Modeling to Understand Plant Protein Structure-Function Relationships-Implications for Seed Storage Proteins

Abstract

Proteins are among the most important molecules on Earth. Their structure and aggregation behavior are key to their functionality in living organisms and in protein-rich products. Innovations, such as increased computer size and power, together with novel simulation tools have improved our understanding of protein structure-function relationships. This review focuses on various proteins present in plants and modeling tools that can be applied to better understand protein structures and their relationship to functionality, with particular emphasis on plant storage proteins. Modeling of plant proteins is increasing, but less than 9% of deposits in the Research Collaboratory for Structural Bioinformatics Protein Data Bank come from plant proteins. Although, similar tools are applied as in other proteins, modeling of plant proteins is lagging behind and innovative methods are rarely used. Molecular dynamics and molecular docking are commonly used to evaluate differences in forms or mutants, and the impact on functionality. Modeling tools have also been used to describe the photosynthetic machinery and its electron transfer reactions. Storage proteins, especially in large and intrinsically disordered prolamins and glutelins, have been significantly less well-described using modeling. These proteins aggregate during processing and form large polymers that correlate with functionality. The resulting structure-function relationships are important for processed storage proteins, so modeling and simulation studies, using up-to-date models, algorithms, and computer tools are essential for obtaining a better understanding of these relationships.

Keywords: albumin; globulin; glutelin; molecular dynamics simulation; monte carlo simulation; prolamin.

Figure 1

Single subunits and polymers obtained from these, of (left to right): The storage proteins 7S globulin in soybean, 11S globulin in pea, a-gliadin in wheat, and low molecular weight glutenin subunits (LMW-GS) in wheat. Amino acid sequences and simulation tools applied to determine the structures are described in Yoshizawa et al. [107] and Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (3AUP) [39] for 7S globulin, and in Tandang-Silvas et al. [108] and RSCB PDB (3KSC) [39] for 11S globulin. Amino acids sequences for a-gliadin and LMW-GS can be found at Uniprot accession numbers Q9ZP09 and P10386 and simulation was carried out using an all-atom model with Monte Carlo algorithms in the program Profasi [126]. All models were visualized using Visual Molecular Dynamics [127].