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

doi:10.1186/s12859-025-06038-y

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

BMC Bioinformatics. 2025 Jan 14;26(1):15. doi: 10.1186/s12859-025-06038-y.

Authors

Lujun Luo¹, Tarikul I Milon¹, Elijah K Tandoh¹, Walter J Galdamez¹, Andrei Y Chistoserdov², Jianping Yu³, Jan Kern⁴, Yingchun Wang⁵, Wu Xu⁶

Affiliations

¹ Department of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
² Department of Biology, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA.
³ Biosciences Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA.
⁴ Bioenergetics Department, MBIB Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
⁵ Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
⁶ Department of Chemistry, University of Louisiana at Lafayette, Lafayette, LA, 70504, USA. [email protected].

PMID: 39810075
DOI: 10.1186/s12859-025-06038-y

Abstract

Background: All 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_-1 and A₀, which are chemically identical chlorophylls, structurally different? (ii) There are two electron transfer chains (A and B branches) in PS I. Are the cofactors on both branches structurally different? (iii) Are the amino acids in cofactor binding sites structurally different from those not in cofactor binding sites?

Results: The 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_-1 and A₀; (iii) the results demonstrated structural differences between A and B branches for the redox cofactors P700, A_-1, A₀ and A₁ as well as their cofactor binding sites; (iv) the tryptophan residues close to A₀ and A₁ are structurally conserved; (v) The TSR-based method outperforms the Root Mean Square Deviation (RMSD) and the Ultrafast Shape Recognition (USR) methods.

Conclusions: The 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.

Keywords: Cofactor and protein interaction; Cofactor binding site and A and B branches; Photosystem I; Representation of cofactor 3D structures; TSR-based method.

MeSH terms

Algorithms*
Binding Sites
Databases, Protein
Models, Molecular
Photosystem I Protein Complex* / chemistry
Photosystem I Protein Complex* / metabolism
Protein Conformation

Substances

Photosystem I Protein Complex

Abstract

MeSH terms

Substances

Grants and funding