Conformation-independent quantitative structure-property relationships study on water solubility of pesticides

SE Fioressi, DE Bacelo, C Rojas, JF Aranda… - Ecotoxicology and …, 2019 - Elsevier
Water solubility is a key physicochemical parameter in pesticide control and regulation,
although sometimes its experimental determination is not an easy task. In this study, we …

Linear regression QSAR models for polo-like kinase-1 inhibitors

PR Duchowicz - Cells, 2018 - mdpi.com
A structurally diverse dataset of 530 polo-like kinase-1 (PLK1) inhibitors is compiled from the
ChEMBL database and studied by means of a conformation-independent quantitative …

Predicting the bioconcentration factor through a conformation-independent QSPR study

JF Aranda, DE Bacelo… - SAR and QSAR in …, 2017 - Taylor & Francis
The ANTARES dataset is a large collection of known and verified experimental
bioconcentration factor data, involving 851 highly heterogeneous compounds from which …

Quantitative structure–activity relationship (QSAR) analysis of plant‐derived compounds with larvicidal activity against Zika Aedes aegypti (Diptera: Culicidae) vector …

LM Saavedra, GP Romanelli… - Pest management …, 2018 - Wiley Online Library
BACKGROUND We have developed a quantitative structure–activity relationship (QSAR)
model for predicting the larvicidal activity of 60 plant‐derived molecules against Aedes …

A non-conformational QSAR study for plant-derived larvicides against Zika Aedes aegypti L. vector

LM Saavedra, GP Romanelli, PR Duchowicz - Environmental Science and …, 2020 - Springer
A set of 263 plant-derived compounds with larvicidal activity against Aedes aegypti
L.(Diptera: Culicidae) vector is collected from the literature, and is studied by means of a non …

QSAR study of human epidermal growth factor receptor (EGFR) inhibitors: conformation-independent models

SE Fioressi, DE Bacelo, PR Duchowicz - Medicinal Chemistry Research, 2019 - Springer
Many compounds have been proposed and tested as human epidermal growth factor
receptor (EGFR) inhibitors for cancer treatment. Recently, new survival mechanisms of …

Mold2 Descriptors Facilitate Development of Machine Learning and Deep Learning Models for Predicting Toxicity of Chemicals

H Hong, J Liu, W Ge, S Sakkiah, W Guo… - Machine Learning and …, 2023 - Springer
Numerical description of chemical structures is necessary for development of machine
learning and deep learning models for predicting the potential toxicity of chemicals. Mold2 is …

Prediction of the aqueous solubility of diverse compounds by 2D-QSPR

SE Fioressi, DE Bacelo, JF Aranda… - Journal of Molecular …, 2020 - Elsevier
Non conformational QSPR models were built for the aqueous solubility (mol/L) at 25° C of
5610 structurally heterogeneous compounds, including pesticides, drugs and solvents …

The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification

M Przybyłek, W Studziński, A Gackowska… - … Science and Pollution …, 2019 - Springer
Develo** of theoretical tools can be very helpful for supporting new pollutant detection.
Nowadays, a combination of mass spectrometry and chromatographic techniques are the …

[PDF][PDF] In silico evaluation and docking studies of pyrazole analogs as potential autophagy modulators against pancreatic cancer cell line MIA PaCa-2

HHM Mohamed, A Hussien, AEM Saeed - Eur. J. Chem, 2020 - academia.edu
Autophagy is a conserved intracellular degradation process that delivers substrates
including bulk cytoplasm, organelles, aggregate-prone proteins, and infectious agents to …