Computational Study of Photosynthetic Pigments: Toward Synthetic Photosynthesis Engineering
Chlorophyll is a widely known photosynthetic pigment in plants, algae, and cyanobacteria, along with bacteriochlorophyll in some photosynthetic bacteria. The pigments consist of tetrapyrrole structures that carry a single magnesium atom at the center. They play important parts in the light-harvestin...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Department of Chemistry, Universitas Gadjah Mada
2025-07-01
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| Series: | Indonesian Journal of Chemistry |
| Subjects: | |
| Online Access: | https://jurnal.ugm.ac.id/ijc/article/view/105059 |
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| Summary: | Chlorophyll is a widely known photosynthetic pigment in plants, algae, and cyanobacteria, along with bacteriochlorophyll in some photosynthetic bacteria. The pigments consist of tetrapyrrole structures that carry a single magnesium atom at the center. They play important parts in the light-harvesting process in photosynthesis. This study aimed to characterize and compare the electronic profiles of chlorophyll and bacteriochlorophyll pigments by using in silico computational approaches, such as density functional theory (DFT), electronic transfer property analysis, and protein-pigment interaction studies via molecular docking. The results showed that chlorophylls a, b, and c have the highest energy gaps at the ground state DFT. For bacteriochlorophylls, bacteriochlorophylls g and b have the highest energy gaps. The time-dependent DFT and the follow-up calculations, including extinction coefficient, tunneling rate, and coherence time, indicated bacteriochlorophyll g as a highly promising and efficient pigment. Additionally, chlorophyll c and bacteriochlorophylls c and d showed the strongest binding affinities with the chlorophyll-binding protein of plant photosystem II. This study provides a comprehensive and replicable computational pipeline for pigment profiling, advancing future synthetic photosynthesis designs through combined quantum and synthetic biology insights. |
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| ISSN: | 1411-9420 2460-1578 |