Key Points
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Since the turn of the century, high-throughput interaction mapping has emerged as an extremely useful approach for connecting genotype with phenotype. Such studies allow us to assign functionality to whole genes or proteins but not to specific domains or residues.
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Many naturally occurring mutations, including many of those that cause disease, result in the alteration of a single residue on a protein rather than the complete loss of function or a truncation. Understanding the consequences of such mutations requires higher-resolution interaction networks.
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Computational methods can be used to integrate structural information with existing protein–protein interaction networks to improve their resolution. Such approaches range from methods that identify the domains responsible for specific interactions to those that allow the complete determination of macromolecular structures.
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Experimental methods have been developed to identify 'edgetic' mutations that perturb one or more protein–protein interactions while leaving other interactions intact. Combining the location of these mutations with structural models identifies putative binding sites.
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Genetic and drug–gene interaction profiles can assess the functional consequences of perturbations to specific residues (including those that are post-translationally modified) even in the absence of detected changes to the protein–protein interaction network.
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High-throughput genetic interaction mapping has traditionally been used to study the consequences of knocking out whole genes, but it has recently been adapted to investigate the consequences of mutating specific residues in essential multifunctional protein complexes. In addition to assigning functionality to specific regions, this has shown that mutations that affect residues which are proximal in three-dimensional space frequently have similar interaction profiles, even when they affect different proteins.
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Although the majority of the high-throughput screens discussed have been carried out in model organisms, the same approaches are increasingly being used to study disease-associated mutations in humans.
Abstract
Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein–protein, genetic and drug–gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies.
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Acknowledgements
The authors thank G. Cagney, D. Fitzpatrick and C. Maher for their comments and feedback. They also thank M. Shales and H. Braberg for suggestions and assistance with figures and K. Lasker for assistance with Box 3. C.J.R. is supported by ICON Plc and the University College Dublin Newman Fellowship Programme; P.C. is supported by a Howard Hughes Predoctoral Fellowship; A.S. is supported by the National Institutes of Health (R01 GM083960, U54 RR022220, U54 GM094662, P01 AI091575, and U01 GM098256); N.J.K. is supported by the US National Institutes of Health (P50 GM082250, R01 GM084448, P01 AI090935, P50G M081879, R01 GM098101, R01 GM084279 and P01 AI091575) and the Defense Advanced Research Projects Agency (DARPA-10-93-Prophecy-PA-008).
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FURTHER INFORMATION
Glossary
- Epistasis
-
A phenomenon whereby the phenotype associated with a mutation is altered by the presence or absence of additional mutations.
- Domains
-
Distinct functional or structural regions of a protein, which can fold independently of the rest of the protein. A protein may contain several domains, and the same domain may be present in different proteins.
- Post-translational modifications
-
(PTMs). The chemical modifications of a protein after its translation, which can change the enzymatic activity, subcellular localization or interaction partners of the protein.
- Exome sequencing
-
The targeted sequencing of only known protein-coding regions.
- Nonsense
-
Pertaining to a mutation that changes an amino acid codon to a stop codon.
- Missense
-
Pertaining to a mutation that changes the encoded amino acid.
- Synonymous
-
Pertaining to a mutation that does not change the encoded amino acid.
- Deletion libraries
-
Sets of mutant strains, each of which has a single gene removed. The removed gene is typically replaced with an antibiotic-resistant marker to allow easy selection in genetic experiments.
- Forward genetics
-
The classical genetics approach, in which the genotypes that are associated with particular phenotypes are identified.
- Reverse genetics
-
The inverse approach to forward genetics, in which phenotypes that are associated with a particular genotype are identified. Such approaches are exemplified by studies of knockout mutants.
- Alleles
-
Multiple forms of a gene that occur at a specific locus.
- Reverse Y2H
-
(Reverse yeast two-hybrid). A genetic strategy to select against specific protein–protein interactions.
- Histone
-
A family of proteins that package DNA into nucleosomes. They consist of a globular domain and a tail that is subject to extensive post-translational modifications.
- Pleiotropic
-
Pertaining to a gene that is associated with multiple distinct phenotypes.
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Ryan, C., Cimermančič, P., Szpiech, Z. et al. High-resolution network biology: connecting sequence with function. Nat Rev Genet 14, 865–879 (2013). https://doi.org/10.1038/nrg3574
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DOI: https://doi.org/10.1038/nrg3574
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