Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives
In this work, the SOFT.PTML tool has been used to pre-process a ChEMBL dataset of pre-clinical assays of antileishmanial compound candidates. A comparative study of different ML algorithms, such as logistic regression (LOGR), support vector machine (SVM), and random forests (RF), has shown that the...
| Autores: | , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad del País Vasco |
| Repositorio: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/64181 |
| Acceso en línea: | http://hdl.handle.net/10810/64181 |
| Access Level: | acceso abierto |
| Palabra clave: | palladium C-H activation leishmania machine learning cheminformatics |
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oai:addi.ehu.eus:10810/64181 |
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Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives Santiago Alvarez, Carlos Ortega-Tenezaca, Bernabé Barbolla Cuadrado, Iratxe Fundora Ortiz, Brenda Arrasate Gil, Sonia Dea-Ayuela, María Auxiliadora González Díaz, Humberto Sotomayor Anduiza, María Nuria palladium C-H activation leishmania machine learning cheminformatics In this work, the SOFT.PTML tool has been used to pre-process a ChEMBL dataset of pre-clinical assays of antileishmanial compound candidates. A comparative study of different ML algorithms, such as logistic regression (LOGR), support vector machine (SVM), and random forests (RF), has shown that the IFPTML-LOGR model presents excellent values of specificity and sensitivity (81−98%) in training and validation series. The use of this software has been illustrated with a practical case study focused on a series of 28 derivatives of 2-acylpyrroles 5a,b, obtained through a Pd(II)-catalyzed C−H radical acylation of pyrroles. Their in vitro leishmanicidal activity against visceral (L. donovani) and cutaneous (L. amazonensis) leishmaniasis was evaluated finding that compounds 5bc (IC50 = 30.87 μM, SI > 10.17) and 5bd (IC50 = 16.87 μM, SI > 10.67) were approximately 6-fold more selective than the drug of reference (miltefosine) in in vitro assays against L. amazonensis promastigotes. In addition, most of the compounds showed low cytotoxicity, CC50 > 100 μg/ mL in J774 cells. Interestingly, the IFPMTL-LOGR model predicts correctly the relative biological activity of these series of acylpyrroles. A computational high-throughput screening (cHTS) study of 2-acylpyrroles 5a,b has been performed calculating >20,700 activity scores vs a large space of 647 assays involving multiple Leishmania species, cell lines, and potential target proteins. Overall, the study demonstrates that the SOFT.PTML all-in-one strategy is useful to obtain IFPTML models in a friendly interface making the work easier and faster than before. The present work also points to 2-acylpyrroles as new lead compounds worthy of further optimization as antileishmanial hits. Ministerio de Ciencia e Innovación (PID2019-104148GB-I00), Gobierno Vasco (IT1558-22) ACS http://hdl.handle.net/10810/64181 |
| title |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives |
| spellingShingle |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives Santiago Alvarez, Carlos palladium C-H activation leishmania machine learning cheminformatics |
| title_short |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives |
| title_full |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives |
| title_fullStr |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives |
| title_full_unstemmed |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives |
| title_sort |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives |
| author |
Santiago Alvarez, Carlos |
| author_facet |
Santiago Alvarez, Carlos Ortega-Tenezaca, Bernabé Barbolla Cuadrado, Iratxe Fundora Ortiz, Brenda Arrasate Gil, Sonia Dea-Ayuela, María Auxiliadora González Díaz, Humberto Sotomayor Anduiza, María Nuria |
| author_role |
author |
| author2 |
Ortega-Tenezaca, Bernabé Barbolla Cuadrado, Iratxe Fundora Ortiz, Brenda Arrasate Gil, Sonia Dea-Ayuela, María Auxiliadora González Díaz, Humberto Sotomayor Anduiza, María Nuria |
| author2_role |
author author author author author author author |
| topic |
palladium C-H activation leishmania machine learning cheminformatics |
| topic_facet |
palladium C-H activation leishmania machine learning cheminformatics |
| description |
In this work, the SOFT.PTML tool has been used to pre-process a ChEMBL dataset of pre-clinical assays of antileishmanial compound candidates. A comparative study of different ML algorithms, such as logistic regression (LOGR), support vector machine (SVM), and random forests (RF), has shown that the IFPTML-LOGR model presents excellent values of specificity and sensitivity (81−98%) in training and validation series. The use of this software has been illustrated with a practical case study focused on a series of 28 derivatives of 2-acylpyrroles 5a,b, obtained through a Pd(II)-catalyzed C−H radical acylation of pyrroles. Their in vitro leishmanicidal activity against visceral (L. donovani) and cutaneous (L. amazonensis) leishmaniasis was evaluated finding that compounds 5bc (IC50 = 30.87 μM, SI > 10.17) and 5bd (IC50 = 16.87 μM, SI > 10.67) were approximately 6-fold more selective than the drug of reference (miltefosine) in in vitro assays against L. amazonensis promastigotes. In addition, most of the compounds showed low cytotoxicity, CC50 > 100 μg/ mL in J774 cells. Interestingly, the IFPMTL-LOGR model predicts correctly the relative biological activity of these series of acylpyrroles. A computational high-throughput screening (cHTS) study of 2-acylpyrroles 5a,b has been performed calculating >20,700 activity scores vs a large space of 647 assays involving multiple Leishmania species, cell lines, and potential target proteins. Overall, the study demonstrates that the SOFT.PTML all-in-one strategy is useful to obtain IFPTML models in a friendly interface making the work easier and faster than before. The present work also points to 2-acylpyrroles as new lead compounds worthy of further optimization as antileishmanial hits. |
| publishDate |
2022 |
| format |
article |
| url |
http://hdl.handle.net/10810/64181 |
| eu_rights_str_mv |
openAccess |
| publisher |
ACS |
| institution |
Universidad del País Vasco |
| collection |
Addi. Archivo Digital para la Docencia y la Investigación |
| reponame_str |
Addi. Archivo Digital para la Docencia y la Investigación |
| instname_str |
Universidad del País Vasco |
| _version_ |
1878432955247886336 |
| publishDateSort |
2022 |
| author_browse |
Arrasate Gil, Sonia Barbolla Cuadrado, Iratxe Dea-Ayuela, María Auxiliadora Fundora Ortiz, Brenda González Díaz, Humberto Ortega-Tenezaca, Bernabé Santiago Alvarez, Carlos Sotomayor Anduiza, María Nuria |
| publisherStr |
ACS |
| score |
6,924472 |