Investigating SAR Insights into Royleanones for P-gp Modulation
Multidrug resistance (MDR) presents a significant challenge in modern pharmacotherapy, greatly diminishing the effectiveness of chemotherapeutic agents. A primary mechanism contributing to MDR is the overexpression of P-glycoprotein (P-gp), also known as MDR1, encoded by the ABCB1 gene, which hamper...
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MDPI AG
2024-12-01
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| author | Gabrielle Bangay Vera M. S. Isca Florencia Z. Brauning Jelena Dinic Milica Pesic Bernardo Brito Palma Daniel J. V. A. dos Santos Ana M. Díaz-Lanza Eduardo Borges de Melo João Paulo Ataide Martins Patrícia Rijo |
| author_facet | Gabrielle Bangay Vera M. S. Isca Florencia Z. Brauning Jelena Dinic Milica Pesic Bernardo Brito Palma Daniel J. V. A. dos Santos Ana M. Díaz-Lanza Eduardo Borges de Melo João Paulo Ataide Martins Patrícia Rijo |
| author_sort | Gabrielle Bangay |
| collection | DOAJ |
| description | Multidrug resistance (MDR) presents a significant challenge in modern pharmacotherapy, greatly diminishing the effectiveness of chemotherapeutic agents. A primary mechanism contributing to MDR is the overexpression of P-glycoprotein (P-gp), also known as MDR1, encoded by the ABCB1 gene, which hampers the success of cancer treatments. Plants from the <i>Plectranthus</i> genus (Lamiaceae) have been traditionally acknowledged for their diverse therapeutic applications. The principal diterpene from <i>Plectranthus grandidentatus</i> Gürke, 7α-acetoxy-6β-hydroxyroyleanone (Roy), has demonstrated anticancer properties against various cancer cell lines. Previously synthesized ester derivatives of Roy have shown improved binding affinity to P-gp. This study employs previously acquired in vitro data on the P-gp activity of Roy derivatives to develop a ligand-based pharmacophore model, highlighting critical features necessary for P-gp modulation. Utilizing these data, we predict the potential of five novel ester derivatives of Roy to modulate P-gp in vitro against resistant NCI-H460 cells. In silico structure–activity relationship (SAR) studies were conducted on 17 previously synthesized royleanone derivatives. A binary classification model was constructed, distinguishing inactive from active compounds, generating 11,016 molecular interaction field (MIF) descriptors from structures optimized at the DFT level. After variable reduction and selection, 12 descriptors were chosen, resulting in a model with two latent variables (LV), using only 34.14% of the encoded information for calibration (LV1: 26.82%; LV2: 7.32%). The activity prediction of new derivatives suggested that four of them have a high likelihood of activity, which will be validated in future in vitro biological assays. |
| format | Article |
| id | doaj-art-4e72ea1c2ba741d5bcf775edf16a66cc |
| institution | Kabale University |
| issn | 2673-4583 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Chemistry Proceedings |
| spelling | doaj-art-4e72ea1c2ba741d5bcf775edf16a66cc2025-08-20T03:27:21ZengMDPI AGChemistry Proceedings2673-45832024-12-011613510.3390/ecsoc-28-20158Investigating SAR Insights into Royleanones for P-gp ModulationGabrielle Bangay0Vera M. S. Isca1Florencia Z. Brauning2Jelena Dinic3Milica Pesic4Bernardo Brito Palma5Daniel J. V. A. dos Santos6Ana M. Díaz-Lanza7Eduardo Borges de Melo8João Paulo Ataide Martins9Patrícia Rijo10Center for Research in Biosciences & Health Technologies (CBIOS), Universidade Lusófona, 1749-024 Lisboa, PortugalCenter for Research in Biosciences & Health Technologies (CBIOS), Universidade Lusófona, 1749-024 Lisboa, PortugalCenter for Research in Biosciences & Health Technologies (CBIOS), Universidade Lusófona, 1749-024 Lisboa, PortugalInstitute for Biological Research “Siniša Stanković”—National Institute of Republic of Serbia, University of Belgrade, Despota Stefana 142, 11060 Belgrade, SerbiaInstitute for Biological Research “Siniša Stanković”—National Institute of Republic of Serbia, University of Belgrade, Despota Stefana 142, 11060 Belgrade, SerbiaCenter for Research in Biosciences & Health Technologies (CBIOS), Universidade Lusófona, 1749-024 Lisboa, PortugalCenter for Research in Biosciences & Health Technologies (CBIOS), Universidade Lusófona, 1749-024 Lisboa, PortugalFacultad de Farmacia, Departamento de Ciencias Biomédicas (Área de Farmacología), Universidad de Alcalá de Henares, 28805 Alcalá de Henares, Madrid, SpainTheoretical Medicinal and Environmental Chemistry Laboratory (LQMAT), Department of Pharmacy, Western Paraná State University (UNIOESTE), Cascavel 85819-110, PR, BrazilDepartment of Chemistry, Federal University of Minas Gerais (UFMG), Belo Horizonte 31270-901, MG, BrazilCenter for Research in Biosciences & Health Technologies (CBIOS), Universidade Lusófona, 1749-024 Lisboa, PortugalMultidrug resistance (MDR) presents a significant challenge in modern pharmacotherapy, greatly diminishing the effectiveness of chemotherapeutic agents. A primary mechanism contributing to MDR is the overexpression of P-glycoprotein (P-gp), also known as MDR1, encoded by the ABCB1 gene, which hampers the success of cancer treatments. Plants from the <i>Plectranthus</i> genus (Lamiaceae) have been traditionally acknowledged for their diverse therapeutic applications. The principal diterpene from <i>Plectranthus grandidentatus</i> Gürke, 7α-acetoxy-6β-hydroxyroyleanone (Roy), has demonstrated anticancer properties against various cancer cell lines. Previously synthesized ester derivatives of Roy have shown improved binding affinity to P-gp. This study employs previously acquired in vitro data on the P-gp activity of Roy derivatives to develop a ligand-based pharmacophore model, highlighting critical features necessary for P-gp modulation. Utilizing these data, we predict the potential of five novel ester derivatives of Roy to modulate P-gp in vitro against resistant NCI-H460 cells. In silico structure–activity relationship (SAR) studies were conducted on 17 previously synthesized royleanone derivatives. A binary classification model was constructed, distinguishing inactive from active compounds, generating 11,016 molecular interaction field (MIF) descriptors from structures optimized at the DFT level. After variable reduction and selection, 12 descriptors were chosen, resulting in a model with two latent variables (LV), using only 34.14% of the encoded information for calibration (LV1: 26.82%; LV2: 7.32%). The activity prediction of new derivatives suggested that four of them have a high likelihood of activity, which will be validated in future in vitro biological assays.https://www.mdpi.com/2673-4583/16/1/35SARroyleanonesP-gpmultidrug resistance<i>Plectranthus</i> |
| spellingShingle | Gabrielle Bangay Vera M. S. Isca Florencia Z. Brauning Jelena Dinic Milica Pesic Bernardo Brito Palma Daniel J. V. A. dos Santos Ana M. Díaz-Lanza Eduardo Borges de Melo João Paulo Ataide Martins Patrícia Rijo Investigating SAR Insights into Royleanones for P-gp Modulation Chemistry Proceedings SAR royleanones P-gp multidrug resistance <i>Plectranthus</i> |
| title | Investigating SAR Insights into Royleanones for P-gp Modulation |
| title_full | Investigating SAR Insights into Royleanones for P-gp Modulation |
| title_fullStr | Investigating SAR Insights into Royleanones for P-gp Modulation |
| title_full_unstemmed | Investigating SAR Insights into Royleanones for P-gp Modulation |
| title_short | Investigating SAR Insights into Royleanones for P-gp Modulation |
| title_sort | investigating sar insights into royleanones for p gp modulation |
| topic | SAR royleanones P-gp multidrug resistance <i>Plectranthus</i> |
| url | https://www.mdpi.com/2673-4583/16/1/35 |
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