A Combination of Receptor-Based Pharmacophore Modeling & QM Techniques for Identification of Human Chymase Inhibitors

Inhibition of chymase is likely to divulge therapeutic ways for the treatment of cardiovascular diseases, and fibrotic disorders. To find novel and potent chymase inhibitors and to provide a new idea for drug design, we used both ligand-based and structure-based methods to perform the virtual screening(VS) of commercially available databases. Different pharmacophore models generated from various crystal structures of enzyme may depict diverse inhibitor binding modes. Therefore, multiple pharmacophore-based approach is applied in this study. X-ray crystallographic data of chymase in complex with different inhibitors were used to generate four structure–based pharmacophore models. One ligand–based pharmacophore model was also developed from experimentally known inhibitors. After successful validation, all pharmacophore models were employed in database screening to retrieve hits with novel chemical scaffolds. Drug-like hit compounds were subjected to molecular docking using GOLD and AutoDock. Finally four structurally diverse compounds with high GOLD score and binding affinity for several crystal structures of chymase were selected as final hits. Identification of final hits by three different pharmacophore models necessitates the use of multiple pharmacophore-based approach in VS process. Quantum mechanical calculation is also conducted for analysis of electrostatic characteristics of compounds which illustrates their significant role in driving the inhibitor to adopt a suitable bioactive conformation oriented in the active site of enzyme. In general, this study is used as example to illustrate how multiple pharmacophore approach can be useful in identifying structurally diverse hits which may bind to all possible bioactive conformations available in the active site of enzyme. The strategy used in the current study could be appropriate to design drugs for other enzymes as well

Prevalence of inappropriate medication using Beers criteria in Japanese long-term care facilities

BACKGROUND: The prevalence and risk factors of potentially inappropriate medication use among the elderly patients have been studied in various countries, but because of the difficulty of obtaining data on patient characteristics and medications they have not been studied in Japan. METHODS: We conducted a retrospective cross-sectional study in 17 Japanese long-term care (LTC) facilities by collecting data from the comprehensive MDS assessment forms for 1669 patients aged 65 years and over who were assessed between January and July of 2002. Potentially inappropriate medications were identified on the basis of the 2003 Beers criteria. RESULTS: The patients in the sample were similar in terms of demographic characteristics to those in the national survey. Our study revealed that 356 (21.1%) of the patients were treated with potentially inappropriate medication independent of disease or condition. The most commonly inappropriately prescribed medication was ticlopidine, which had been prescribed for 107 patients (6.3%). There were 300 (18.0%) patients treated with at least 1 inappropriate medication dependent on the disease or condition. The highest prevalence of inappropriate medication use dependent on the disease or condition was found in patients with chronic constipation. Multiple logistic regression analysis revealed psychotropic drug use (OR = 1.511), medication cost of per day (OR = 1.173), number of medications (OR = 1.140), and age (OR = 0.981) as factors related to inappropriate medication use independent of disease or condition. Neither patient characteristics nor facility characteristics emerged as predictors of inappropriate prescription. CONCLUSION: The prevalence and predictors of inappropriate medication use in Japanese LTC facilities were similar to those in other countries

Complex associations between cross‐kingdom microbial endophytes and host genotype in ash dieback disease dynamics

Tree pathogens are a major threat to forest ecosystems. Conservation management strategies can exploit natural mechanisms of resistance, such as tree genotype and host‐associated microbial communities. However, fungal and bacterial communities are rarely looked at in the same framework, particularly in conjunction with host genotype. Here, we explore these relationships and their influence on ash dieback disease, caused by the pathogen Hymenoscyphus fraxineus, in European common ash trees. We collected leaves from UK ash trees and used microsatellite markers to genotype trees, qPCR to quantify H. fraxineus infection load, and ITS and 16S rRNA amplicon sequencing to identify fungal and bacterial communities, respectively. There was a significant association between H. fraxineus infection intensity and ash leaf fungal and bacterial community composition. Higher infection levels were positively correlated with fungal community alpha diversity, and a number of fungal and bacterial genera were significantly associated with infection presence and intensity. Under higher infection loads, leaf microbial networks were characterised by stronger associations between fewer members than those associated with lower infection levels. Together these results suggest that H. fraxineus disrupts stable endophyte communities after a particular infection threshold is reached, and may enable proliferation of opportunistic microbes. We identified three microbial genera associated with an absence of infection, potentially indicating an antagonistic relationship with H. fraxineus that could be utilised in the development of anti‐pathogen treatments. Host genotype did not directly affect infection, but did significantly affect leaf fungal community composition. Thus, host genotype could have the potential to indirectly affect disease susceptibility through genotype x microbiome interactions, and should be considered when selectively breeding trees. Synthesis. We show the diversity, composition and network structure of ash leaf microbial communities are associated with the severity of infection from ash dieback disease, with evidence of disease‐induced dysbiosis. We also show that host genotype influences leaf fungal community composition, but does not directly influence tree infection. These findings help to elucidate relationships between host genetics, the microbiome, and a tree pathogen, highlighting potential resistance mechanisms and possible co‐infection concerns that could inform ash tree manage ment