Selection of 2D/3D molecular descriptors and QSAR modeling of aromatic Morita–Baylis–Hillman adducts with leishmanicidal activities

Aromatic Morita–Baylis–Hillman adducts (MBHA) are a class of compounds which have shown antiparasitic potential in tropical diseases (such as Leishmaniases, Chagas disease, malaria). MBHA analogs have been studied by our research group on synthetical, theoretical, and bioactivity aspects. We present...

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Bibliographic Details
Published in:Medicinal chemistry research 2014, Vol.23 (12), p.5328-5335
Main Authors: Alencar Filho, Edilson B., Weber, Karen C., Vasconcellos, Mário L. A. A.
Format: Article
Language:English
Subjects:
Adducts
Algorithms
Antiparasitic agents
Aromatic compounds
Biochemistry
Biological activity
Biomedical and Life Sciences
Biomedicine
Cell Biology
Chagas disease
Malaria
Modelling
Molecular structure
Original Research
Parameter robustness
Pharmacology/Toxicology
Prediction models
Structure-activity relationships
Three dimensional models
Tropical diseases
Two dimensional models
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Summary:Aromatic Morita–Baylis–Hillman adducts (MBHA) are a class of compounds which have shown antiparasitic potential in tropical diseases (such as Leishmaniases, Chagas disease, malaria). MBHA analogs have been studied by our research group on synthetical, theoretical, and bioactivity aspects. We present here a variable selection of 2D and 3D molecular descriptors, followed by quantitative structure–activity relationship (QSAR) modeling of thirty-two MBHA bioactive against the parasite Leishmania amazonensis . Descriptors were calculated by E-Dragon online platform. Variable selection was performed using ordered predictor selector (OPS) algorithm, and QSAR models were obtained using partial least squares (PLS). Internal and external validation parameters indicated a robust and predictive model, which may help the synthesis of most potent leishmanicidal compounds.
ISSN:1054-2523
1554-8120
DOI:10.1007/s00044-014-1077-y