The comparative molecular field analysis (CoMFA) based on three dimensional quantitative structure–activity relationship (3D-QSAR) studies were carried out employing, natural terpenes as potent antimycobacterial agents. The best prediction were obtained with a CoMFA standard model (q2 = 0.569, r2 = 0.999) using steric, electrostatic, hydrophobic and hydrogen bond donor fields. In the current st...

A new Receptor-Dependent LQTA-QSAR approach, RD-LQTA-QSAR, is proposed as a new 4D-QSAR method. It is an evolution of receptor independent LQTA-QSAR. This approach uses the free GROMACS package to carry out molecular dynamics simulations and generates a conformational ensemble profile for each compound. Such an ensemble is used to build molecular interaction field-based QSAR models, as in CoMFA...

A novel 4D-QSAR approach which makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package is presented in this study. This new methodology, named LQTA-QSAR (LQTA, Laboratório de Quimiometria Teórica e Aplicada), has a module (LQTAgrid) that calculates intermolecular interaction energies at each grid point considering probes and all aligned ...

The proposed REACH (Registration, Evaluation and Authorisation of Chemicals) regulation calls for reducing of animal testing by using alternative methods. QSAR (Quantitative structure–activity relationship) approaches provide a valuable means of achieving this goal. Compared with the QSAR modelling of ecotoxicological endpoints, the modelling of mammalian toxicity is more complicated. The main ...

A compound 2-(anilino)-1-(4-phenylphenyl)ethanone was synthesized by reaction between biphenyl acid chloride and aniline. The synthesized compound was screened for analgesic activity. The selection of the compound was on the basis of QSAR study performed on the biphenyl analogs having anti-inflammatory activity. 2D QSAR study using topological descriptors revealed the important features require...

A case study of toxicity of (benzo)triazoles ((B)TAZs) to the algae Pseudokirchneriella subcapitata is used to discuss some problems and solutions in QSAR modeling, particularly in the environmental context. The relevance of data curation (not only of experimental data, but also of chemical structures and input formats for the calculation of molecular descriptors), the crucial points of QSAR mo...

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature...

A common step in drug design is the formation of a quantitative structure-activity relationship (QSAR) to model an exploratory series of compounds. A QSAR generalizes how the structure of a compound relates to its biological activity. There is growing interest in the application of machine learning techniques in QSAR modeling research. However, no single technique can claim to be uniformly supe...

The quantitative structure-activity relationship (QSAR) model searches for a reliable relationship between the chemical structure and biological activities in the field of drug design and discovery. (1) Background: In the study of QSAR, the chemical structures of compounds are encoded by a substantial number of descriptors. Some redundant, noisy and irrelevant descriptors result in a side-effec...

In this paper, a three level in silico approach was applied to investigate some important structural and physicochemical aspects of a series of anthranilic acid derivatives (AAD) newly identified as potent partial farnesoid X receptor (FXR) agonists. Initially, both two and three-dimensional quantitative structure activity relationship (2D- and 3D-QSAR) studies were performed based on such AAD ...