Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches
Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approache...
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| Format: | Article |
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MDPI AG
2020-09-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/25/18/4183 |
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| author | Pedro H. F. Araújo Ryan S. Ramos Jorddy N. da Cruz Sebastião G. Silva Elenilze F. B. Ferreira Lúcio R. de Lima Williams J. C. Macêdo José M. Espejo-Román Joaquín M. Campos Cleydson B. R. Santos |
| author_facet | Pedro H. F. Araújo Ryan S. Ramos Jorddy N. da Cruz Sebastião G. Silva Elenilze F. B. Ferreira Lúcio R. de Lima Williams J. C. Macêdo José M. Espejo-Román Joaquín M. Campos Cleydson B. R. Santos |
| author_sort | Pedro H. F. Araújo |
| collection | DOAJ |
| description | Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson’s correlation for the construction of quantitative structure–activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R<sup>2</sup> = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, <b>Z-964</b>, <b>Z-627</b>, and <b>Z-814</b>, with their predicted pIC<sub>50</sub> (−log IC<sub>50</sub>) values, <b>Z-814</b> = 7.9484, <b>Z-627</b> = 9.3458, and <b>Z-964</b> = 9.5272. All candidates inhibitors complied with Lipinski’s rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data. |
| first_indexed | 2024-03-10T16:22:43Z |
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| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T16:22:43Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
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| series | Molecules |
| spelling | doaj.art-a33310ece1514aaab1316be5262273bc2023-11-20T13:32:04ZengMDPI AGMolecules1420-30492020-09-012518418310.3390/molecules25184183Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling ApproachesPedro H. F. Araújo0Ryan S. Ramos1Jorddy N. da Cruz2Sebastião G. Silva3Elenilze F. B. Ferreira4Lúcio R. de Lima5Williams J. C. Macêdo6José M. Espejo-Román7Joaquín M. Campos8Cleydson B. R. Santos9Graduate Program in Innovation Pharmaceutical, Federal University of Amapá, 68903-419 Amapá-AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, 68902-280 Macapá-AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, 68902-280 Macapá-AP, BrazilCampus Abaetetuba, Universidade Federal do Para, Ramal Manoel de Abreu, s/n-Mutirão, Abaetetuba, 68440-000 Pará, BrazilGraduate Program in Innovation Pharmaceutical, Federal University of Amapá, 68903-419 Amapá-AP, BrazilLaboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, 68902-280 Macapá-AP, BrazilGraduate Program in Innovation Pharmaceutical, Federal University of Amapá, 68903-419 Amapá-AP, BrazilDepartment of Pharmaceutical Organic Chemistry, Faculty of Pharmacy, Biosanitary Institute of Granada (Ibs.GRANADA), Campus of Cartuja s/n, University of Granada, 18071 Granada, SpainDepartment of Pharmaceutical Organic Chemistry, Faculty of Pharmacy, Biosanitary Institute of Granada (Ibs.GRANADA), Campus of Cartuja s/n, University of Granada, 18071 Granada, SpainGraduate Program in Innovation Pharmaceutical, Federal University of Amapá, 68903-419 Amapá-AP, BrazilNon-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson’s correlation for the construction of quantitative structure–activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R<sup>2</sup> = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, <b>Z-964</b>, <b>Z-627</b>, and <b>Z-814</b>, with their predicted pIC<sub>50</sub> (−log IC<sub>50</sub>) values, <b>Z-814</b> = 7.9484, <b>Z-627</b> = 9.3458, and <b>Z-964</b> = 9.5272. All candidates inhibitors complied with Lipinski’s rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data.https://www.mdpi.com/1420-3049/25/18/4183in silicoCOX-2 inhibitorsmolecular modeling |
| spellingShingle | Pedro H. F. Araújo Ryan S. Ramos Jorddy N. da Cruz Sebastião G. Silva Elenilze F. B. Ferreira Lúcio R. de Lima Williams J. C. Macêdo José M. Espejo-Román Joaquín M. Campos Cleydson B. R. Santos Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches Molecules in silico COX-2 inhibitors molecular modeling |
| title | Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches |
| title_full | Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches |
| title_fullStr | Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches |
| title_full_unstemmed | Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches |
| title_short | Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches |
| title_sort | identification of potential cox 2 inhibitors for the treatment of inflammatory diseases using molecular modeling approaches |
| topic | in silico COX-2 inhibitors molecular modeling |
| url | https://www.mdpi.com/1420-3049/25/18/4183 |
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