Evidence map›Paper›PMID 39966220›Full record

ArticlePharmaceutical research2025

Structure Bioinformatics of Six Human Integral Transmembrane Enzymes and their AlphaFold3 Predicted Water-Soluble QTY Analogs: Insights into FACE1 and STEA4 Binding Mechanisms.

Edward Chen, Emily Pan, Shuguang Zhang

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Article in Pharmaceutical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Edward ChenCarnegie Mellon University, Pittsburgh, PA, USA.ORCID http://orcid.org/0009-0002-1734-5702
Emily PanMassachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.
Shuguang ZhangMedia Lab, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. Shuguang@mit.edu.ORCID http://orcid.org/0000-0002-3856-3752

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveHuman integral membrane enzymes are essential for catalyzing a wide range of biochemical reactions and regulating key cellular processes. However, studying these enzymes remains challenging due to their hydrophobic nature, which necessitates the use of detergents. This study explores whether applying the QTY code can reduce the hydrophobicity of these enzymes while preserving their structures and functions, thus facilitating bioinformatics analysis of six key integral membrane enzymes: MGST2, LTC4S, PTGES, FACE1, STEA4, and SCD.

methodsThe water-soluble QTY analogs of the six membrane enzymes were predicted using AlphaFold3. The predicted structures were superposed with CyroEM determined native structures in PyMOL to observe changes in structure and protein-ligand binding ability.

resultsThe native membrane enzymes superposed well with their respective QTY analogs, with the root mean square deviation (RMSD) ranging from 0.273 Å to 0.875 Å. Surface hydrophobic patches on the QTY analogs were significantly reduced. Importantly, the protein-ligand interactions in FACE1 and STEA4 were largely preserved, indicating maintained functionality.

conclusionOur structural bioinformatics studies using the QTY code and AlphaFold3 not only provide the opportunities of designing more water-soluble integral membrane enzymes, but also use these water-soluble QTY analogs as antigens for therapeutic monoclonal antibody discovery to specifically target the key integral membrane enzymes.

Indexed as

Computational BiologyMembrane ProteinsBinding SitesHumansHydrophobic and Hydrophilic InteractionsLigandsProtein BindingProtein ConformationSolubilityWaterLigandsMembrane ProteinsWaterbioinformaticsbiophysics proteinscomputational biophysicsmembrane protein structureprotein dynamics simulation

Identifiers

PMID39966220
PMCPMC11880043

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