pitavastatin + valsartan (Livalsartan / Livasartan)

Knowledge graph and machine learning-guided virtual screening prioritizes putative blockers of the PSMD11/Rpn6-EBOV glycoprotein interface.

Wang Yanshuang Y, Li Yuanjian Y, Zhu Lin L, Jiang Zhiguo Z et al.

Host-directed antiviral discovery requires a traceable route from host-factor identification to testable molecular hypotheses. This study developed such a workflow around a host factor associated with Ebola virus glycoprotein (EBOV GP). GFP-GP pulldown coupled with co-immunoprecipitation/mass spectrometry was used to identify GP-associated host candidates. A PSMD11/Rpn6-centred workflow integrated knowledge-graph inference, ligand-only machine learning, ADMETlab profiling and interface-guided docking. Candidate prioritization was assessed through score-weight sensitivity analysis, applicability-domain assessment and docking controls addressing seed reproducibility, search convergence, whole-receptor context and macrocycle ring-conformer sensitivity. Docking scores were contextualized against a matched 59-compound library. The analysis recovered 424 GP-pulldown-specific host proteins and nominated PSMD11/Rpn6 as a proteostasis anchor. The tier-gated knowledge-graph candidate membership was invariant across the tested weight perturbations, with Spearman rho = 0.998 under equal weighting. The selected ExtraTrees model achieved an AUC of 0.912 for the Ki endpoint. Applicability-domain assessment and ADMET profiling differentiated candidate confidence and predicted liabilities. Docking reproducibility checks yielded a maximum standard deviation of 0.05 kcal/mol for conformationally restricted ligands, while macrocyclic candidates showed greater protocol-dependent variability. Rule-based triage integrating upstream evidence, ADMET burden, chemotype diversity and mechanistic coverage returned five candidates: betamethasone, bafilomycin A1, everolimus, pitavastatin and CHEMBL1410015. The workflow links a proteomic host-factor signal to a compact set of chemically diverse hypotheses with explicit evidence sources and limitations. The candidates remain hypotheses for experimental assessment; direct target engagement, interface blockade and antiviral activity are not established by the present study.

Molecular Toxicological Mechanisms of Pharmaceutical Nitrosamines: DNA Damage, Metabolic Activation, Carcinogenesis, and Advanced Analytical Detection Strategies.

Karale Pradip P, Chabukswar Vishal V, Avachar Ishvari I, Chaudhari Nilesh N et al.

In light of the valsartan recalls in 2018, nitrosamine impurities have become some of the most important pharmaceutical quality concerns to be seen in recent years, as NDMA and other nitrosamines have been discovered in angiotensin receptor blockers, metformin, ranitidine, and many other medicines. Nitrosamine impurities fall under the IARC classification of probable human carcinogens (Group 2A), and although present in very small amounts, these have prompted stricter standards for their presence, as set by the FDA, EMA, MHRA, PMDA, and Health Canada. The present review provides an overview of the current mechanistic knowledge within four interrelated areas. The first aspect to be discussed is that of the chemistry of nitrosamine generation. Second, the mechanisms underlying the metabolic activation via cytochrome P450 are explained in detail with emphasis on the key role played by α-hydroxylation, isoform specificities (with CYP2E1 and CYP2A6 enzymes being the most important players) and the mechanistic fork leading to either toxication through dealkylation or detoxification through denitrosation and hence determining the genotoxicity potential of the chemical. Third, the DNA adduct formation and mutagenicity associated with the nitrosamine compound is connected to the structure-based risk assessment systems like the Carcinogenic Potency Categorization Approach (CPCA). Fourth, analytical detection methods such as high resolution mass spectrometry, which can operate with sub-part per billion sensitivity levels, and computational prediction techniques are discussed as indispensable supplements to the mechanism-based risk assessment.

Obesity and Change in NT-proBNP with Angiotensin-Neprilysin Inhibition in Patients with Mildly Reduced or Preserved Ejection Fraction and a Worsening Heart Failure Event: PARAGLIDE-HF.

Harrington Josephine J, Sharma Kavita S KS, Erickson Tyler T, Adams Kirkwood F KF et al.

To determine the relationship between obesity status and the effect of sacubitril/valsartan (sac/val) vs valsartan (val) on change in NT-proBNP and a hierarchical outcome of clinical benefit among patients with heart failure with mildly reduced or preserved ejection fraction (HFpEF). In the PARAGLIDE-HF trial, patients with HFpEF and a recent worsening HF event randomized to sac/val vs. val had a greater decrease in NT-proBNP over 8 weeks and showed a trend towards clinical benefit. Patients with HFpEF and obesity represent a unique population with high symptom burden and elevated risk for HF hospitalization. The efficacy and safety of sac/val in this high-risk population following a recent worsening HF event is not well characterized. To assess the interaction between obesity status and sac/val vs val on NT-proBNP, the time-averaged proportional change in NT-proBNP from baseline to Weeks 4 and 8 was assessed with an analysis of covariance model that included the interaction of treatment-by-BMI group (obese with BMI ≥30 kg/m2 vs not obese with BMI 18.5 to <30 kg/m2). A win ratio consisting of a hierarchy of cardiovascular death, total HF hospitalizations, urgent HF visits, and change in NT-proBNP was calculated for both BMI groups. Overall, 65% (n=298) of participants had obesity and 35% (n=164) of participants did not have obesity. When the interaction between BMI category and the effect of sac/val vs val on the time-averaged proportional change from baseline NT-proBNP was assessed, participants with obesity had a numerically larger decrease in NT-proBNP (ratio of change 0.82 (95% CI 0.68 to 0.99) with obesity vs 0.96 (95% CI 0.71 to 1.29) without obesity that was not statistically significant, p interaction 0.37. Participants with obesity were significantly more likely to derive benefit overall from sac/val vs val as compared to participants without obesity (win ratio 1.38, 95% CI 1.01-1.90 vs 0.90, 95% CI 0.62-1.32, p-interaction = 0.09). In this prespecified secondary analysis of PARAGLIDE-HF, patients with HFpEF and obesity had a similar magnitude of decrease in NT-proBNP with randomization to sac/val vs val, but may derive greater clinical benefit as assessed by a win ratio. This hypothesis-generating evidence suggests that patients that patients with obesity and HFpEF may particularly benefit from sac/val.

Correction to: Sacubitril/valsartan compared to equivalent/sub-equivalent dose angiotensin receptor blocker or angiotensin-converting enzyme inhibitor in heart failure with reduced ejection fraction: a meta-analysis of randomized trials.

Rindone Joseph P JP, Mellen Chadwick K CK