Search results for "Quantitative Structure-Activity Relationship"
showing 10 items of 113 documents
QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents
2015
The QuBiLs-MAS approach is used for the in silico modelling of the antifungal activity of organic molecules. To this effect, non-stochastic (NS) and simple-stochastic (SS) atom-based quadratic indices are used to codify chemical information for a comprehensive dataset of 2478 compounds having a great structural variability, with 1087 of them being antifungal agents, covering the broadest antifungal mechanisms of action known so far. The NS and SS index-based antifungal activity classification models obtained using linear discriminant analysis (LDA) yield correct classification percentages of 90.73% and 92.47%, respectively, for the training set. Additionally, these models are able to correc…
Comparative study to predict toxic modes of action of phenols from molecular structures.
2013
Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. M…
Kinetic and thermodynamic insights into interaction of erlotinib with epidermal growth factor receptor: Surface plasmon resonance and molecular docki…
2020
Abstract Epidermal growth factor receptor (EGFR) plays an important role in cell proliferation at non-small cell lung cancer (NSCLC). Therefore, targeted therapy of cancer via this kind of receptor is highly interested. Small molecule drugs such as erlotinib and gefitinib inhibit EGFR tyrosine kinase and thus suppress cell proliferation. At this paper, erlotinib interaction with EGFR on the cell surface was studied via surface plasmon resonance (SPR) and molecular docking methods. Kinetic parameters indicated that erlotinib affinity toward EGFR was increased through increment of temperature. The thermodynamic analysis showed that van der Waals and hydrogen binding forces play a major role i…
Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree
2021
Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation p…
Prediction of acute toxicity of organophosphorus pesticides using topological indices
2007
Topological indices were used in the prediction of the acute toxicity (intraperitoneal and oral LD(50)) of organophosphorus pesticides on rats. Models with six variables for the prediction of LD(50)-i.p. (r = 0.849, Q(2) = 0.613) and eight variables for LD(50)-oral (r = 0.906, Q(2) = 0.701) were selected. External group and cross-validation by use of leave-n-out tests were also performed in order to assess the stability and the prediction performance of the selected topological models.
Quantitative structure-retention and retention-activity relationships of beta-blocking agents by micellar liquid chromatography.
2001
Abstract Sixteen β-blocking agents (acebutolol, alprenolol, atenolol, bisoprolol, carteolol, celiprolol, esmolol, labetalol, metoprolol, nadolol, oxprenolol, pindolol, practolol, propranolol, sotalol and timolol) showing a large range of hydrophobicity (octanol–water partition coefficients, log P between −0.026 and 2.81) were subjected to micellar liquid chromatography with sodium dodecyl sulfate as micelle forming agent, and n-propanol as organic modifier. The correlation between log P and the retention factor extrapolated to a mobile phase free of micelles and organic modifier was investigated. The use of an interpolated retention factor or the retention factor for specific individual exp…
Biopartitioning micellar chromatography to pedict mutagenicity of aromatic amines
2007
[EN] Mutagenicity is a toxicity endpoint associated with the chronic exposure to chemicals. Aromatic amines have considerable industrial and environmental importance due to their widespread use in industry and their mutagenic capacity. Biopartitioning micellar chromatography (BMC), a mode of micellar liquid chromatography that uses micellar mobile phases of Brij35 in adequate experimental conditions, has demonstrated to be useful in mimicking the drug partitioning process into biological systems. In this paper, the usefulness of BMC for predicting mutagenicity of aromatic amines is demonstrated. A multiple linear regression (MLR) model based on BMC retention data is proposed and compared wi…
Reliability of Virtual Screening Methods in Prediction of PDE4Binhibitor Activity
2015
Identification of active ligands using computational methods is a challenging task. For example, molecular docking, pharmacophore modeling, and three dimensional quantitative structure-activity relationship models (3D-QSAR) are widely used methods to identify novel small molecules. However, all these methods have, in addition to advantages, also significant pitfalls. The aim of this study was to compare some commonly used computational methods to estimate their ability to separate highly active PDE4B-inhibitors from less active and inactive ones. Here, 152 molecules with pIC 50 -range of 3.4-10.5, originating from six original studies were used. High correlation coefficients by using dockin…
Ligand-based discovery of novel trypanosomicidal drug-like compounds: In silico identification and experimental support
2010
Abstract Two-dimensional bond-based linear indices and linear discriminant analysis are used in this report to perform a quantitative structure–activity relationship study to identify new trypanosomicidal compounds. A database with 143 anti-trypanosomal and 297 compounds having other clinical uses, are utilized to develop the theoretical models. The best discriminant models computed using bond-based linear indices provides accuracies greater than 90 for both training and test sets. Our models identify as anti-trypanosomals five out of nine compounds of a set of already-synthesized substances. The in vitro anti-trypanosomal activity of this set against epimastigote forms of Trypanosoma cruzi…
Atom- and Bond-Based 2D TOMOCOMD-CARDD Approach and Ligand-Based Virtual Screening for the Drug Discovery of New Tyrosinase Inhibitors
2008
Two-dimensional atom- and bond-based TOMOCOMD-CARDD descriptors and linear discriminant analysis (LDA) are used in this report to perform a quantitative structure-activity relationship (QSAR) study of tyrosinase-inhibitory activity. A database of inhibitors of the enzyme is collected for this study, within 246 highly dissimilar molecules presenting antityrosinase activity. In total, 7 discriminant functions are obtained by using the whole set of atom- and bond-based 2D indices. All the LDA-based QSAR models show accuracies above 90% in the training set and values of the Matthews correlation coefficient (C) varying from 0.85 to 0.90. The external validation set shows globally good classifica…