Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR
Cardiovascular diseases, mostly related to hyperlipidemia, have a significant impact on the population; it is known that HMG-CoA reductase inhibitors are the first-line medications for their treatment, being the most prescribed worldwide. However, their prolonged use can lead to drug-induced myopath...
- Autores:
-
Blanco Niño, Manuel Andres
Delgado Cruz, Diana Paola
- Tipo de recurso:
- https://purl.org/coar/resource_type/c_7a1f
- Fecha de publicación:
- 2024
- Institución:
- Universidad El Bosque
- Repositorio:
- Repositorio U. El Bosque
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unbosque.edu.co:20.500.12495/12092
- Acceso en línea:
- https://hdl.handle.net/20.500.12495/12092
- Palabra clave:
- Hipercolesterolemia
Inhibidores de la HMG CoA-Reductasa
QSAR
Drug Discovery
615.19
Hypercholesterolemia
HMG CoA Reductase Inhibitors
QSAR
Drug Discovery
- Rights
- closedAccess
- License
- Acceso cerrado
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Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR |
| dc.title.translated.none.fl_str_mv |
Design and synthesis of a novel HMG-CoA reductase inhibitor derivate using QSAR |
| title |
Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR |
| spellingShingle |
Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR Hipercolesterolemia Inhibidores de la HMG CoA-Reductasa QSAR Drug Discovery 615.19 Hypercholesterolemia HMG CoA Reductase Inhibitors QSAR Drug Discovery |
| title_short |
Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR |
| title_full |
Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR |
| title_fullStr |
Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR |
| title_full_unstemmed |
Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR |
| title_sort |
Diseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSAR |
| dc.creator.fl_str_mv |
Blanco Niño, Manuel Andres Delgado Cruz, Diana Paola |
| dc.contributor.advisor.none.fl_str_mv |
Guevara Pulido, James Oswaldo |
| dc.contributor.author.none.fl_str_mv |
Blanco Niño, Manuel Andres Delgado Cruz, Diana Paola |
| dc.subject.none.fl_str_mv |
Hipercolesterolemia Inhibidores de la HMG CoA-Reductasa QSAR Drug Discovery |
| topic |
Hipercolesterolemia Inhibidores de la HMG CoA-Reductasa QSAR Drug Discovery 615.19 Hypercholesterolemia HMG CoA Reductase Inhibitors QSAR Drug Discovery |
| dc.subject.ddc.none.fl_str_mv |
615.19 |
| dc.subject.keywords.none.fl_str_mv |
Hypercholesterolemia HMG CoA Reductase Inhibitors QSAR Drug Discovery |
| description |
Cardiovascular diseases, mostly related to hyperlipidemia, have a significant impact on the population; it is known that HMG-CoA reductase inhibitors are the first-line medications for their treatment, being the most prescribed worldwide. However, their prolonged use can lead to drug-induced myopathy, with the potential development of rhabdomyolysis. Hence arises the need for the design of safer statin analogs for patients, which is the aim of this research. The project was conducted in two sections, an in silico one corresponding to QSAR models and rational design, where parameters such as affinity values, biological activity (IC50 and CC50), log P, and toxicity were evaluated; resulting in the selection of analog 13a. The second section, corresponding to the experimental phase, involved the chemical synthesis of the analog and its characterization. Finally, it was concluded that analog 13a demonstrated better pharmacological and physicochemical attributes compared to atorvastatin, proving that rational analog design and the use of neural networks are potential tools for the development of new drugs. |
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2024 |
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2024-05-09T20:23:17Z |
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2024-05-09T20:23:17Z |
| dc.date.issued.none.fl_str_mv |
2024-04-29 |
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http://purl.org/coar/resource_type/c_7a1f |
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https://purl.org/coar/resource_type/c_7a1f |
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https://hdl.handle.net/20.500.12495/12092 |
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Universidad El Bosque |
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spa |
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spa |
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Stevens CW. Brenner and Stevens’ Pharmacology. 6th ed. Vol. Chapter 15. 2022. 161–172 p. Harper CR, Jacobson TA. The broad spectrum of statin myopathy: from myalgia to rhabdomyolysis. Curr Opin Lipidol. agosto de 2007;18(4):401–8. Turner RM, Pirmohamed M. Statin-Related Myotoxicity: A Comprehensive Review of Pharmacokinetic, Pharmacogenomic and Muscle Components. J Clin Med. el 20 de diciembre de 2019;9(1):22. Skottheim IB, Gedde-Dahl A, Hejazifar S, Hoel K, Åsberg A. Statin induced myotoxicity: The lactone forms are more potent than the acid forms in human skeletal muscle cells in vitro. European Journal of Pharmaceutical Sciences. abril de 2008;33(4–5):317–25. Escalona JC, Padrón JA, Carrasco R. Introducción al diseño racional de fármacos. 1a ed. Vol. 1. 2020. 21–45 p. Maia EHB, Assis LC, de Oliveira TA, da Silva AM, Taranto AG. Structure-Based Virtual Screening: From Classical to Artificial Intelligence. Vol. 8, Frontiers in Chemistry. Frontiers Media S.A.; 2020. Gonzalez Amaya JA, Cabrera DZ, Matallana AM, Arevalo KG, Guevara-Pulido J. In-silico design of new enalapril analogs (ACE inhibitors) using QSAR and molecular docking models. Inform Med Unlocked. 2020;19:100336. Jaramillo DN, Millán D, Guevara-Pulido J. Design, synthesis and cytotoxic evaluation of a selective serotonin reuptake inhibitor (SSRI) by virtual screening. European Journal of Pharmaceutical Sciences. abril de 2023;183:106403. Rajathei DM, Parthasarathy S, Selvaraj S. Combined QSAR Model and Chemical Similarity Search for Novel HMG-CoA Reductase Inhibitors for Coronary Heart Disease. Curr Comput Aided Drug Des. el 3 de septiembre de 2020;16(4):473–85. Najafi S, Moshtaghie AA, Hassanzadeh F, Nayeri H, Jafari E. Design, synthesis, and biological evaluation of novel atorvastatin derivatives. J Mol Struct. junio de 2023;1282:135229. Park WKC, Kennedy RM, Larsen SD, Miller S, Roth BD, Song Y, et al. Hepatoselectivity of statins: Design and synthesis of 4-sulfamoyl pyrroles as HMG-CoA reductase inhibitors. Bioorg Med Chem Lett. febrero de 2008;18(3):1151–6. Morales A, Guevara J. Síntesis de una nueva molécula basada en moduladores CFTR para el tratamiento de la fibrosis quística diseñada mediante cribado virtual basado en estructura y cribado virtual basado en ligandos. [Bogota]; 2023. Yap CW. PaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints. J Comput Chem. el 17 de mayo de 2011;32(7):1466–74. Daigavane A, Madan G, Sinha A, Thakurta AG, Aggarwal G, Jain P. Node-Level Differentially Private Graph Neural Networks. el 23 de noviembre de 2021; Disponible en: http://arxiv.org/abs/2111.15521 Meshram SG, Singh VP, Kisi O, Karimi V, Meshram C. Application of Artificial Neural Networks, Support Vector Machine and Multiple Model-ANN to Sediment Yield Prediction. Water Resources Management. el 1 de diciembre de 2020;34(15):4561–75. Olasupo SB, Uzairu A, Shallangwa G, Uba S. QSAR modeling, molecular docking and ADMET/pharmacokinetic studies: a chemometrics approach to search for novel inhibitors of norepinephrine transporter as potent antipsychotic drugs. Journal of the Iranian Chemical Society. el 10 de agosto de 2020;17(8):1953 Yang D, Zhou Q, Labroska V, Qin S, Darbalaei S, Wu Y, et al. G protein-coupled receptors: structure- and function-based drug discovery. Vol. 6, Signal Transduction and Targeted Therapy. Springer Nature; 2021. Darwish HW, Hassan SA, Salem MY, El-Zeany BA. Advanced stability indicating chemometric methods for quantitation of amlodipine and atorvastatin in their quinary mixture with acidic degradation products. Spectrochim Acta A Mol Biomol Spectrosc. el 5 de febrero de 2016;154:58–66. Vashist SK. Comparison of 1-Ethyl-3-(3-Dimethylaminopropyl) Carbodiimide Based Strategies to Crosslink Antibodies on Amine-Functionalized Platforms for Immunodiagnostic Applications. Diagnostics. el 27 de agosto de 2012;2(3):23–33. |
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Guevara Pulido, James OswaldoBlanco Niño, Manuel AndresDelgado Cruz, Diana Paola2024-05-09T20:23:17Z2024-05-09T20:23:17Z2024-04-29https://hdl.handle.net/20.500.12495/12092Universidad El Bosquereponame:Repositorio Institucional Universidad El Bosquerepourl:https://repositorio.unbosque.edu.coCardiovascular diseases, mostly related to hyperlipidemia, have a significant impact on the population; it is known that HMG-CoA reductase inhibitors are the first-line medications for their treatment, being the most prescribed worldwide. However, their prolonged use can lead to drug-induced myopathy, with the potential development of rhabdomyolysis. Hence arises the need for the design of safer statin analogs for patients, which is the aim of this research. The project was conducted in two sections, an in silico one corresponding to QSAR models and rational design, where parameters such as affinity values, biological activity (IC50 and CC50), log P, and toxicity were evaluated; resulting in the selection of analog 13a. The second section, corresponding to the experimental phase, involved the chemical synthesis of the analog and its characterization. Finally, it was concluded that analog 13a demonstrated better pharmacological and physicochemical attributes compared to atorvastatin, proving that rational analog design and the use of neural networks are potential tools for the development of new drugs.PregradoQuímico FarmacéuticoLas enfermedades cardiovasculares, en su mayoría relacionadas con la hiperlipidemia, representan un alto impacto en la población; se conoce que los inhibidores de la HMG-CoA reductasa son los medicamentos de primera línea para su tratamiento, siendo a su vez los más prescritos a nivel mundial. Sin embargo, su uso prolongado puede desencadenar miopatía inducida por medicamentos, con potencial desarrollo de rabdomiólisis. A partir de esto surge la necesidad del diseño de nuevos análogos de las estatinas más seguros para los pacientes, siendo este el objetivo de la presente investigación. El proyecto se llevó a cabo en dos secciones, una in silico correspondiente a modelos QSAR y diseño racional, donde se evaluaron parámetros como valores de afinidad, actividad biológica (IC50 y CC50), log P y toxicidad; dando como resultado la selección del análogo 13a. La segunda sección, correspondiente a la fase experimental acoge el planteamiento de la síntesis química del análogo y su caracterización. Finalmente, se pudo concluir que el análogo 13a demostró mejores atributos farmacológicos y fisicoquímicos en contraste con la atorvastatina, demostrando que el diseño racional de análogos y el uso de redes neuronales son herramientas potenciales para el desarrollo de nuevos fármacos.application/pdfHipercolesterolemiaInhibidores de la HMG CoA-ReductasaQSARDrug Discovery615.19HypercholesterolemiaHMG CoA Reductase InhibitorsQSARDrug DiscoveryDiseño y síntesis química de un análogo de los inhibidores de la HMG-CoA reductasa mediante QSARDesign and synthesis of a novel HMG-CoA reductase inhibitor derivate using QSARQuímica FarmacéuticaUniversidad El BosqueFacultad de CienciasTesis/Trabajo de grado - Monografía - Pregradohttps://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/resource_type/c_7a1finfo:eu-repo/semantics/bachelorThesishttps://purl.org/coar/version/c_ab4af688f83e57aaStevens CW. Brenner and Stevens’ Pharmacology. 6th ed. Vol. Chapter 15. 2022. 161–172 p.Harper CR, Jacobson TA. The broad spectrum of statin myopathy: from myalgia to rhabdomyolysis. Curr Opin Lipidol. agosto de 2007;18(4):401–8.Turner RM, Pirmohamed M. Statin-Related Myotoxicity: A Comprehensive Review of Pharmacokinetic, Pharmacogenomic and Muscle Components. J Clin Med. el 20 de diciembre de 2019;9(1):22.Skottheim IB, Gedde-Dahl A, Hejazifar S, Hoel K, Åsberg A. Statin induced myotoxicity: The lactone forms are more potent than the acid forms in human skeletal muscle cells in vitro. European Journal of Pharmaceutical Sciences. abril de 2008;33(4–5):317–25.Escalona JC, Padrón JA, Carrasco R. Introducción al diseño racional de fármacos. 1a ed. Vol. 1. 2020. 21–45 p.Maia EHB, Assis LC, de Oliveira TA, da Silva AM, Taranto AG. Structure-Based Virtual Screening: From Classical to Artificial Intelligence. Vol. 8, Frontiers in Chemistry. Frontiers Media S.A.; 2020.Gonzalez Amaya JA, Cabrera DZ, Matallana AM, Arevalo KG, Guevara-Pulido J. In-silico design of new enalapril analogs (ACE inhibitors) using QSAR and molecular docking models. Inform Med Unlocked. 2020;19:100336.Jaramillo DN, Millán D, Guevara-Pulido J. Design, synthesis and cytotoxic evaluation of a selective serotonin reuptake inhibitor (SSRI) by virtual screening. European Journal of Pharmaceutical Sciences. abril de 2023;183:106403.Rajathei DM, Parthasarathy S, Selvaraj S. Combined QSAR Model and Chemical Similarity Search for Novel HMG-CoA Reductase Inhibitors for Coronary Heart Disease. Curr Comput Aided Drug Des. el 3 de septiembre de 2020;16(4):473–85.Najafi S, Moshtaghie AA, Hassanzadeh F, Nayeri H, Jafari E. Design, synthesis, and biological evaluation of novel atorvastatin derivatives. J Mol Struct. junio de 2023;1282:135229.Park WKC, Kennedy RM, Larsen SD, Miller S, Roth BD, Song Y, et al. Hepatoselectivity of statins: Design and synthesis of 4-sulfamoyl pyrroles as HMG-CoA reductase inhibitors. Bioorg Med Chem Lett. febrero de 2008;18(3):1151–6.Morales A, Guevara J. Síntesis de una nueva molécula basada en moduladores CFTR para el tratamiento de la fibrosis quística diseñada mediante cribado virtual basado en estructura y cribado virtual basado en ligandos. [Bogota]; 2023.Yap CW. PaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints. J Comput Chem. el 17 de mayo de 2011;32(7):1466–74.Daigavane A, Madan G, Sinha A, Thakurta AG, Aggarwal G, Jain P. Node-Level Differentially Private Graph Neural Networks. el 23 de noviembre de 2021; Disponible en: http://arxiv.org/abs/2111.15521Meshram SG, Singh VP, Kisi O, Karimi V, Meshram C. Application of Artificial Neural Networks, Support Vector Machine and Multiple Model-ANN to Sediment Yield Prediction. Water Resources Management. el 1 de diciembre de 2020;34(15):4561–75.Olasupo SB, Uzairu A, Shallangwa G, Uba S. QSAR modeling, molecular docking and ADMET/pharmacokinetic studies: a chemometrics approach to search for novel inhibitors of norepinephrine transporter as potent antipsychotic drugs. Journal of the Iranian Chemical Society. el 10 de agosto de 2020;17(8):1953Yang D, Zhou Q, Labroska V, Qin S, Darbalaei S, Wu Y, et al. G protein-coupled receptors: structure- and function-based drug discovery. Vol. 6, Signal Transduction and Targeted Therapy. Springer Nature; 2021.Darwish HW, Hassan SA, Salem MY, El-Zeany BA. Advanced stability indicating chemometric methods for quantitation of amlodipine and atorvastatin in their quinary mixture with acidic degradation products. Spectrochim Acta A Mol Biomol Spectrosc. el 5 de febrero de 2016;154:58–66.Vashist SK. Comparison of 1-Ethyl-3-(3-Dimethylaminopropyl) Carbodiimide Based Strategies to Crosslink Antibodies on Amine-Functionalized Platforms for Immunodiagnostic Applications. Diagnostics. el 27 de agosto de 2012;2(3):23–33.Acceso cerradoinfo:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbspaLICENSElicense.txtlicense.txttext/plain; charset=utf-82000https://repositorio.unbosque.edu.co/bitstreams/c5c94fcc-d8e2-41b5-815f-ca4e5a415289/download17cc15b951e7cc6b3728a574117320f9MD51Carta de autorizacion.pdfapplication/pdf304528https://repositorio.unbosque.edu.co/bitstreams/f304a444-7eeb-49ea-88cd-20a5b16b2f01/downloadbecc3fb4402ac816e2ee6fcb20911168MD55Anexo 1 Acta de aprobacion.pdfapplication/pdf1848248https://repositorio.unbosque.edu.co/bitstreams/4f566ffb-a40f-4879-8e6d-2505b1a0c2aa/downloadf45353571c76a35117d78f99d9e2a72eMD56ORIGINALTrabajo de grado.pdfTrabajo de grado.pdfapplication/pdf2085944https://repositorio.unbosque.edu.co/bitstreams/8892dfcc-e484-47af-9d89-68551c0a879b/downloadb6da9a588b031ca62f618d7d405dbf75MD52TEXTTrabajo de grado.pdf.txtTrabajo de grado.pdf.txtExtracted texttext/plain71562https://repositorio.unbosque.edu.co/bitstreams/39337d21-4d25-4df1-ae9d-71eca88ffc52/download563fc1d5bfe0f39938994fb6a39a67cbMD57THUMBNAILTrabajo de grado.pdf.jpgTrabajo de grado.pdf.jpgGenerated Thumbnailimage/jpeg5589https://repositorio.unbosque.edu.co/bitstreams/153dd917-59e8-461d-9cf1-8920f1420edb/downloadf0a1441e8d6d9ba544551ac99e7ad164MD5820.500.12495/12092oai:repositorio.unbosque.edu.co:20.500.12495/120922024-05-10 03:03:55.104embargo2026-05-27https://repositorio.unbosque.edu.coRepositorio Institucional Universidad El Bosquebibliotecas@biteca.com |