Development of QSAR model based on Monte Carlo optimization for predicting GABAA receptor binding of newly emerging benzodiazepines.

Benzodiazepines and their derivatives belong to a category of new psychoactive substances that have been introduced into the continually expanding illicit market. However, there is a notable absence of available pharmacological data for these substances. To gain a deeper understanding of their pharmacology, we employed the Monte Carlo optimization conformation-independent method as a tool for developing QSAR models. These models were built using optimal molecular descriptors derived from both SMILES notation and molecular graph representations. The resulting QSAR model demonstrated robustness and a high degree of predictability, proving to be very reliable. Moreover, we were able to identify specific molecular fragments that exerted both positive and negative effects on binding activity. This discovery paves the way for the swift prediction of binding activity for emerging benzodiazepines, offering a faster and more cost-effective alternative to traditional in vitro/in vivo analyses.

Assessment of hemostatic disturbances in women with established rheumatoid arthritis.

OBJECTIVES: This study was aimed to assess hemostatic disturbances in female patients with established rheumatoid arthritis (RA) in relation to menopausal status and disease activity. METHOD: Ninety women were included in the study, 42 patients and 48 age-matched healthy controls. There were no differences between the investigated groups regarding the presence of traditional cardiovascular risk factors. Two global hemostatic assays were employed, namely endogenous thrombin potential (ETP) and overall hemostasis potential (OHP). The parameters of the ETP assay (ETP, C-max, t-lag, t-max) and OHP assay (overall coagulation potential (OCP) and overall fibrinolytic potential (OFP)) were assessed. Moreover, the parameters of the fibrin clot (lag time, Max Abs, and slope) were measured by clot turbidity and scanning electron microscopy (SEM). Both patients and controls were divided into four subgroups according to menopause status. RESULTS: The premenopausal controls differed significantly from all other subgroups in terms of diminished levels of ETP (p = 0.02), C-max (p = 0.01), OCP (p = 0.02), OHP (p = 0.001), and Max Abs (p = 0.008), while OFP (p = 0.0001) was increased. This tendency was not seen in the premenopausal RA patients compared with the postmenopausal RA patients. SEM images showed denser clots composed of thinner fibers in samples from RA patients. The disease activity measured by DAS28 correlated with OCP and OHP (r = 0.54; p = 0.001 and r = 0.44; p = 0.003, respectively) indicating persistent hypercoagulable condition in the whole group of RA patients. CONCLUSIONS: Our results point towards coagulation activation in premenopausal women with established RA. The patients were well characterized, which enabled assessment in a real-life setting. Key Points • Extensive assessment points towards persistent coagulation activation in premenopausal women with established rheumatoid arthritis. • Impaired thrombin generation and fibrin formation are associated with menopause in healthy women, while rheumatoid arthritis closes the gap within patients regarding menopause. • Fibrin morphology is unfavorably altered and fibrinolysis is decreased in patients with established rheumatoid arthritis. • Increased activity of thrombin activatable fibrinolysis inhibitor (TAFI) may contribute to impaired fibrinolysis in patients with rheumatoid arthritis.

QSPR in forensic analysis - The prediction of retention time of pesticide residues based on the Monte Carlo method.

A method for the prediction of retention indices of pesticides using the Monte Carlo method and with optimal molecular descriptors based on local graph invariants and the SMILES notation of studied compounds has been presented. Quite satisfactory results were obtained with the proposed method, since a robust model with good statistical quality was developed. The predictive potential of the applied approach was tested and the robustness of the model was proven with different methods. The best calculated QSPR model had following statistical parameters: r2 = 0.9182 for the training set and r2 = 0.8939 for the test set. Structural indicators defined as molecular fragments responsible for the increases and decreases of gas chromatographic retention indices activity were calculated.