Evidence map›Paper›PMID 39810075›Full record

ArticleBMC bioinformatics2025

Development of a TSR-based method for understanding structural relationships of cofactors and local environments in photosystem I.

Lujun Luo, Tarikul I Milon, Elijah K Tandoh, Walter J Galdamez, Andrei Y Chistoserdov, Jianping Yu, Jan Kern, Yingchun Wang, Wu Xu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 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. Article
  2. 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

9 authors.

Lujun LuoDepartment of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
Tarikul I MilonDepartment of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
Elijah K TandohDepartment of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
Walter J GaldamezDepartment of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
Andrei Y ChistoserdovDepartment of Biology, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
Jianping YuBiosciences Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA.
Jan KernBioenergetics Department, MBIB Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Yingchun WangInstitute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
Wu XuDepartment of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA. wxx6941@louisiana.edu.

Funding

Development of a new TSR algorithm to represent sequences of proteins and 3D structures of nucleotides and molecular complexes for mechanistic understanding of protein sequence and structure relationsR15GM144944 · NIGMS · UNIVERSITY OF LOUISIANA AT LAFAYETTE · PI Wu Xu · 2021 to 2026
$963k
National Science Foundation 2313482NIGMS NIH HHS R15 GM144944NIH NIGMS 1R15GM144944-01
6 · The paper itself

Abstract

backgroundAll chemical forms of energy and oxygen on Earth are generated via photosynthesis where light energy is converted into redox energy by two photosystems (PS I and PS II). There is an increasing number of PS I 3D structures deposited in the Protein Data Bank (PDB). The Triangular Spatial Relationship (TSR)-based algorithm converts 3D structures into integers (TSR keys). A comprehensive study was conducted, by taking advantage of the PS I 3D structures and the TSR-based algorithm, to answer three questions: (i) Are electron cofactors including P700, A

resultsThe key contributions and important findings include: (i) a novel TSR-based method for representing 3D structures of pigments as well as for quantifying pigment structures was developed; (ii) the results revealed that the redox cofactor, P700, are structurally conserved and different from other redox factors. Similar situations were also observed for both A

conclusionsThe structural analyses of redox cofactors and their binding sites provide a foundation for understanding the unique chemical and physical properties of each redox cofactor in PS I, which are essential for modulating the rate and direction of energy and electron transfers.

Indexed as

AlgorithmsCoenzymesPhotosystem I Protein ComplexBinding SitesDatabases, ProteinModels, MolecularProtein ConformationCoenzymesPhotosystem I Protein ComplexCofactor and protein interactionCofactor binding site and A and B branchesPhotosystem IRepresentation of cofactor 3D structuresTSR-based method

Identifiers

PMID39810075
PMCPMC11731568

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.