Evidence map›Paper›PMID 41055983›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Design principles of the common Gly-X6-Gly membrane protein building block.

Kiana Golden, Catalina Avarvarei, Charlie T Anderson, Matthew Holcomb, Weiyi Tang, Xiaoping Dai, Minghao Zhang, Colleen A Mailie, Brittany B Sanchez, Jason S Chen and 2 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. bioRxiv : the preprint server for biology · 2026
    Article
  2. Design principles of the common Gly-X6-Gly membrane protein building block.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Kiana GoldenDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.ORCID 0009-0006-2377-8861
Catalina AvarvareiDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.ORCID 0009-0009-2742-6304
Charlie T AndersonDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.ORCID 0009-0009-3059-937X
Matthew HolcombDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.
Weiyi TangDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.
Xiaoping DaiDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.ORCID 0000-0003-1734-0717
Minghao ZhangDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.
Colleen A MailieDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.
Brittany B SanchezDepartment of Chemistry, The Scripps Research Institute, La Jolla, CA 92037.
Jason S ChenDepartment of Chemistry, The Scripps Research Institute, La Jolla, CA 92037.
Stefano ForliDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.ORCID 0000-0002-5964-7111
Marco MravicDepartment of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037.ORCID 0000-0001-6294-1824

Funding

AutoDock Suite: Next Generation Environment for Drug DesignR01GM069832 · NIGMS · SCRIPPS RESEARCH INSTITUTE, THE · PI FORLI, STEFANO · 2004 to 2025
$10.9M
Achievement Rewards for College Scientists Foundation (ARCS) 2023-2024 SCHOLARSHHS | National Institutes of Health (NIH) R01GM069832NIGMS NIH HHS R01 GM069832U.S. Department of Energy (DOE) DE-AC02-76SF00515
6 · The paper itself

Abstract

Protein behavior in lipids is poorly understood and inadequately represented in current computational models. Design and prediction abilities for bilayer-embedded molecular structures may be improved by characterizing membrane proteins' most frequent, favored structural features to glean both context-specific and general principles. We used protein design to proactively interrogate the sequence-structure relationship and stabilizing atomic details of two highly prevalent antiparallel transmembrane (TM) motifs with Small-X

Indexed as

GlycineMembrane ProteinsProtein EngineeringAmino Acid MotifsAmino Acid SequenceCrystallography, X-RayLipid BilayersModels, MolecularProtein ConformationGlycineLipid BilayersMembrane Proteinsbioinformaticslipid bilayersmembrane proteinprotein designprotein folding

Identifiers

PMID41055983
PMCPMC12541321

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.