Ensemble learning application to discover new trypanothione synthetase inhibitors.
Algorithms
Amide Synthases
/ antagonists & inhibitors
Antiprotozoal Agents
/ chemistry
Databases, Pharmaceutical
Drug Discovery
/ methods
Drug Evaluation, Preclinical
/ methods
Enzyme Inhibitors
/ chemistry
Humans
Machine Learning
Metabolic Networks and Pathways
Models, Theoretical
ROC Curve
Structure-Activity Relationship
Chagas disease
Ensemble learning
Machine learning
QSAR
Trypanosoma cruzi
Trypanothione synthetase
Journal
Molecular diversity
ISSN: 1573-501X
Titre abrégé: Mol Divers
Pays: Netherlands
ID NLM: 9516534
Informations de publication
Date de publication:
Aug 2021
Aug 2021
Historique:
received:
12
04
2021
accepted:
24
06
2021
pubmed:
16
7
2021
medline:
6
1
2022
entrez:
15
7
2021
Statut:
ppublish
Résumé
Trypanosomatid-caused diseases are among the neglected infectious diseases with the highest disease burden, affecting about 27 million people worldwide and, in particular, socio-economically vulnerable populations. Trypanothione synthetase (TryS) is considered one of the most attractive drug targets within the thiol-polyamine metabolism of typanosomatids, being unique, essential and druggable. Here, we have compiled a dataset of 401 T. brucei TryS inhibitors that includes compounds with inhibitory data reported in the literature, but also in-house acquired data. QSAR classifiers were derived and validated from such dataset, using publicly available and open-source software, thus assuring the portability of the obtained models. The performance and robustness of the resulting models were substantially improved through ensemble learning. The performance of the individual models and the model ensembles was further assessed through retrospective virtual screening campaigns. At last, as an application example, the chosen model-ensemble has been applied in a prospective virtual screening campaign on DrugBank 5.1.6 compound library. All the in-house scripts used in this study are available on request, whereas the dataset has been included as supplementary material.
Identifiants
pubmed: 34264440
doi: 10.1007/s11030-021-10265-9
pii: 10.1007/s11030-021-10265-9
doi:
Substances chimiques
Antiprotozoal Agents
0
Enzyme Inhibitors
0
Amide Synthases
EC 6.3.1.-
trypanothione synthetase
EC 6.3.1.9
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1361-1373Subventions
Organisme : FONCyT
ID : 2017-0643
Organisme : FONCyT
ID : 2016-02056
Organisme : UNLP
ID : 11/X785
Organisme : consejo nacional de investigaciones científicas y técnicas
ID : PIP11220130100311
Organisme : Fondo para la Cooperación del MERCOSUR
ID : COF 03/11
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
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