Fatima Shahid, Neeladri Sen, Hawa Najibah Rasni, Nurulhikma Md Isa, Nyuk Ling Ma, Christine Orengo, Su Datt Lam
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引用次数: 0
Abstract
Plants face formidable challenges due to environmental stresses, including pathogens, salt, drought, cold, heat, heavy metal exposure, and flooding, all of which affect growth and agricultural productivity. To combat these stresses, plants have evolved various adaptive mechanisms, including the expression of stress-response proteins. Exploring the three-dimensional structures of plant proteins can be valuable for discovering and characterising stress tolerance mechanisms at the molecular level. Until recently, large-scale analyses were not feasible due to the limited number of experimentally determined plant protein structures. However, the recently developed AlphaFold, RoseTTA-Fold, and ESM-fold protein structure prediction methods, along with their associated portals, now provide hundreds of millions of high-quality predicted 3D models, covering a wide range of plant proteins. This review highlights insights from recent structural investigations into plant stress response using experimental or predicted protein structures. We include analyses of diverse paralogs and isoforms and insights from molecular docking and molecular dynamics simulations. We consider the value of using experimental and predicted structural data in understanding the mechanisms of common stress-modulating plant proteins. Studying the structures of these proteins together with their inferred functions can aid improvements in crop productivity, help foster sustainable agriculture, and contribute to global food security efforts.
期刊介绍:
Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:
Structure and function of proteins, nucleic acids and other macromolecules
Structure and function of multi-component complexes
Protein folding, processing and degradation
Enzymology
Computational and structural studies of plant systems
Microbial Informatics
Genomics
Proteomics
Metabolomics
Algorithms and Hypothesis in Bioinformatics
Mathematical and Theoretical Biology
Computational Chemistry and Drug Discovery
Microscopy and Molecular Imaging
Nanotechnology
Systems and Synthetic Biology