Chemically identical chlorophyll (Chl) molecules undergo conformational changes when they are embedded in a protein matrix. The conformational changes will modulate their absorption spectra to meet the need for programmed excitation energy transfer or electron transfer. To interpret spectroscopic data using the knowledge of pigment–protein interactions requires a single pigment embedded in one polypeptide matrix. Unfortunately, most of the known photosynthetic systems contain a set of multiple pigments in each protein subunit. This makes it complicated to interpret spectroscopic data using structural data due to the potential overlapping spectra of two or more pigments. Chl–protein interactions have not been systematically studied to answer three fundamental questions: (i) What are the structural characteristics and commonly shared substructures of different types of Chl molecules (e.g., Chl a, b, c, d, and f)? (ii) How many structural groups can Chl molecules be divided into and how are different structural groups influenced by their surrounding environments? (iii) What are the structural characteristics of pigment surrounding environments? Having no clear answers to the unresolved questions is probably due to a lack of computational methods for quantifying conformational changes in individual Chls and individual surrounding amino acids. The first version of the Triangular Spatial Relationship (TSR)-based method was developed for comparing protein 3D structures. The input data for the TSR-based method are experimentally determined 3D structures from the Protein Data Bank (PDB). In this study, we take advantage of the 3D structures of Chl-binding proteins deposited in the PDB and the TSR-based method to systematically investigate the 3D structures of various types of Chls and their protein environments. The key contributions of this study can be summarized as follows: (i) Specific structural characteristics of Chl d and f were identified and are defined using the TSR keys. (ii) Two and three clusters were found for various types of Chls and Chls a, respectively. The signature structures for distinguishing their corresponding two and three clusters were identified. (iii) Histidine residues were used as an example for revealing structural characteristics of Chl-binding sites. This study provides evidence for the three unresolved questions and builds a structural foundation through quantifying Chl conformations as well as structures of their embedded protein environments for future mechanistic understanding of relationships between Chl–protein interactions and their corresponding spectroscopic data. 
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                    This content will become publicly available on January 14, 2026
                            
                            Development of a TSR-based method for understanding structural relationships of cofactors and local environments in photosystem I
                        
                    
    
            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-1and 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? 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-1and A0; (iii) the results demonstrated structural differences between A and B branches for the redox cofactors P700, A-1, A0and A1as well as their cofactor binding sites; (iv) the tryptophan residues close to A0and A1are structurally conserved; (v) The TSR-based method outperforms the Root Mean Square Deviation (RMSD) and the Ultrafast Shape Recognition (USR) methods. 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. 
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                            - Award ID(s):
- 2313482
- PAR ID:
- 10631284
- Publisher / Repository:
- BMC Bioinformatics
- Date Published:
- Journal Name:
- BMC Bioinformatics
- Volume:
- 26
- Issue:
- 1
- ISSN:
- 1471-2105
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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