3D-QSAR studies on 1,2,4-triazolyl 5-azaspiro [2.4]-heptanes as D 3 R antagonists

Comparison of various methods for validity evaluation of QSAR models

BACKGROUND

Quantitative structure-activity relationship (QSAR) modeling is one of the most important computational tools employed in drug discovery and development. The external validation of QSAR models is the main point to check the reliability of developed models for the prediction activity of not yet synthesized compounds. It was performed by different criteria in the literature.

METHODS

In this study, 44 reported QSAR models for biologically active compounds reported in scientific papers were collected. Various statistical parameters of external validation of a QSAR model were calculated, and the results were discussed.

RESULTS

The findings revealed that employing the coefficient of determination (r²) alone could not indicate the validity of a QSAR model. The established criteria for external validation have some advantages and disadvantages which should be considered in QSAR studies.

CONCLUSION

This study showed that these methods alone are not only enough to indicate the validity/invalidity of a QSAR model.

Integration of Fuzzy Matter-Element Method and 3D-QSAR Model for Generation of Environmentally Friendly Quinolone Derivatives

The environmental pollution of quinolone antibiotics (QAs) has caused rising public concern due to their widespread usage. In this study, Gaussian 09 software was used to obtain the infrared spectral intensity (IRI) and ultraviolet spectral intensity (UVI) of 24 QAs based on the Density Functional Theory (DFT). Rather than using two single-factor inputs, a fuzzy matter-element method was selected to calculate the combined effects of infrared and ultraviolet spectra (CI). The Comparative Molecular Field Analysis (CoMFA) was then used to construct a three-dimensional quantitative structure–activity relationship (3D-QSAR) with QAs’ molecular structure as the independent variable and CI as the dependent variable. Using marbofloxacin and levofloxacin as target molecules, the molecular design of 87 QA derivatives was carried out. The developed models were further used to determine the stability, functionality (genetic toxicity), and the environmental effects (bioaccumulation, biodegradability) of these designed QA derivatives. Results indicated that all QA derivatives are stable in the environment with their IRI, UVI, and CI enhanced. Meanwhile, the genetic toxicity of the 87 QA derivatives increased by varying degrees (0.24%–29.01%), among which the bioaccumulation and biodegradability of 43 QA derivatives were within the acceptable range. Through integration of fuzzy matter-element method and 3D-QSAR, this study advanced the QAs research with the enhanced CI and helped to generate the proposed environmentally friendly quinolone derivatives so as to aid the management of this class of antibiotics.

Dibenzepinones, dibenzoxepines and benzosuberones based p38α MAP kinase inhibitors: Their pharmacophore modelling, 3D-QSAR and docking studies

In the present study, a series of dibenzepinones, dibenzoxepines, and benzosuberones targeting p38α MAP kinase were subjected to pharmacophore modelling, 3D-QSAR and molecular docking studies. The IC₅₀ values for these 67 compounds ranged between 0.003 and 6.80 μM. A five-point model (DDHHR.8) was generated using these compounds. This model was found to be statistically significant and was found to have high correlation (R² = 0.98), cross-validation coefficient (Q² = 0.95) and F (330) values at six component PLS factor. Tests were performed to ascertain the efficacy of the generated model. These tests included external validation, Tropsha's test for predictive ability, Y-randomisation test and domain of applicability (APD). In order to check the restrictivity of the model, enrichment studies were performed with inactive compounds by using decoy set molecules. To evaluate the effectiveness of the docking protocol, the co-crystallised ligand was extracted from the ligand-binding domain of the protein and was re-docked into the same position. Both the conformers were then superimposed, suggesting satisfactory docking parameters with an RMSD value of less than 1.0 Å (0.853 Å). A 10 ns molecular dynamics simulation confirmed the docking results of the 3UVP-ligand complex and the presumed active conformation. The outcome of the present study provides insight into the molecular features that promote bioactivity and can be exploited for the prediction of novel potent p38α MAP kinase inhibitors before carrying out their synthesis and anticancer evaluation.