Quantitative structure-activity relationship (QSAR) studies are useful computational tools often used in drug discovery research and in many scientific disciplines. In this study, a robust fragment-similarity-based QSAR (FS-QSAR) algorithm was developed to correlate structures with biological activities by integrating fragment-based drug design concept and a multiple linear regression method. S...

Several QSAR models have been developed using a linear optimization approach that enabled distinguishing metabolic substances isolated from human-, bacterial-, plant- and fungal- cells. Seven binary classifiers based on a k-Nearest Neighbors method have been created using a variety of 'inductive' and traditional QSAR descriptors that allowed up to 95% accurate recognition of the studied groups ...

Farnesyltranseferase inhibitors (FTIs) are one of the most promising classes of anticancer agents, but though some compounds in this category are in clinical trials there are no marketed drugs in this class yet. Quantitative structure activity relationship (QSAR) models can be used for predicting the activity of FTI candidates in early stages of drug discovery. In this study 192 imidazole-conta...

objective(s): the structure- activity relationship of a series of 36 molecules, showing l-type calcium channel blocking was studied using a qsar (quantitative structure–activity relationship) method. materials and methods: structures were optimized by the semi-empirical am1 quantum-chemical method which was also used to find structure-calcium channel blocking activity trends. several types of d...

Histamine H3 receptor subtype has been the target of several recent drug development programs. Quantitative structure-activity relationship (QSAR) methods are used to predict the pharmaceutically relevant properties of drug candidates whenever it is applicable. The aim of this study was to compare the predictive powers of three different QSAR techniques, namely, multiple linear regression (MLR)...

This study concentrates on the external validation of an existing Quantitative Structure-Activity Relationship (QSAR) model widely used for long-term aquatic toxicity to fish. In the context of the REACH legislation, QSARs are used as an alternative for experimental data to achieve a complete environmental assessment without the need for animal testing. The predictivity of the model was evaluat...

Quantitative structure activity relationship (QSAR) models can be used to predict the activity of new drug candidates in early stages of drug discovery. In the present study, the information of the ninety two 2,5-diaminobenzophenone-containing farnesyltranaferase inhibitors (FTIs) were taken from the literature. Subsequently, the structures of the molecules were optimized using Hyperchem softwa...

BACKGROUND QSAR is an established and powerful method for cheap in silico assessment of physicochemical properties and biological activities of chemical compounds. However, QSAR models are rather complex mathematical constructs that cannot easily be interpreted. Medicinal chemists would benefit from practical guidance regarding which molecules to synthesize. Another possible approach is analysi...

The implementation of OFDM transmitters typically consists of a discrete DFT matrix and a digital-to-analog (DAC) converter. Many existing results on the analysis of OFDM systems, e.g., spectral roll-off, are based on a convenient analog representation. In this paper, we show that the analog representation and the DFT-based OFDM transmitters are equivalent only in special cases. Using the analo...

In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector m...