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Abstract Structures of proteins and protein–protein complexes are determined by the same physical principles and thus share a number of similarities. At the same time, there could be differences because in order to function, proteins interact with other molecules, undergo conformations changes, and so forth, which might impose different restraints on the tertiary versus quaternary structures. This study focuses on structural properties of protein–protein interfaces in comparison with the protein core, based on the wealth of currently available structural data and new structure‐based approaches. The results showed that physicochemical characteristics, such as amino acid composition, residue–residue contact preferences, and hydrophilicity/hydrophobicity distributions, are similar in protein core and protein–protein interfaces. On the other hand, characteristics that reflect the evolutionary pressure, such as structural composition and packing, are largely different. The results provide important insight into fundamental properties of protein structure and function. At the same time, the results contribute to better understanding of the ways to dock proteins. Recent progress in predicting structures of individual proteins follows the advancement of deep learning techniques and new approaches to residue coevolution data. Protein core could potentially provide large amounts of data for application of the deep learning to docking. However, our results showed that the core motifs are significantly different from those at protein–protein interfaces, and thus may not be directly useful for docking. At the same time, such difference may help to overcome a major obstacle in application of the coevolutionary data to docking—discrimination of the intramolecular information not directly relevant to docking.
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Bioinformatic Approaches for Characterizing Molecular Structure and Function of Food Proteins
Structural bioinformatics analyzes protein structural models with the goal of uncovering molecular drivers of food functionality. This field aims to develop tools that can rapidly extract relevant information from protein databases as well as organize this information for researchers interested in studying protein functionality. Food bioinformaticians take advantage of millions of protein amino acid sequences and structures contained within these databases, extracting features such as surface hydrophobicity that are then used to model functionality, including solubility, thermostability, and emulsification. This work is aided by a protein structure–function relationship framework, in which bioinformatic properties are linked to physicochemical experimentation. Strong bioinformatic correlations exist for protein secondary structure, electrostatic potential, and surface hydrophobicity. Modeling changes in protein structures through molecular mechanics is an increasingly accessible field that will continue to propel food science research.
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- Award ID(s):
- 2003635
- PAR ID:
- 10412946
- Date Published:
- Journal Name:
- Annual Review of Food Science and Technology
- Volume:
- 14
- Issue:
- 1
- ISSN:
- 1941-1413
- Page Range / eLocation ID:
- 203 to 224
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1146/annurev-food-060721-022222
