Plant catalase in silico characterization and phylogenetic analysis with structural modeling

Area of Science:

• Biochemistry
• Computational Biology
• Bioinformatics

Background:

• Catalase (EC 1.11.1.6) is a vital heme enzyme involved in cellular signaling and hydrogen peroxide metabolism.
• It is a historically significant enzyme, being the first to be crystallized, and has broad industrial applications.
• In silico analysis of catalase genes and proteins is increasingly important for biomarker and drug development.

Purpose of the Study:

• To investigate the evolutionary relationships among plant catalase species.
• To characterize the physicochemical properties of plant catalases.
• To predict and validate protein structures and identify functional relationships using computational methods.

Main Methods:

• Computational evaluation of approximately 65 plant catalase sequences.
• Bioinformatics assessments including physicochemical characterization, multiple sequence alignment, and phylogenetic tree construction.
• Secondary and tertiary structure prediction (SOPMA) and 3D model validation (PROCHECK, ERRAT, Verify3D, Ramachandran plot).

Main Results:

• Phylogenetic analysis identified six distinct clusters, with Oryza sativa showing the greatest catalase diversity.
• Proteins exhibited thermostability and hydrophilic characteristics (high aliphatic index, negative GRAVY value).
• Predicted secondary structures were dominated by random coils; a 3D model of Arabidopsis thaliana catalase was validated as a thermostable homotetramer.

Conclusions:

• In silico analysis provides valuable insights into the physiochemical characteristics, structure, and evolution of plant catalases.
• This study enhances the understanding of protein structure-function relationships, particularly when experimental crystal structures are unavailable.
• The findings aid researchers in comprehending plant catalase behavior and potential applications.