Evidence map›Paper›PMID 40121339›Full record

ArticleCommunications chemistry2025

A quantitative analysis of ligand binding at the protein-lipid bilayer interface.

Allison Pearl Barkdull, Matthew Holcomb, Stefano Forli

Abstract read
In one paragraph

Article in Communications chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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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

3 authors.

Allison Pearl BarkdullDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.ORCID http://orcid.org/0000-0001-6813-7191
Matthew HolcombDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-8409-4344
Stefano ForliDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA. forli@scripps.edu.ORCID http://orcid.org/0000-0002-5964-7111

Funding

AutoDock Suite: Next Generation Environment for Drug DesignR01GM069832 · NIGMS · SCRIPPS RESEARCH INSTITUTE, THE · PI FORLI, STEFANO · 2004 to 2025
$10.9M
NIGMS NIH HHS R01 GM069832U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R01GM069832
6 · The paper itself

Abstract

The majority of drugs target membrane proteins, and many of these proteins contain ligand binding sites embedded within the lipid bilayer. However, targeting these therapeutically relevant sites is hindered by limited characterization of both the sites and the molecules that bind to them. Here, we introduce the Lipid-Interacting LigAnd Complexes Database (LILAC-DB), a curated dataset of 413 structures of ligands bound at the protein-bilayer interface. Analysis of these structures reveals that ligands binding to lipid-exposed sites exhibit distinct chemical properties, such as higher calculated partition coefficient (clogP), molecular weight, and a greater number of halogen atoms, compared to ligands that bind to soluble proteins. Additionally, we demonstrate that the atomic properties of these ligands vary significantly depending on their depth within and exposure to the lipid bilayer. We also find that ligand binding sites exposed to the bilayer have distinct amino acid compositions compared to other protein regions, which may aid in the identification of lipid-exposed binding sites. This analysis provides valuable guidelines for researchers pursuing structure-based drug discovery targeting underexploited ligand binding sites at the protein-lipid bilayer interface.

Identifiers

PMID40121339
PMCPMC11929912

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.