OL9B02520_SI_001.PDF.
dc.relation.referencesN. Srinivasan, A. Yurek-George, and A. Ganesan, “Rapid deprotection of N-Boc amines by TFA combined with freebase generation using basic ion-exchange resins,” Molecular Diversity, vol. 9, no. 4, pp. 291–293, Nov. 2005, doi: 10.1007/S11030-005-4386-8/METRICS.
dc.rights.accessrightsinfo:eu-repo/semantics/closedAccess
dc.rights.accessrightshttp://purl.org/coar/access_right/c_14cb
dc.rights.localAcceso cerradospa
dc.subjectCáncer colorrectal
dc.subjectAND topoisomerasa 1
dc.subjectMachine learning
dc.subjectQSAR
dc.subjectFarmacocinética
dc.subjectFarmacodinamia
dc.subject.ddc615.19
dc.subject.keywordsColorectal cancer
dc.subject.keywordsDNA topoisomerase 1
dc.subject.keywordsMachine learning
dc.subject.keywordsQSAR
dc.subject.keywordsPharmacokinetics
dc.subject.keywordsPharmacodynamics
dc.titleDesarrollo y síntesis de un análogo de los quimioterapéuticos inhibidores de la topoisomerasa I, por metodologías de cribado virtual basadas en cambios bioisostéricos y QSAR
dc.title.translatedDevelopment and synthesis of an analog of the chemotherapeutic topoisomerase I inhibitors, using virtual screening methodologies based on bioisosteric changes and QSAR.
dc.type.coarhttps://purl.org/coar/resource_type/c_7a1f
dc.type.coarversionhttps://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.driverinfo:eu-repo/semantics/bachelorThesis
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.type.localTesis/Trabajo de grado - Monografía - Pregrado

Archivos