Coumarins and P450s, Studies Reported to-Date.

Cytochrome P450 enzymes (CYPs) are important phase I enzymes involved in the metabolism of endogenous and xenobiotic compounds mainly through mono-oxygenation reactions into more polar and easier to excrete species. In addition to their role in detoxification, they play important roles in the biosynthesis of endogenous compounds and the bioactivation of xenobiotics. Coumarins, phytochemicals abundant in food and commonly used in fragrances and cosmetics, have been shown to interact with P450 enzymes as substrates and/or inhibitors. In this review, these interactions and their significance in pharmacology and toxicology are discussed in detail.

Molecular Modeling Studies on Carbazole Carboxamide Based BTK Inhibitors Using Docking and Structure-Based 3D-QSAR.

Rheumatoid arthritis (RA) is the second common rheumatic immune disease with chronic, invasive inflammatory characteristics. Non-steroidal anti-inflammatory drugs (NSAIDs), slow-acting anti-rheumatic drugs (SAARDs), or glucocorticoid drugs can improve RA patients’ symptoms, but fail to cure. Broton’s tyrosine kinase (BTK) inhibitors have been proven to be an efficacious target against autoimmune indications and B-cell malignancies. Among the current 11 clinical drugs, only BMS-986142, classified as a carbazole derivative, is used for treating RA. To design novel and highly potent carbazole inhibitors, molecular docking and three dimensional quantitative structure⁻activity relationship (3D-QSAR) were applied to explore a dataset of 132 new carbazole carboxamide derivatives. The established comparative molecular field analysis (CoMFA) (q² = 0.761, r² = 0.933) and comparative molecular similarity indices analysis (CoMSIA) (q² = 0.891, r² = 0.988) models obtained high predictive and satisfactory values. CoMFA/CoMSIA contour maps demonstrated that bulky substitutions and hydrogen-bond donors were preferred at R1 and 1-position, respectively, and introducing hydrophilic substitutions at R1 and R4 was important for improving BTK inhibitory activities. These results will contribute to the design of novel and highly potent BTK inhibitors.

Antitumor evaluation and 3D-QSAR studies of a new series of the spiropyrroloquinoline isoindolinone/aza-isoindolinone derivatives by comparative molecular field analysis (CoMFA).

In current study, antitumor activity of two series of the newly synthesized spiropyrroloquinoline isoindolinone and spiropyrroloquinoline aza-isoindolinone scaffolds was evaluated against three human breast normal and cancer cell lines (MCF-10A, MCF-7 and SK-BR-3) and compared with cytotoxicity values of doxorubicin and colchicine as the standard drugs. It was found that several compounds were endowed with cytotoxicity in the low micromolar range. Among these two series, compounds 6i, 6j, 6k and 7l, 7m, 7n, 7o containing 3-ethyl-1H-indole moiety were found to be highly effective against both cancer cell lines ranging from [Formula: see text] to [Formula: see text] in comparison with the corresponding analogs. Compared with human cancer cells, the most potent compounds did not show high cytotoxicity against human breast normal MCF-10A cells. Generally, most of the evaluated compounds 6a-l and 7a-o series showed more antitumor activity against SK-BR-3 than MCF-7 cells. Moreover, comparative molecular field analysis (CoMFA) as a popular tools of three-dimensional quantitative structure-activity relationship (3D-QSAR) studies was carried out on 27 spiropyrroloquinolineisoindolinone and spiropyrroloquinolineaza-isoindolinone derivatives with antitumor activity against on SK-BR-3 cells. The obtained CoMFA models showed statistically excellent performance, which also possessed good predictive ability for an external test set. The results confirm the important effect of molecular steric and electrostatic interactions of these compounds on in vitro cytotoxicity against SK-BR-3.

3D-QSAR, molecular dynamics simulations, and molecular docking studies on pyridoaminotropanes and tetrahydroquinazoline as mTOR inhibitors.

Cancer is a second major disease after metabolic disorders where the number of cases of death is increasing gradually. Mammalian target of rapamycin (mTOR) is one of the most important targets for treatment of cancer, specifically for breast and lung cancer. In the present research work, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies were performed on 50 compounds reported as mTOR inhibitors. Three different alignment methods were used, and among them, distill method was found to be the best method. In CoMFA, leave-one-out cross-validated coefficients [Formula: see text], conventional coefficient [Formula: see text], and predicted correlation coefficient [Formula: see text] values were found to be 0.664, 0.992, and 0.652, respectively. CoMSIA study was performed in 25 different combinations of features, such as steric, electrostatic, hydrogen bond donor, hydrogen bond acceptor, and hydrophobic. From this, a combination of steric, electrostatic, hydrophobic (SEH), and a combination of steric, electrostatic, hydrophobic, donor, and acceptor (SEHDA) were found as best combinations. In CoMSIA (SEHDA), [Formula: see text], [Formula: see text] and [Formula: see text] were found to be 0.646, 0.977, and 0.682, respectively, while in the case of CoMSIA (SEH), the values were 0.739, 0.976, and 0.779, respectively. Contour maps were generated and validated by molecular dynamics simulation-assisted molecular docking study. Highest active compound 19, moderate active compound 15, and lowest active compound 42 were docked on mTOR protein to validate the results of our molecular docking study. The result of the molecular docking study of highest active compound 19 is in line with the outcomes generated by contour maps. Based on the features obtained through this study, six novel mTOR inhibitors were designed and docked. This study could be useful for designing novel molecules with increased anticancer activity.

[Three-dimensional quantitative structure-activity relationship study on gas chromatographic retention index of the fragrance compounds of Liliumspp].

Quantitative structure-activity relationship models on the gas chromatographic retention index of the 38 volatile fragrance compounds of Liliumspp were investigated and established by comparative molecular field analysis (CoMFA) and comparative molecular similarity index (CoMSIA) methods. The robustness and predictive performance of the developed models were assessed using external test set validation and leave-one-out cross validation. Further, the effects of the molecular structure on the gas chromatographic retention indices of these compounds were intuitively studied in light of the three-dimensional contour maps of molecular fields provided by the developed CoMSIA and CoMFA models. The validation results demonstrated that both the models could accurately predict the retention indices of the investigated components. The influence of the molecular structure on the retention indices could be reasonably explained by these models. Moreover, the prediction accuracy of the CoMSIA model was slightly higher than that of the CoMFA model. Obviously, the proposed CoMSIA model is more promising for the analysis of the volatile fragrance compounds of Lilium spp.

QSAR studies of bioconcentration factors of polychlorinated biphenyls (PCBs) using DFT, PCS and CoMFA.

The bioconcentration factors (BCFs) of 58 polychlorinated biphenyls (PCBs) were modeled by quantitative structure-activity relationship (QSAR) using density functional theory (DFT), the position of Cl substitution (PCS) and comparative molecular field analysis (CoMFA) methods. All the models were robust and predictive, and especially, the best CoMFA model was significant with a correlation coefficient (R(2)) of 0.926, a cross-validation correlation coefficient (Q(2)) of 0.821 and a root mean square error estimated (RMSE) of 0.235. The results indicate that the electrostatic descriptors play a more significant role in BCFs of PCBs. Additionally, a test set was used to compare the predictive ability of our models to others, and results show that our CoMFA model present the lowest RMSE. Thus, the models obtain in this work can be used to predict the BCFs of remaining 152 PCBs without available experimental values.