2D and 3D-QSAR/CoMSIA Comparative Study On a Series of Thiazole Derivatives as SDHI Inhibitors

A database includes compounds based on thiazole derivatives having values of Succinate dehydrogenase inhibitors against S. sclerotiorum (ssSDH) pEC50 was used to develop a structure-activity relationship using 2D and 3D-QSAR methods. The data set used was randomly distributed into 80% as a learning set and 20% to assess the external prediction of the selected models (test set). the reliability and the predictive power of the established models were examined by various methods of internal validation, external validation, and randomized Y test. To detect outliers, the applicability domain was used using the Williams plot.The 2D-QSAR results revealed that the best 2D-QSAR model was established using the multiple linear regression method (MLR) (giving R²= 0.80 and Q²= 0.63), and the partial least squares regression method (PLS) (giving R² = 0.78 and Q² = 0.64), with four descriptors: J, Log P, NRB and MD. These models have successfully passed all external and internal validation criteria.The 3D-QSAR results show that the best model selected using the molecular field analysis method (CoMSIA), giving R² = 0.957, Q² = 0.614, and R²test = 0.80. The analysis of the CoMSIA contour maps shows the nature and the position of certain structural indicators important for the improvement of the studied biological activity such as the steric and electrostatic and hydrophobic substituents, as well as the substitutes of hydrogen bonds donors. These results will also be useful for the development of new thiazole derivatives with very high pEC50 values

Antioxidant activity and chemical analysis of Mentha spicata cultivated from west northern region of Algeria by headspace solid phase micro-extraction and hydro-distillation

International audienceThe essential oil of a Mentha spicata L. (collected fromAlgeria) was extracted by hydrodistillation and solid phasemicro-extraction (SPME). The oils have been studied by GC and GC-MS. Thirty seven compounds identified in the aerial parts oil extracted by hydrodistillation, the principal components being carvone (48.42%), eucalyptol (17.6%) and neoisodehydrocarveol acetate (11.7%). On the other hand, the oil extracted by SPME showed eucalyptol (55.1%) as the principal componentwithmoderate amounts of carvone (7.2%), (Z)-dehydro-carvone (4.3%), cis-carveol (3.9%) and carvacrol (3.0%). In addition, it should be noted that 11 compounds identified only in the volatile fractions extracted using HS-SPME and not indentified in essential oils. Isolated essential oil was tested for radical-scavenging ability using the stable DPPH radical assay, which showed concentration-dependant antiradical activities, i.e. a percent of inhibition of 52.21%in the presence of 12.6 mg/mL

Structure-odor relationship in pyrazines and derivatives: A physicochemical study using 3D-QSPR, HQSPR, Monte Carlo, molecular docking, ADME-Tox and molecular dynamics

In this study, using both 2D-QSPR and 3D-QSPR approaches, to understand the structure-odor relationship of 78 1–4-pyrazine odorant molecules and to use this knowledge for the design of new food and flavor products. According to our results, the developed models have good predictability such as the HQSPR/BC model with QLOO2=0.832, R2 = 0.916, CoMSIA/SEH model with Q2 = 0.624, Rcv2 = 0.590, Rncv2 = 0.932, Rbs2 = 0.963, and Topomer CoMFA model withRtraining2 = 0.899, Rtest2 = 0.916. The Monte Carlo method was used in the creation of a Quantitative Structure-Property Relationship (QSPR) model. The molecular structure is represented using optimized Simplified Molecular Input Line Entry System (SMILES) and molecular descriptors. The performance of the model is evaluated using the Correlation Ideality Index (IIC) and the Correlation Contradiction Index (CCI). The best model, designated as TF2, boasts excellent statistical properties with a training R-squared value of 0.957 and a test R-squared value of 0.834. The model was then used to determine promoter activity levels, which formed the basis for the design of 36 new odorant molecules. Molecular docking and pharmacokinetic properties were used to explain the mode of binding between the proposed compounds and the active site of the Porcine Odorant Binding Protein complexed with pyrazine (2-isobutyl-3-methoxypyrazine). Molecular dynamic simulation was used to assess and justify the stability of the ligand in the active site of the receptor. The results of this study provide a basis for the discovery of new compounds with lower olfactory thresholds and diverse pharmacological properties