Análise estrutural e evolutiva de famílias de hemoproteinas de plantas

Abstract

Heme proteins play fundamental roles in various cellular processes in plants, including electron transfer, oxygen metabolism, and stress responses. This work brings together two structural bioinformatics approaches focused on the study of these proteins in different plant species. The first chapter centers on catalase, a key enzyme in the decomposition of hydrogen peroxide (H2O2) in peroxisomes, particularly relevant due to its functional interaction with glycolate oxidase (GOX) in Oryza sativa. Catalases from this species and from representatives of the Fabaceae family were modeled to provide a structural basis for future studies. The predicted models were compared to experimental structures available in the Protein Data Bank (PDB) and evaluated through molecular dynamics simulations, demonstrating high structural quality, stability, and strong conservation with known catalases. These models may serve as references for comparative structural analyses, protein engineering, and the development of stress-tolerant plants through targeted mutagenesis. The second chapter presents a systematic analysis of heme proteins in Arabidopsis thaliana, focusing on structural and evolutionary aspects. A total of 390 sequences were analyzed for conserved motifs, with 366 used to construct a phylogenetic tree. Predicted structures obtained using AlphaFold2 were subjected to molecular dynamics simulations and analyzed with the RING tool to identify non-covalent interactions with the heme group. The results revealed a high evolutionary divergence among the heme proteins and the absence of a single common heme-binding motif across all sequences. However, conserved patterns were identified among proteins belonging to specific domain families, with five recurrent motifs observed in the classes of peroxidases and cytochrome P450s, which account for the majority of the identified heme proteins. These findings may assist in the functional annotation of uncharacterized proteins, the identification of new targets for metabolic engineering, and the improvement of functional prediction tools for plant genomes.