For the first time, a set of (43) natural sesquiterpene polyol esters isolated from the root bark of Celastrus angulatus Maxim and Euonymus japonicus Thunb were subjected to 3D-QSAR comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies, with the aim of proposing novel sesquiterpene-based compounds with optimal narcotic or insecticida...

Leading QSAR models provide supporting documentation in addition to a predicted toxicological value. Such information enables the toxicologist to explore the properties of chemical substances as well as to review and to increase the reliability of toxicity predictions. This article focuses on the use of this information in practice. We explore the supporting documentation provided by the EPISui...

An intriguing question in 3D-QSAR lies on which conformation(s) to use when generating molecular descriptors (MD) for correlation with bioactivity values. This is not a simple task because the bioactive conformation in molecule data sets is usually unknown and, therefore, optimized structures in a receptor-free environment are often used to generate the MD´s. In this case, a wrong conformationa...

Linear and nonlinear quantitative structure-activity relationship (QSAR) models and docking score functions were developed for dihydrofolate reductase (DHFR) inhibition by cycloguanil derivatives using small molecule descriptors derived from MOE and in silico docking energies. The best QSAR models and docking score functions were identified when using artificial neural networks optimized by evo...

There are two broadly-defined applications of artificial neural networks (ANNs) in SAR/QSAR modeling. The first is the use of networks as preprocessors to reduce the dimensionality of chemical descriptors for use in statistical or network models. The second is to create classification models for predictive toxicology. This report discusses the use of ANNs as classifiers in SAR/QSAR modeling and...

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 structure-activity relationship (QSAR) approach. A large number (26,761) of molecular descriptors are explored with the main intention of capturing the most relevant structural characteristics affecting the bioactivity. T...

The Quantitative Structure Activity Relationship (QSAR) study is performed over a set of 15, 4-alkyl/aryl-substituted 1- [benzofuran-2-yl-phenylmethyl]-1 H-triazoles derivatives. This study is based on the application of physicochemical parameters in QSAR. The parameters include (MR (molar refractivity), MW (molecular weight), Pc (parachor), St (surface tension), D (density), Ir (index of refra...

The Topoisomerase I enzyme has become an attractive target for the treatment of cancer. In this paper molecular dynamics, 2D and 3D QSAR and molecular docking studies were performed on 90 naphthoquinone derivatives as Topoisomerase I inhibitors by using the human Topo I-DNA cleavable complex. This model has the drug intercalated with its planar pharmacophore between +1 and -1 bp flanking cleava...

Derivation of quantitative structure-activity relationships (QSAR) usually involves computational models that relate a set of input variables describing the structural properties of the molecules for which the activity has been measured to the output variable representing activity. Many of the input variables may be correlated, and it is therefore often desirable to select an optimal subset of ...

A quantitative structure-activity relationship model was developed on a series of compounds containing oxadiazole-ligated pyrrole pharmacophore to identify key structural fragments required for anti-tubercular activity. Two-dimensional (2D) and three-dimensional (3D) QSAR studies were performed using multiple linear regression (MLR) analysis and k-nearest neighbour molecular field analysis (kNN...