Protein interactions and ligand binding: From protein subfamilies to functional specificity

The divergence accumulated during the evolution of protein families translates into their internal organization as subfamilies, and it is directly reflected in the characteristic patterns of differentially conserved residues. These specifically conserved positions in protein subfamilies are known as “specificity determining positions” (SDPs). Previous studies have limited their analysis to the study of the relationship between these positions and ligand-binding specificity, demonstrating significant yet limited predictive capacity. We have systematically extended this observation to include the role of differential protein interactions in the segregation of protein subfamilies and explored in detail the structural distribution of SDPs at protein interfaces. Our results show the extensive influence of protein interactions in the evolution of protein families and the widespread association of SDPs with protein interfaces. The combined analysis of SDPs in interfaces and ligand-binding sites provides a more complete picture of the organization of protein families, constituting the necessary framework for a large scale analysis of the evolution of protein function.

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Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2016.00054 ◽

2016 ◽

Vol 3 ◽

Cited By ~ 8

Author(s):

Elise Delaforge ◽

Sigrid Milles ◽

Jie-rong Huang ◽

Denis Bouvier ◽

Malene Ringkjøbing Jensen ◽

...

Keyword(s):

Protein Interactions ◽

Large Scale ◽

Protein Protein Interactions ◽

Domain Dynamics

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FrustratometeR: an R-package to compute Local frustration in protein structures, point mutants and MD simulations

10.1101/2020.11.26.400432 ◽

2020 ◽

Author(s):

Atilio O. Rausch ◽

Maria I. Freiberger ◽

Cesar O. Leonetti ◽

Diego M. Luna ◽

Leandro G. Radusky ◽

...

Keyword(s):

Protein Interactions ◽

Large Scale ◽

Protein Structures ◽

Md Simulations ◽

R Package ◽

Protein Protein Interactions ◽

Large Scale Analysis ◽

Functional Aspects ◽

Catalytic Sites ◽

Polypeptide Chains

Once folded natural protein molecules have few energetic conflicts within their polypeptide chains. Many protein structures do however contain regions where energetic conflicts remain after folding, i.e. they have highly frustrated regions. These regions, kept in place over evolutionary and physiological timescales, are related to several functional aspects of natural proteins such as protein-protein interactions, small ligand recognition, catalytic sites and allostery. Here we present FrustratometeR, an R package that easily computes local energetic frustration on a personal computer or a cluster. This package facilitates large scale analysis of local frustration, point mutants and MD trajectories, allowing straightforward integration of local frustration analysis in to pipelines for protein structural analysis.Availability and implementation: https://github.com/proteinphysiologylab/frustratometeR

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iProteinDB: an integrative database of Drosophila post-translational modifications

10.1101/386268 ◽

2018 ◽

Cited By ~ 2

Author(s):

Yanhui Hu ◽

Richelle Sopko ◽

Verena Chung ◽

Romain A. Studer ◽

Sean D. Landry ◽

...

Keyword(s):

Protein Interactions ◽

Protein Function ◽

Large Scale ◽

Model Organisms ◽

General Strategy ◽

Post Translational Modification ◽

Post Translational Modifications ◽

Functional Sites ◽

Evolutionarily Conserved ◽

And Function

AbstractPost-translational modification (PTM) serves as a regulatory mechanism for protein function, influencing stability, protein interactions, activity and localization, and is critical in many signaling pathways. The best characterized PTM is phosphorylation, whereby a phosphate is added to an acceptor residue, commonly serine, threonine and tyrosine. As proteins are often phosphorylated at multiple sites, identifying those sites that are important for function is a challenging problem. Considering that many phosphorylation sites may be non-functional, prioritizing evolutionarily conserved phosphosites provides a general strategy to identify the putative functional sites with regards to regulation and function. To facilitate the identification of conserved phosphosites, we generated a large-scale phosphoproteomics dataset from Drosophila embryos collected from six closely-related species. We built iProteinDB (https://www.flyrnai.org/tools/iproteindb/), a resource integrating these data with other high-throughput PTM datasets, including vertebrates, and manually curated information for Drosophila. At iProteinDB, scientists can view the PTM landscape for any Drosophila protein and identify predicted functional phosphosites based on a comparative analysis of data from closely-related Drosophila species. Further, iProteinDB enables comparison of PTM data from Drosophila to that of orthologous proteins from other model organisms, including human, mouse, rat, Xenopus laevis, Danio rerio, and Caenorhabditis elegans.

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Algorithms for protein interaction networks

Biochemical Society Transactions ◽

10.1042/bst0330530 ◽

2005 ◽

Vol 33 (3) ◽

pp. 530-534 ◽

Cited By ~ 3

Author(s):

M. Lappe ◽

L. Holm

Keyword(s):

Protein Interactions ◽

Biological Networks ◽

Protein Function ◽

Large Scale ◽

Sequence Similarity ◽

Functional Characterization ◽

Interaction Networks ◽

Computational Techniques ◽

Interaction Patterns ◽

Main Challenge

The functional characterization of all genes and their gene products is the main challenge of the postgenomic era. Recent experimental and computational techniques have enabled the study of interactions among all proteins on a large scale. In this paper, approaches will be presented to exploit interaction information for the inference of protein structure, function, signalling pathways and ultimately entire interactomes. Interaction networks can be modelled as graphs, showing the operation of gene function in terms of protein interactions. Since the architecture of biological networks differs distinctly from random networks, these functional maps contain a signal that can be used for predictive purposes. Protein function and structure can be predicted by matching interaction patterns, without the requirement of sequence similarity. Moving on to a higher level definition of protein function, the question arises how to decompose complex networks into meaningful subsets. An algorithm will be demonstrated, which extracts whole signal-transduction pathways from noisy graphs derived from text-mining the biological literature. Finally, an algorithmic strategy is formulated that enables the proteomics community to build a reliable scaffold of the interactome in a fraction of the time compared with uncoordinated efforts.

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High throughput flow cytometry based yeast two-hybrid array approach for large-scale analysis of protein-protein interactions

Cytometry Part A ◽

10.1002/cyto.a.21144 ◽

2011 ◽

Vol 81A (1) ◽

pp. 90-98 ◽

Cited By ~ 7

Author(s):

Jun Chen ◽

Mark B. Carter ◽

Bruce S. Edwards ◽

Hong Cai ◽

Larry A. Sklar

Keyword(s):

Flow Cytometry ◽

High Throughput ◽

Protein Interactions ◽

Large Scale ◽

Scale Analysis ◽

Protein Protein Interactions ◽

Yeast Two Hybrid ◽

Large Scale Analysis ◽

Two Hybrid

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Folding and unfolding for binding: large-scale protein dynamics in protein–protein interactions

Biochemical Society Transactions ◽

10.1042/bst0340971 ◽

2006 ◽

Vol 34 (5) ◽

pp. 971-974 ◽

Cited By ~ 4

Author(s):

G.C.K. Roberts

Keyword(s):

Protein Dynamics ◽

Protein Interactions ◽

Dynamic Process ◽

Large Scale ◽

Protein Protein Interactions ◽

Key Residues

The role of dynamics in the function of proteins, from enzymes to signalling proteins, is widely recognized. In many cases, the dynamic process is a relatively localized one, involving motion of a limited number of key residues, while in others large-scale domain movements may be involved. These motions all take place within the context of a folded protein; however, there is increasing evidence for the existence of some proteins where a transition between folded and unfolded structures is required for function.

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Reliable identification of protein-protein interactions by crosslinking mass spectrometry

10.1101/2020.05.25.114256 ◽

2020 ◽

Author(s):

Swantje Lenz ◽

Ludwig R. Sinn ◽

Francis J. O’Reilly ◽

Lutz Fischer ◽

Fritz Wegner ◽

...

Keyword(s):

Mass Spectrometry ◽

Protein Interactions ◽

Large Scale ◽

Protein Complexes ◽

Estimation Procedure ◽

Scale Analysis ◽

Protein Protein Interactions ◽

False Discovery ◽

Large Scale Analysis ◽

False Discovery Rate Estimation

Crosslinking mass spectrometry is widening its scope from structural analyzes of purified multi-protein complexes towards systems-wide analyzes of protein-protein interactions. Assessing the error in these large datasets is currently a challenge. Using a controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate a reliable false-discovery rate estimation procedure for protein-protein interactions identified by crosslinking mass spectrometry.

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Molecular Biologist's Guide to Proteomics

Microbiology and Molecular Biology Reviews ◽

10.1128/mmbr.66.1.39-63.2002 ◽

2002 ◽

Vol 66 (1) ◽

pp. 39-63 ◽

Cited By ~ 312

Author(s):

Paul R. Graves ◽

Timothy A. J. Haystead

Keyword(s):

Posttranslational Modifications ◽

Protein Function ◽

Large Scale ◽

Protein Identification ◽

Functional Proteomics ◽

Computer Algorithms ◽

Large Scale Analysis ◽

Proteomics Approach ◽

And Function ◽

Identification And Characterization

SUMMARY The emergence of proteomics, the large-scale analysis of proteins, has been inspired by the realization that the final product of a gene is inherently more complex and closer to function than the gene itself. Shortfalls in the ability of bioinformatics to predict both the existence and function of genes have also illustrated the need for protein analysis. Moreover, only through the study of proteins can posttranslational modifications be determined, which can profoundly affect protein function. Proteomics has been enabled by the accumulation of both DNA and protein sequence databases, improvements in mass spectrometry, and the development of computer algorithms for database searching. In this review, we describe why proteomics is important, how it is conducted, and how it can be applied to complement other existing technologies. We conclude that currently, the most practical application of proteomics is the analysis of target proteins as opposed to entire proteomes. This type of proteomics, referred to as functional proteomics, is always driven by a specific biological question. In this way, protein identification and characterization has a meaningful outcome. We discuss some of the advantages of a functional proteomics approach and provide examples of how different methodologies can be utilized to address a wide variety of biological problems.

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