Evidence map›Paper›PMID 37573260›Full record

ArticleJournal of computer-aided molecular design2023

A least-squares-fitting procedure for an efficient preclinical ranking of passive transport across the blood-brain barrier endothelium.

Christian Jorgensen, Evan P Troendle, Jakob P Ulmschneider, Peter C Searson, Martin B Ulmschneider

Abstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Permeability Benchmarking: Guidelines for ComparingJournal of chemical information and modeling · 2025
    Review
  7. Article
  8. Review
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Christian JorgensenInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA. Cjorgen4@jhu.edu.
Evan P TroendleDepartment of Chemistry, King's College, London, UK.
Jakob P UlmschneiderSchool of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, China.
Peter C SearsonInstitute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA.
Martin B UlmschneiderDepartment of Chemistry, King's College, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The treatment of various disorders of the central nervous system (CNS) is often impeded by the limited brain exposure of drugs, which is regulated by the human blood-brain barrier (BBB). The screening of lead compounds for CNS penetration is challenging due to the biochemical complexity of the BBB, while experimental determination of permeability is not feasible for all types of compounds. Here we present a novel method for rapid preclinical screening of libraries of compounds by utilizing advancements in computing hardware, with its foundation in transition-based counting of the flux. This method has been experimentally validated for in vitro permeabilities and provides atomic-level insights into transport mechanisms. Our approach only requires a single high-temperature simulation to rank a compound relative to a library, with a typical simulation time converging within 24 to 72 h. The method offers unbiased thermodynamic and kinetic information to interpret the passive transport of small-molecule drugs across the BBB.

Indexed as

Blood-Brain BarrierBiological TransportComputer SimulationEndotheliumHumansPermeabilityBlood–brain barrierBrain permeabilityCNS penetrationKineticsMolecular dynamicsTransport properties

Identifiers

PMID37573260
PMCPMC10505096

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.