Effect of changes in metabolic enzymes and transporters on drug metabolism in the context of liver disease: Impact on pharmacokinetics and drug-drug interactions

An in-silico approach to target multiple proteins involved in anti-microbial resistance using natural compounds produced by wild mushrooms

Bacterial resistance to antibiotics and the number of patients infected by multi-drug-resistant bacteria have increased significantly over the past decade. This study follows a computational approach to identify potential antibacterial compounds from wild mushrooms. Twenty-six known compounds produced by wild mushrooms were docked to assess their affinity with drug targets of antibiotics such as penicillin-binding protein-1a (PBP1a), DNA gyrase, and isoleucyl-tRNA synthetase (ILERS). Docking scores were further validated by multiple receptor conformer (MRC)-based docking studies. Based on the MRC-based docking results, eight molecules were shortlisted for ADMET analysis. Molecular dynamics (MD) simulations were further performed to evaluate the conformational stability of the ligand-protein complexes. Binding energies were computed by the gmx_MMPBSA method. The data were obtained in terms of root-mean square deviation, and root-mean square fluctuation justified the stability of Austrocortilutein A, Austrocortirubin, and Confluentin in complex with several proteins under physiological conditions. Among these, Austrocortilutein A displayed better binding affinity with PBP1a and ILERS when compared with their respective reference ligands. This study is preliminary and aims to help drive the search for compounds that have the capacity to overcome the anti-microbial resistance of prevalent bacteria, using natural compounds produced by wild mushrooms. Further experimental validation is required to justify the clinical use of the studied compounds.

Beyond CL and VSS: A comprehensive approach to human pharmacokinetic predictions

This article presents a comprehensive examination of processes related to the prediction of human pharmacokinetics (PK), a crucial task of clinical drug candidate selection. By systematically incorporating in vitro absorption, distribution, metabolism and excretion (ADME) and in vivo PK data with expert judgement, the study achieves high-quality human PK predictions for 40 orally administered compounds from Boehringer Ingelheim's new chemical entity (NCE) portfolio. Overall, the article provides a detailed evaluation of and guidance for a structured process to predict full concentration-time profiles beyond single-parameter predictions, using state-of-the-art methodologies. Furthermore, it discusses future challenges and improvements, and aims to provide valuable insights for scientists working in drug metabolism and PK (DMPK) or PK/pharmacodynamics (PK/PD) modelling.

Physiologically Based Pharmacokinetic Modeling to Predict the Impact of Liver Cirrhosis on Glucuronidation via UGT1A4 and UGT2B7/2B4-A Case Study with Midazolam

Hepatic impairment, due to liver cirrhosis, decreases the activity of cytochrome P450 enzymes (CYPs). The use of physiologically based pharmacokinetic (PBPK) modeling to predict this effect for CYP substrates has been well-established, but the effect of cirrhosis on uridine-glucuronosyltransferase (UGT) activities is less studied and few PBPK models have been reported. UGT enzymes are involved in primary N-glucuronidation of midazolam and glucuronidation of 1'-OH-midazolam following CYP3A hydroxylation. In this study, Simcyp was used to establish PBPK models for midazolam, its primary metabolites midazolam-N-glucuronide (UGT1A4) and 1'-OH midazolam (CYP3A4/3A5), and the secondary metabolite 1'-OH-midazolam-O-glucuronide (UGT2B7/2B4), allowing to simulate the impact of liver cirrhosis on the primary and secondary glucuronidation of midazolam. The model was verified in noncirrhotic subjects before extrapolation to cirrhotic patients of Child-Pugh (CP) classes A, B, and C. Our model successfully predicted the exposures of midazolam and its metabolites in noncirrhotic and cirrhotic patients, with 86% of observed plasma concentrations within 5th-95th percentiles of predictions and observed geometrical mean of area under the plasma concentration curve between 0 hours to infinity and maximal plasma concentration within 0.7- to 1.43-fold of predictions. The simulated metabolic ratio defined as the ratio of the glucuronide metabolite AUC over the parent compound AUC (AUCglucuronide/AUCparent, metabolic ratio [MR]), was calculated for midazolam-N-glucuronide to midazolam (indicative of UGT1A4 activity) and decreased by 40% (CP A), 48% (CP B), and 75% (CP C). For 1'-OH-midazolam-O-glucuronide to 1'-OH-midazolam, the MR (indicative of UGT2B7/2B4 activity) dropped by 35% (CP A), 51% (CP B), and 64% (CP C). These predicted MRs were corroborated by the observed data. This work thus increases confidence in Simcyp predictions of the effect of liver cirrhosis on the pharmacokinetics of UGT1A4 and UGT2B7/UGT2B4 substrates. SIGNIFICANCE STATEMENT: This article presents a physiologically based pharmacokinetic model for midazolam and its metabolites and verifies the accurate simulation of pharmacokinetic profiles when using the Simcyp hepatic impairment population models. Exposure changes of midazolam-N-glucuronide and 1'-OH-midazolam-O-glucuronide reflect the impact of decreases in UGT1A4 and UGT2B7/2B4 glucuronidation activity in cirrhotic patients. The approach used in this study may be extended to verify the modeling of other uridine glucuronosyltransferase enzymes affected by liver cirrhosis.