ArticlePharmaceutical research2017
Drug Distribution. Part 1. Models to Predict Membrane Partitioning.
Article in Pharmaceutical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- An integrated computational strategy for profiling terpenoid for dual-target leads against Klebsiella pneumoniae penicillin-binding protein 3 and beta-lactamase.Molecular diversity · 2026Article
- Mechanistic studies on pH-permeability relationships: Impact of the membrane polar headgroup region on pKa.International journal of pharmaceutics · 2025Article
- Data set of fraction unbound values in the in vitro incubations for metabolic studies for better prediction of human clearance.Database : the journal of biological databases and curation · 2024Article
- Relative Performance of Volume of Distribution Prediction Methods for Lipophilic Drugs with Uncertainty in LogP Value.Pharmaceutical research · 2024Article
- A permeability- and perfusion-based PBPK model for improved prediction of concentration-time profiles.Clinical and translational science · 2022Article
- Predicting Impact of Food and Feeding Time on Oral Absorption of Drugs with a Novel Rat Continuous Intestinal Absorption Model.Drug metabolism and disposition: the biological fate of chemicals · 2022Article
- Mechanisms of Herb-Drug Interactions Involving Cinnamon and CYP2A6: Focus on Time-Dependent Inhibition by Cinnamaldehyde and 2-Methoxycinnamaldehyde.Drug metabolism and disposition: the biological fate of chemicals · 2020Article
- Prediction of Tissue-Plasma Partition Coefficients Using Microsomal Partitioning: Incorporation into Physiologically based Pharmacokinetic Models and Steady-State Volume of Distribution Predictions.Drug metabolism and disposition: the biological fate of chemicals · 2019Article
- Heterogeneous drug tissue binding in brain regions of rats, Alzheimer's patients and controls: impact on translational drug development.Scientific reports · 2019Article
- Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A.Molecular pharmaceutics · 2018Article
- Evaluation and calibration of high-throughput predictions of chemical distribution to tissues.Journal of pharmacokinetics and pharmacodynamics · 2017Article
- Continuous Intestinal Absorption Model Based on the Convection-Diffusion Equation.Molecular pharmaceutics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
purposeTissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution.
methodsTwo structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs.
resultsThe resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs).
conclusionsTogether these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.