Plant catalase in silico characterization and phylogenetic analysis with structural modeling

Abstract

Background Catalase (EC 1.11.1.6) is a heme-containing tetrameric enzyme that plays a critical role in signaling and hydrogen peroxide metabolism. It was the first enzyme to be crystallized and isolated. Catalase is a well-known industrial enzyme used in diagnostic and analytical methods in the form of biomarkers and biosensors, as well as in the textile, paper, food, and pharmaceutical industries. In silico analysis of CAT genes and proteins has gained increased interest, emphasizing the development of biomarkers and drug designs. The present work aims to understand the catalase evolutionary relationship of plant species and analyze its physicochemical characteristics, homology, phylogenetic tree construction, secondary structure prediction, and 3D modeling of protein sequences and its validation using a variety of conventional computational methods to assist researchers in better understanding the structure of proteins. Results Around 65 plant catalase sequences were computationally evaluated and subjected to bioinformatics assessment for physicochemical characterization, multiple sequence alignment, phylogenetic construction, motif and domain identification, and secondary and tertiary structure prediction. The phylogenetic tree revealed six unique clusters where diversity of plant catalases was found to be the largest for Oryza sativa. The thermostability and hydrophilic nature of these proteins were primarily observed, as evidenced by a relatively high aliphatic index and negative GRAVY value. The distribution of 5 sequence motifs was uniformly distributed with a width length of 50 with the best possible amino residue sequences that resemble the plant catalase PLN02609 superfamily. Using SOPMA, the predicted secondary structure of the protein sequences revealed the predominance of the random coil. The predicted 3D CAT model from Arabidopsis thaliana was a homotetramer, thermostable protein with 59-KDa weight, and its structural validation was confirmed by PROCHECK, ERRAT, Verify3D, and Ramachandran plot. The functional relationships of our query sequence revealed the glutathione reductase as the closest interacting protein of query protein. Conclusions This theoretical plant catalases in silico analysis provide insight into its physiochemical characteristics and functional and structural understanding and its evolutionary behavior and exploring protein structure-function relationships when crystal structures are unavailable.

Secretome Analysis for a New Strain of the Blackleg Fungus Plenodomus lingam Reveals Candidate Proteins for Effectors and Virulence Factors

“…The AI refers to the relative volume occupied by a protein's aliphatic hydrophobic side chains of amino acids such as V (valine), A (alanine), L (leucine), and I (isoleucine). It is an indicator of the thermal stability of proteins: the higher the AI value, the more stable the protein is at high temperatures [63,65]. AI values of the studied secretome reflected high thermostability of 177 proteins (70.09-95.97) over wide temperature ranges (Table S2).…”

“…The GRAVY score of 200 proteins was found to be negative, with values ranging from −0.002 to 0.721 (Figure 2c). The negative GRAVY score predicts that these proteins could be hydrophilic (polar) with good solubility, rather than hydrophobic (non-polar) [65].…”

In Silico Evaluation, Phylogenetic Analysis, and Structural Modeling of the Class II Hydrophobin Family from Different Fungal Phytopathogens

“…determines the hydrophilic or hydrophobic nature of proteins [77]. All proteins showed positive GRAVY scores except one protein (KAI3335996.1), which showed a negative GRAVY score (−0.119) (Figure 1a).…”

“…The AI values of the studied proteins reflected the high thermostability of most hydrophobin proteins (53.93-110.95) over wide temperature ranges (Table S2). GRAVY is one of the important parameters studied that determines the hydrophilic or hydrophobic nature of proteins [77]. All proteins showed positive GRAVY scores except one protein (KAI3335996.1), which showed a negative GRAVY score (−0.119) (Figure 1a).…”

Studies on the structure and stimulating effect on Caco-2 cells of flagellin and its truncated proteins of Escherichia coli Nissle 1917

“…CD can be used to determine protein conformation in solution state, with a fast and simple method that is sensitive to conformational changes (Sreerama, et al 2004). At the same time, the development of various arti cial intelligences such as AlphaFold2 provides another way for the research of protein structure and function (Nene, et al 2022;Goulet, et al 2022).…”