التفاصيل البيبلوغرافية
| العنوان: |
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives [Dataset] |
| المؤلفون: |
Santiago, Carlos, Ortega Tenezaca, Bernabé, Barbolla, Iratxe, Fundora, Brenda, Arrasate, Sonia, Dea-Ayuela, M. Auxiliadora, González-Díaz, Humberto, Sotomayor, Nuria, Lete, Esther |
| بيانات النشر: |
Figshare |
| سنة النشر: |
2022 |
| المجموعة: |
Digital.CSIC (Consejo Superior de Investigaciones Científicas / Spanish National Research Council) |
| مصطلحات موضوعية: |
Potential target proteins, Friendly interface making, Relative biological activity, 700 activity scores, Antileishmanial compound candidates, 5bd, 5bc, Obtain ifptml models, Different ml algorithms, Leishmanicidal activity, vs, Vitro, Leishmania, Antileishmanial hits, Throughput screening, Svm ), rf ), Random forests, Performed calculating, One strategy, Logistic regression, Large space, j774 cells, General model, Evaluated finding, Computational high, Chembl dataset, Cell lines |
| Time: |
50 |
| الوصف: |
1 table. -- ChEMBL dataset used to train and validate the model, compounds codes, SMILE codes, preclinical assay conditions, observed values, predicted classifications, probabilities, etc. ; 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. ; Peer reviewed |
| نوع الوثيقة: |
dataset |
| وصف الملف: |
application/vnd.ms-excel |
| اللغة: |
English |
| Relation: |
Santiago, Carlos; Ortega Tenezaca, Bernabé; Barbolla, Iratxe; Fundora, Brenda; Arrasate, Sonia; Dea-Ayuela, M. Auxiliadora; González-Díaz, Humberto; Sotomayor, Nuria; Lete, Esther. Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2-Acylpyrrole Derivatives. http://dx.doi.org/10.1021/acs.jcim.2c00731. http://hdl.handle.net/10261/304205; https://doi.org/10.1021/acs.jcim.2c00731.s001; Sí; Santiago, Carlos; Ortega Tenezaca, Bernabé; Barbolla, Iratxe; Fundora, Brenda; Arrasate, Sonia; Dea-Ayuela, M. Auxiliadora; González-Díaz, Humberto; Sotomayor, Nuria; Lete, Esther; 2022; Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives [Dataset]; Figshare; https://doi.org/10.1021/acs.jcim.2c00731.s001; http://hdl.handle.net/10261/331583 |
| DOI: |
10.1021/acs.jcim.2c00731.s001 |
| الاتاحة: |
http://hdl.handle.net/10261/331583
https://doi.org/10.1021/acs.jcim.2c00731.s001 |
| Rights: |
open |
| رقم الانضمام: |
edsbas.FDEBCA9C |
| قاعدة البيانات: |
BASE |