Hydroxyzine Pamoate

Retention of molecules on immobilized artificial membrane (IAM) chromatography is a key physicochemical property for predictive models of permeability across biological barriers, with applications in drug design and ecotoxicology. Currently, IAM retention is solely experimentally determined, which limits its utility for screening virtual compound libraries or for predictions of yet not synthesized molecules. The present study focuses on developing predictive models of IAM retention factors (logk_w(IAM)) for a structurally diverse set of drug compounds, scrutinizing the role of lipophilicity, experimental and calculated, as well as the contribution of additional molecular parameters, selected from a pool of physicochemical, constitutional, topological and 3D descriptors. After obtaining a data overview by principal component analysis, both multiple linear regression (MLR) and partial least squares (PLS) analyses were used to construct lipophilicity-based models and lipophilicity-independent models. Bulk, polarity and fraction of anionic species were common descriptors in all models. It was demonstrated that calculated lipophilicity values introduced additional uncertainty, depending on the software used. On the other hand, lipophilicity-independent MLR and PLS models, which relied solely on computational descriptors, showed comparable performance with lipophilicity-based models, while offering the advantage to more useful for screening large libraries in early drug discovery. The reliability of lipophilicity-independent MLR and PLS models was assessed by external validation as well as by using a blind test set. Error distribution between lipophilicity-based and lipophilicity-independent models was also investigated and found to be comparable, while it was better than the differences between experimental and calculated lipophilicity values.

Besides aroma, the tastes of Pixian Broad Bean Paste (PBBP) are also important, however, they have not yet been thoroughly elucidated. Therefore, this study employed sensory and untargeted metabolomics approaches to investigate taste characteristics, molecular basis and their metabolic pathways of PBBP from three different manufacturers and two grades. Results showed PBBP was predominantly characterized by strong sour, umami and salty tastes, and significant differences were observed in samples from different manufacturers and grades (p < 0.05), especially higher sourness, saltiness and umami in premium PBBP. Based on non-volatiles, 55 key differential metabolites were identified through orthogonal partial least square discriminant analysis (OPLS-DA, P value<0.05, VIP value>1.0) and Pearson correlation analysis (|ρ| > 0.7). These key differential metabolites responsible for taste differences were metabolized by 36 crucial KEGG pathways (P value<0.05, impact value>0.05). These results could expand our understandings of PBBP taste compounds and their metabolisms, and provide theoretical evidences for further quality improvement.