A QSAR study was developed in order to model the antioxidant activity, specifically the radical scavenger activity (RSA), of 26 di(hetero)arylamines' derivatives of benzo[b]thiophenes. The QSAR model was constructed, using the partial least squares projection of latent structures (PLS) method, and its robustness and predictability were verified by internal and external cross-validation methods....

Quantitative structure-activity relationship (QSAR) software offers a rapid, cost effective means of prioritizing the mutagenic potential of chemicals. MDL QSAR models were developed using atom-type E-state indices and non-parametric discriminant analysis. Models were developed for Salmonella typhimurium gene mutation, combining results from strains TA97, TA98, TA100, TA1535, TA1536, TA1537, an...

BACKGROUND Monoterpenoids are a large group of plant secondary metabolites. Many of these naturally occurring compounds have shown good insecticidal potency on pest insects. Previous studies in this laboratory have indicated that some monoterpenoids have positive modulatory effects on insect GABA receptors. In this study, the key properties of monoterpenoids involved in monoterpenoid binding ac...

BACKGROUND The emergence of drug resistant tuberculosis poses a serious concern globally and researchers are in rigorous search for new drugs to fight against these dreadful bacteria. Recently, the bacterial GlmU protein, involved in peptidoglycan, lipopolysaccharide and techoic acid synthesis, has been identified as an important drug target. A unique C-terminal disordered tail, essential for s...

Alignment-free, three dimensional structure–activity relationships (3D QSAR) of the antiproliferative potency of twenty-two glutarimide-containing compounds, taken from National Cancer Institute Developmental therapeutics Program database, toward eight representative human tumour cell lines are reported. The descriptors used in the QSAR study were derived from GRID molecular interaction fields....

BACKGROUND Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally ...

This study describes the generation of a three-dimensional quantitative structure activity relationship (3D-QSAR) model for 29 structurally diverse, competitive CYP2C9 inhibitors defined experimentally from an initial data set of 73 compounds. In parallel, a homology model for CYP2C9 using the rabbit CYP2C5 coordinates was built. For molecules with a known interaction mode with CYP2C9, this hom...

Scientific disciplines such as medicinal- and environmental chemistry, pharmacology, and toxicology deal with the questions related to the effects small organic compounds exhort on biological targets and the compounds' physicochemical properties responsible for these effects. A common strategy in this endeavor is to establish structure-activity relationships (SARs). The aim of this work was to ...

Phosphodiesterase-4 (PDE-4) is an important drug target for several diseases, including COPD (chronic obstructive pulmonary disorder) and neurodegenerative diseases. In this paper, we describe the development of improved QSAR (quantitative structure-activity relationship) models using a novel multi-conformational structure-based pharmacophore key (MC-SBPPK) method. Similar to our previous work,...

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the local lymph node assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, for eaxample, quantitative structure-activity relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data hav...