In Silico Structural Analysis of Chlorophyll Synthase: A Comparative Study between Monocot and Eudicot

Chlorophyll, a member of an essential class of green pigments, is predominantly found in all mature plant cells, whether in the leaf of a green plant or any photosynthetic organisms, including cyanobacteria or algal species. The primary function of this pigment is to convert the light energy into chemical energy through a series of synthesizing several chemical compounds; alternatively, the whole process is termed as 'Photosynthesis.' Monocots and eudicots are two different variants of angiosperms or flowering plants, where this chlorophyll synthesis occurs distinctly. Our present course of study mainly aims at the in silico comparative structural analysis of chlorophyll synthase enzyme in these two divergent angiosperm species.After retrieving the FASTA sequence for each plant chlorophyll synthase from the UniProt database, Multiple Sequence Alignment followed by Phylogenetic Tree preparation was done using CLUSTALW; the primary and secondary structural components analyses were done by ExPASy ProtParam and GOR4 server; after that 3D structure of each of the protein sequence was generated via Homology Modelling using SWISS-MODELonline server. Lastly, each of the protein models was undergone through various quality checking parameters. Multiple Sequence Alignment followed by Phylogenetic Tree prediction and 3D structure superposition analysis reveals that though the chlorophyll synthases of these two divergent angiosperm species evolved in different time scales, they share highly conserved structure. Since the structure is the basis of function, the findings support the overall functional importance of the terminal enzyme of the chlorophyll synthesis pathway.

@article{moumita2026,
  author  = {Moumita Saha1, Ranjita Mukherjee1, Sirshendu Chatterjee1*, Chandreyi Ghosh1, Pranabesh Ghosh2},
  title   = {{In Silico Structural Analysis of Chlorophyll Synthase: A Comparative Study between Monocot and Eudicot}},
  journal = {Journal of Bioresearch},
  year    = {2026},
  volume  = {1},
  number  = {2},
  doi     = {https://doi.org/10.17605/OSF.IO/6Q2JU},
}