Cargando…

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

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 understan...

Descripción completa

Detalles Bibliográficos
Autores principales: Rasheed, Faiza, Markgren, Joel, Hedenqvist, Mikael, Johansson, Eva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071054/
https://www.ncbi.nlm.nih.gov/pubmed/32079172
http://dx.doi.org/10.3390/molecules25040873
_version_ 1783506115951067136
author Rasheed, Faiza
Markgren, Joel
Hedenqvist, Mikael
Johansson, Eva
author_facet Rasheed, Faiza
Markgren, Joel
Hedenqvist, Mikael
Johansson, Eva
author_sort Rasheed, Faiza
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7071054
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-70710542020-03-19 Modeling to Understand Plant Protein Structure-Function Relationships—Implications for Seed Storage Proteins Rasheed, Faiza Markgren, Joel Hedenqvist, Mikael Johansson, Eva Molecules Review 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. MDPI 2020-02-17 /pmc/articles/PMC7071054/ /pubmed/32079172 http://dx.doi.org/10.3390/molecules25040873 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Rasheed, Faiza
Markgren, Joel
Hedenqvist, Mikael
Johansson, Eva
Modeling to Understand Plant Protein Structure-Function Relationships—Implications for Seed Storage Proteins
title Modeling to Understand Plant Protein Structure-Function Relationships—Implications for Seed Storage Proteins
title_full Modeling to Understand Plant Protein Structure-Function Relationships—Implications for Seed Storage Proteins
title_fullStr Modeling to Understand Plant Protein Structure-Function Relationships—Implications for Seed Storage Proteins
title_full_unstemmed Modeling to Understand Plant Protein Structure-Function Relationships—Implications for Seed Storage Proteins
title_short Modeling to Understand Plant Protein Structure-Function Relationships—Implications for Seed Storage Proteins
title_sort modeling to understand plant protein structure-function relationships—implications for seed storage proteins
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071054/
https://www.ncbi.nlm.nih.gov/pubmed/32079172
http://dx.doi.org/10.3390/molecules25040873
work_keys_str_mv AT rasheedfaiza modelingtounderstandplantproteinstructurefunctionrelationshipsimplicationsforseedstorageproteins
AT markgrenjoel modelingtounderstandplantproteinstructurefunctionrelationshipsimplicationsforseedstorageproteins
AT hedenqvistmikael modelingtounderstandplantproteinstructurefunctionrelationshipsimplicationsforseedstorageproteins
AT johanssoneva modelingtounderstandplantproteinstructurefunctionrelationshipsimplicationsforseedstorageproteins