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Protein-protein interactions

Protein-protein interaction of a horseshoe ribonuclease inhibitor (skeleton model shown) with ribonuclease. Contacts between two proteins are shown as colored spots.

Protein-protein interactions ( PPIs ) are physical contacts between two or more proteins with high specificity. These contacts are formed as a result of biochemical events using electrostatic interactions , including the [1] .

Proteins are important macromolecules for both intracellular and external processes. Proteins rarely act alone: ​​to participate in various vital processes inside the cell, these macromolecules using protein-protein interactions are assembled into multiprotein complexes . Protein-protein interactions form the basis of the interaction of any living cell [1] . They participate in such important cellular processes as signal transmission , cellular communication, transcription , replication , membrane transport, and others. Therefore, it is not surprising that violations of these interactions lead to many diseases, such as Creutzfeldt-Jakob disease , Alzheimer's disease and cancer [2] .

Not all protein-protein interactions are formed once and for all. Some proteins are part of stable complexes that are molecular machines (for example, ATP synthase or cytochrome oxidase ). Other proteins are reversibly assembled to perform some time function (for example, to activate gene expression in the case of transcription factors and activators ) [1] .

Protein-protein interactions are considered by biochemistry, quantum chemistry, molecular dynamics, cell signaling [3] . The information obtained allows you to create extensive networks of protein interactions, similar to metabolic or genetic / epigenetic bonds. This broadens the current knowledge of biochemical cascades and the pathogenesis of diseases, and also opens up new possibilities for finding new therapeutic targets.

Types of protein-protein interactions

Proteins can “temporarily” bind with each other or form “stable” multiprotein complexes. Moreover, protein complexes can be both hetero- and homo-oligomeric. Classical examples of PPI are the enzyme - inhibitor and antibody - antigen interactions , but apart from them, PPI can occur between two domains or a domain and a peptide [1] .

Homo- and hetero-oligomers

Homo - oligomers are macromolecular complexes consisting of only one type of protein subunit. If a bond is formed between non-identical protein chains, a heterooligomer is formed. Heterooligomers differ in their stability, and for most homooligomeric complexes, symmetry and stability are characteristic. Disassembling of homooligomers often requires denaturation [4] . Some enzymes , transport proteins, transcription factors perform their function being homooligomers. The interactions between different proteins play a large role in cellular signaling.

Mandatory and optional interactions

For the separation of PPI into mandatory and optional information on the stability of the proteins (monomers) involved in the interaction in the free state and as part of the protein complex is needed. If the monomers are stable in vivo only as part of a complex, then the interaction between them is mandatory . As a result of mandatory interactions, mandatory or obligate complexes are formed. If proteins can exist independently, then they participate in optional PPI. Most macromolecular machines in a cell are examples of binding interactions [2] . Mandatory complexes include human cathepsin D and the DNA dimer of the P22 Arc repressor binding protein, and optional interactions include the interaction of RhoA with RhoGAP and thrombin with its inhibitor rootnin [5] .

Permanent and temporary interactions

BBI can be divided by the lifetime of the complex. Constant interactions are usually very stable: when interacting, proteins form a constant complex. They are often present in homo-oligomers (for example, Cytochrome c ) and in some hetero-oligomers (for example, ATPase subunits). Temporary interactions are constantly being formed and destroyed. They can occur when the hormone interacts with the receptor, the transmission of a cellular signal. This type of interaction is widespread in signaling and regulatory pathways [2] .

Covalent and non-covalent interactions

Covalent bonds are the strongest and are formed in the case of electron exchange (for example, disulfide bonds). Although these bonds are rarely found in protein-protein interactions, in some post-translational modifications they are decisive (for example, ubiquitating and hanging SUMO proteins). Non-covalent bonds are usually formed in temporary interactions due to combinations of weak bonds: hydrogen , ionic, van der Waals, or hydrophobic [6] .

Transition from unstructured to structured state

Separately, it is possible to distinguish PPI, which are formed by . In such proteins there are sites, the amino acid sequence of which does not allow to form a stable tertiary structure. These proteins can interact with others, selecting a suitable conformation to form a bond with a partner [2] .

The three-dimensional structure of protein complexes

Molecular structures of many protein complexes were resolved by X-ray diffraction [7] [8] . The first such structure was sperm whale myoglobin [9] . Later, NMR was also used to determine the three-dimensional structure of protein complexes. For example, one of the first was the structure of calmodulin-related domains that interact with calmodulin [8] [10] . This method is well suited for the determination of weak protein-protein interactions [11] .

Domains

Thanks to the development of methods for resolving the three-dimensional structure of proteins, we managed to isolate structural domains that are involved in the formation of PPI. Such, for example, are:

  • Phosphorylated protein SH2 domain;
  • SH3-domain specific to proline- rich sequences;
  • A PTB domain that interacts with sequences containing a phosphotyrosine group;
  • A LIM domain containing a cysteine-rich zinc finger motif and capable of binding to a PDZ domain and its like;
  • SAM-domain binding proteins that do not contain this domain;
  • PDZ domain, S / TXV recognition motif at the C-terminus of the protein, as well as LIM domains or similar ones;
  • FERM-domain capable of binding PI (4,5) P 2 (phosphoinositol-4,5-bisphosphate) [12] .

Biological effects of protein-protein interactions

Protein-protein interactions play an important role in many biological processes. The function and activity of the protein in most cases change upon binding to protein partners. They can have a significant impact on the kinetic parameters of the enzyme due to the allosteric effect, lead to its inactivation (for example, when the enzyme binds to the inhibitor) or to change the specificity of the enzyme to its substrate [13] .

In addition, the interaction of proteins with each other can lead to the formation of a new binding site for the substrate on the surface of the interaction of two molecules. Due to the interaction of two or more enzymes with each other, becomes possible, which increases the efficiency of enzymatic reactions by stabilizing intermediates and increasing their local concentration [13] .

Methods for studying protein-protein interactions

There are many methods for studying protein-protein interactions [13] . Some of them allow us to experimentally determine the protein partners for the studied protein, others only to verify the possible interaction of the two proteins. To confirm the partnership of the two proteins, bimolecular fluorescence complementation (BiFC), FRET-methods, Far-Western, yeast two-hybrid system is used. To solve the problem of detecting partner proteins, coimmunoprecipitation with subsequent affinity chromatography and mass spectrometry is used, the AviTag system with promiscuous BirA ligase. The main problem in the application of these methods is the possible non-specificity of the protein, which is defined as part of the protein complex.

Yeast Two-Hybrid Analysis

 
Principles at the heart of two-hybrid systems for yeast and mammals

Two-hybrid yeasts allow in vivo to detect paired PPI (binary method), as well as non-specific sticky interactions ( 14) .

Yeast cells are transfected with two plasmids: bait — the protein of interest with the linking DNA-binding domain of the yeast transcription factor, for example Gal4, and extraction — the cDNA library (cDNA) of the fragments attached to the activating domain of the transcription factor. If the prey and bait interact, the two domains of the transcription factor join and become functional. Thus, the presence of the results of production of the reporter gene can be judged on the presence of interaction between proteins [6] [15] .

Despite its utility, the yeast two-hybrid system has several limitations: relatively low specificity; the use of yeast as the main host organism, which can lead to problems in the study of other biological systems; relatively low number of detectable PPIs, since some proteins with weak bonds are lost in the process of isolation [16] (for example, membrane proteins are poorly detected [17] [18] ). Restrictions are overcome by using different variants of the two-hybrid system, for example, membrane yeast two-hybrid (membrane yeast two-hybrid) [18] , split-ubiquitin systems [15] , which are not limited to interactions only inside the core; and bacterial dual-hybrid systems (using bacteria, respectively) [19] .

Affinity chromatography followed by mass spectrometry

 
The principle of tandem affinity chromatography

Affinity chromatography with subsequent mass spectrometry makes it possible to detect mostly stable interactions, thereby better reflecting the functional PPIs that exist in a living cell ( in vivo ) [14] [15] . When using this method, first tagged protein, expressed in the cell, usually in in vivo concentrations, and proteins interacting with it ( affinity chromatography ) is isolated . One of the most advantageous and widely used methods for the isolation of proteins in the event of strong background pollution is the method of . BBIs can be qualitatively and quantitatively analyzed by various mass spectrometric methods: chemical fusion, biological or metabolic fusion (SILAC), or methods without using labels [4] .

Computational methods for predicting the BBI

Since there are still no complete data on the intektome and not all the PIDs are detected, various computational methods are used in the reconstruction of signaling or metabolic interaction maps. They allow to eliminate gaps, predicting the presence of certain interactions between network nodes. With the help of computational methods, it is possible to predict not only the possibility of the BBI, but also their strength [2] .

Below are a few computational approaches for predicting the BBI:

  • Search for gene fusion or protein domain events : , which often also means domain fusion, can be used to search for a functional link between proteins. It uses the assumption that the selection of these genes during evolution contributed to the selection [20] .
  • Methods of comparative genomics and clustering of genes : often genes that encode proteins with a similar function or interacting with each other proteins are in the same operon (in the case of bacteria) or co-regulated (co-regulation) (in the case of eukaryotes). Such genes are usually closely located in the genome. Gene clustering methods estimate the probability of the joint occurrence of protein orthologs that encode genes from a single cluster. Such approaches help identify functional interaction between proteins rather than their physical contact [2] .
  • Methods based on phylogenetic profiles : in such methods it is assumed that if non-homologous proteins are functionally related, then there is a possibility that they can join the PPI and co-evolve. In order to find a functional connection between proteins, clustering by these proteins is used, or the probability of joint occurrence of proteins in different proteomes is estimated [2] . The idea that the proteins interacting with each other are often similar in topology to phylogenetic trees is used in the “mirror tree” method [21] .
  • Homology-based prediction methods : this approach assumes that the proteins studied will interact with each other if it is known that their homologs interact. Such pairs of proteins from different organisms that have retained the ability to interact with each other during evolution are called . Examples of services using this method are PPISearch and BIPS [2] .
  • Prediction based on coexpression of genes : if the proteins studied encode genes with similar expression patterns (similar profile and expression level ) at different time intervals, then it can be assumed that these proteins are functionally related and, possibly, somehow interact with each other [ 22] .
  • Methods based on network topology : a WBC network can be represented as a graph, where the nodes are proteins, and each edge indicates the interaction between proteins. With the help of a mathematical interpretation of the WBC network (for example, in the form of an adjacency matrix ), it is possible to determine how proteins are functionally related to each other, as well as to predict new WSPs. If two proteins have a lot of common partners in the network, then most likely they take part in the same biological process and can potentially interact with each other [2] .
  • In-Silico Two-Hybrid approach : the main assumption of this method is that proteins interacting with each other co-evolve to preserve functionality. This method analyzes multiple alignments of the protein family and searches for correlated mutations to predict PPI and search for bases that are in the binding site [23] .
  • Prediction of PPI, based on the structure of proteins : this approach allows not only to find out whether proteins can interact, but also to characterize this interaction (for example, its physical characteristics or amino acids that are part of the interaction surface of two proteins). One of the methods using the three-dimensional structure of proteins is docking . This also includes methods that suggest the evolutionary conservatism of the bases that make up the interaction surface. Thus, on the basis of already known structures, one can predict what the multimolecular complex of the studied proteins will look like [2] .
  • Methods based on machine learning or text mining : on the basis of machine learning, a PPI prediction method was developed that uses only sequences of the studied proteins [24] . This allows you to analyze, although less accurately, a greater number of possible interactions, since only amino acid sequences are used for the work. Predictive text analysis looks for a connection between proteins, considering their mutual reference in sentences or paragraphs of various text blocks [25] .

Bases of protein-protein interactions

A large-scale search for PPIs revealed hundreds of thousands of interactions, information about which was collected in specialized biological databases (DB). These databases are constantly updated in order to provide a complete attack . The first such database was the [26] . Since its inception, the number of public databases has continued to grow. These databases can be divided into three classes: primary, meta-DB and prediction DB [1] .

  • Primary databases collect information about published BBIs whose existence has been proven in small or large scale experiments. For example, these include DIP , Biomolecular Interaction Network Database (BIND), Biological General Repository for Interaction Datasets (BioGRID), Human Protein Reference Database (HPRD), IntAct Molecular Interaction Database, Molecular Interactions Database (MINT), MIPS Protein Interaction Resource on Yeast (MIPS-MPact) and MIPS Mammalian Protein-Protein Interaction Database (MIPS-MPPI) [1] .
  • Meta-databases are usually the result of combining data from primary databases, but may later be replenished with original information. Examples: Agile Protein Interaction DataAnalyzer (APID), The Microbial Protein Interaction Database (MPID8) and Protein Interaction Network Analysis (PINA) platform [1] .
  • The predicted BBI databases are populated with results obtained using various techniques. Examples: Michigan Molecular Interactions (MiMI), Human Protein-Protein Interaction Prediction Database (PIPs), Online Predicted Human Interaction Database (OPHID), Known and Predicted Protein-Protein Interactions (STRING) , and Unified Human Interactome (UniHI) [1 ] .

Protein-protein interaction networks

 
Visualization of a human interactiona , where dots denote proteins, and the blue lines connecting them - interactions between proteins

The information contained in the bases of the BBI, allows you to build a network of protein interactions. The network of PPI for one specific protein is quite possible to describe, for example, using text. But the task of creating a diagram of all kinds of intracellular PPIs is truly complex and difficult to visualize. One example of a manually created molecular interaction map is the cell cycle control map, created by Kurt Kohn in 1999 [27] . Based on the map of Kona, Schwikowski and others, in 2000 they published a map of PPI in yeast, which combined 1548 interacting proteins, information about which was obtained by the two-hybrid analysis method. For visualization, the layer-by-layer image method of the graph was used for the initial location of the vertices, and then the resulting image was improved by applying a force based algorithm [28] [29] .

In order to simplify the complex task of visualization, various bioinformatics tools have been developed, which also allow combining information about PPI with other types of data. For example, the widely used open source package Cytoscape , to which a lot of plug-ins are available [1] [30] . Pajek [31] is suitable for visualizing and analyzing very large networks.

The important role of PPI in physiological and pathological processes is a good motivation for expanding the intectoma. As examples of already published interactomes, one can cite a thyroid-specific interaction by DREAM [32] and PP1α-interactive in the human brain [33] .

Notes

  1. ↑ 1 2 3 4 5 6 7 8 9 De Las Rivas, J .; Fontanillo, C. Protein-protein interactions essentials: key concepts for building and analyzing interactome networks. (English) // PLoS computational biology: journal. - 2010. - Vol. 6 , no. 6 - P. e1000807 . - PMID 20589078 .
  2. ↑ 1 2 3 4 5 6 7 8 9 10 Keskin, O .; Tuncbag, N; Gursoy, A. Predicting Protein – Protein Interactions from the Molecular to the Proteome Level (Eng.) // Chemical Reviews : journal. - 2016. - Vol. 116 , no. 8 - P. 4884-4909 . - PMID 27074302 .
  3. ↑ Herce, HD; Deng, W .; Helma, J .; Leonhardt, H .; Cardoso, MC Visualization of living cells (Eng.) // Nature Communications : journal. - Nature Publishing Group , 2013. - Vol. 4 - P. 2660 . - PMID 24154492 .
  4. ↑ 1 2 Jones, S .; Thornton, JM Principles of protein-protein interactions. (Eng.) // Proceedings of the United States of America : journal. - 1996. - Vol. 93 , no. 1 . - P. 13-20 . - PMID 8552589 .
  5. ↑ Nooren, IM; Thornton, JM Diversity of protein-protein interactions. (Eng.) // EMBO J. : journal. - 2003. - Vol. 22 , no. 14 - P. 3486-3492 . - PMID 12853464 .
  6. ↑ 1 2 Westermarck, J .; Ivaska, J .; Corthals, GL Identification of protein interactions involved in cellular signaling. (English) // Molecular & cellular proteomics: MCP: journal. - 2013. - Vol. 12 , no. 7 - P. 1752-1763 . - PMID 23481661 .
  7. ↑ Janin J. , Chothia C. The structure of the protein-protein recognition sites. (Eng.) // The Journal of biological chemistry. - 1990. - Vol. 265, no. 27 . - P. 16027-16030. - PMID 2204619 .
  8. ↑ 1 2 Bruce, A. Molecular biology of the cell / A. Bruce, A. Johnson, J. Lewis ... [[et al. ] . - 4th. - New York: Garland Science, 2002. - ISBN 0-8153-3218-1 .
  9. ↑ Kendrew, JC; Bodo, G .; Dintzis, HM; Parrish, RG; Wyckoff, H .; Phillips, DC A three-dimensional model of myoglobin molecule by x-ray analysis. (English) // Nature: journal. - 1958. - Vol. 181 , no. 4610 . - P. 662-666 . - PMID 13517261 .
  10. ↑ Wand, AJ; Englander, SW Protein Spectroscopy. (Neopr.) // Current opinion in biotechnology. - 1996. - V. 7 , № 4 . - p . 403-408 . - PMID 8768898 .
  11. ↑ Vinogradova, O .; Qin, J. NMR as a unique tool for assessment and complex determination of weak protein-protein interactions. (English) // Topics in current chemistry: journal. - 2012. - Vol. 326 . - P. 35-45 . - PMID 21809187 .
  12. Ridge Berridge, MJ Cell Signaling Biology: Module 6 - Spatial and Temporal Aspects of Signaling (Eng.) // Biochemical Journal : journal. - 2012. - DOI : 10.1042 / csb0001006 .
  13. 2 1 2 3 Phizicky EM , Fields S. Protein-protein interactions: methods for detection and analysis. (Eng.) // Microbiological reviews. - 1995. - Vol. 59, no. 1 . P. 94-123. - PMID 7708014 .
  14. 2 1 2 Brettner LM , Masel J. Protein stickiness, rather than the number of functional protein-protein interactions, in yeast. (English) // BMC systems biology. - 2012. - Vol. 6. - P. 128. - DOI : 10.1186 / 1752-0509-6-128 . - PMID 23017156 .
  15. ↑ 1 2 3 Wodak, SJ; Vlasblom, J .; Turinsky, AL; Pu, S. Protein-protein interaction networks: the puzzling riches. (English) // Current opinion in structural biology: journal. - 2013. - Vol. 23 , no. 6 - P. 941-953 . - PMID 24007795 .
  16. ↑ Rajagopala, SV; Sikorski, P .; Caufield, JH; Tovchigrechko, A .; Uetz, P. Studying the protein by the yeast two-hybrid system. (English) // Methods: journal. - 2012. - Vol. 58 , no. 4 - P. 392-399 . - PMID 22841565 .
  17. ↑ Stelzl, U .; Wanker, EE The value of high quality protein-protein interaction networks for systems biology. (English) // Current opinion in chemical biology: journal. - 2006. - Vol. 10 , no. 6 - P. 551-558 . - PMID 17055769 .
  18. ↑ 1 2 Petschnigg, J .; Snider, J .; Stagljar, I. Interactive proteomics research technologies: recent applications and advances. (English) // Current opinion in biotechnology: journal. - 2011. - Vol. 22 , no. 1 . - P. 50-8 . - PMID 20884196 .
  19. ↑ Battesti, A; Bouveret, E. The bacterial two-hybrid system based on adenylate cyclase reconstitution in Escherichia coli. (English) // Methods: journal. - 2012. - Vol. 58 , no. 4 - P. 325—334 . - PMID 22841567 .
  20. ↑ Enright, AJ; Iliopoulos, I .; Kyrpides, NC; Ouzounis, CA Protein Interactive Maps for Genomes Based on Gene Fusion Events. (English) // Nature: journal. - 1999. - Vol. 402 , no. 6757 . - P. 86-90 . - PMID 10573422 .
  21. ↑ Pazos, F .; Valencia, A. Similarity of Phylogenetic Trees Indicator of Protein-Protein Interaction. (English) // Protein Eng., Des. Sel. : journal. - 2001. - Vol. 14 , no. 9 - P. 609-614 . - PMID 11707606 .
  22. ↑ Jansen, R .; IGreenbaum, D .; Gerstein, M. Relating Whole-Genome Expression Data with Protein-Protein Interactions. (English) // Genome Res. : journal. - 2002. - Vol. 12 , no. 1 . - P. 37—46 . - PMID 11779829 .
  23. ↑ Pazos, F .; Valencia, A.In Silico Two-Hybrid System for the Selection of Physically Interacting Protein Pairs. (English) // Proteins: Struct., Funct., Genet. : journal. - 2002. - Vol. 47 , no. 2 - P. 219-227 . - PMID 11933068 .
  24. ↑ Shen, J .; IZhang, J .; Luo, X .; Zhu, W .; Yu, K .; Chen, K .; Li, Y .; Jiang, H. Predicting protein-protein interactions based only on sequences information. (Eng.) // Proceedings of the United States of America : journal. - 2007. - Vol. 104 , no. 11 P. 4337-4341 . - PMID 17360525 .
  25. ↑ Papanikolaou, N .; Pavlopoulos, GA; Theodosiou, T .; Iliopoulos, I. Protein-protein interaction predictions using text mining methods. (English) // Methods: journal. - 2015. - Vol. 74 . P. 47–53 . - PMID 25448298 .
  26. ↑ Xenarios I. , Rice DW , Salwinski L. , Baron MK , Marcotte EM , Eisenberg D. DIP: the database of interacting proteins. (Eng.) // Nucleic acids research. - 2000. - Vol. 28, no. 1 . - p. 289-291. - PMID 10592249 .
  27. ↑ Schwikowski B. , Uetz P. , Fields S. A network of protein-protein interactions in yeast. (English) // Nature biotechnology. - 2000. - Vol. 18, no. 12 - p. 1257–1261. - DOI : 10.1038 / 82360 . - PMID 11101803 .
  28. ↑ Rigaut G. , Shevchenko A. , Rutz B. , Wilm M. , Mann M. , Séraphin B. A generic protein purification method. (English) // Nature biotechnology. - 1999. - Vol. 17, no. 10 - P. 1030-1032. - DOI : 10.1038 / 13732 . - PMID 10504710 .
  29. Rie Prieto C. , De Las Rivas J. APID: Agile Protein Interaction DataAnalyzer. (Eng.) // Nucleic acids research. - 2006. - Vol. 34. - P. 298-302. - DOI : 10.1093 / nar / gkl128 . - PMID 16845013 .
  30. ↑ Michael Kohl, Sebastian Wiese, and Bettina Warscheid (2011) Cytoscape: Software for Visualization and Analysis of Biological Networks. In: Michael Hamacher et al. (eds.), Data Mining in Proteomics: From Standards to Applications, Methods in Molecular Biology, vol. 696, DOI 10.1007 / 978-1-60761-987-1_18
  31. ↑ Raman, K. Construction and analysis of protein-protein interaction networks. (eng.) // Automated experimentation: journal. - 2010. - Vol. 2 , no. 1 . - P. 2 . - PMID 20334628 .
  32. ↑ Rivas, M .; Villar, D .; González, P .; Dopazo, XM; Mellstrom, B .; Naranjo, JR Building the DREAM interactome. (Neopr.) // Science China. Life sciences. - 2011. - Vol. 54 , No. 8 . - p . 786-792 . - PMID 21786202 .
  33. ↑ Esteves, SL; Domingues, SC; da Cruz e Silva, OA; Fardilha, M .; da Cruz e Silva, EF Protein phosphatase 1α interacting proteins in the human brain. (Eng.) // Omics: a journal of integrative biology: journal. - 2012. - Vol. 16 , no. 1-2 . - P. 3-17 . - PMID 22321011 .

Links

  • Stark, C. "BioGRID: a general repository for interaction datasets" (eng.) . http://www.thebiogrid.org . Nucleic Acids Res (2006). - Biological General Repository for Interaction Datasets (BioGRID). The appeal date is May 13, 2017.
  • Peri, S. "Human protein reference database for a discovery resource for proteomics" (eng.) . http://www.hprd.org . Nucleic Acids Res (2004). - Human Portein Reference Database (HPRD). The appeal date is May 13, 2017.
  • Hermjakob, H. "IntAct: an open source molecular interaction database" (Eng.) . http://www.ebi.ac.uk/intact . Nucleic Acids Res (2004). - IntAct Molecular Interaction Database. The appeal date is May 13, 2017.
  • Chatr-aryamontri, A. "MINT: the Molecular INTeraction database" (Eng.) . http://mint.bio.uniroma2.it/mint/ . Nucleic Acids Res (2007). - Molecular Interactions Database (MINT). The appeal date is May 13, 2017.
Source - https://ru.wikipedia.org/w/index.php?title= Protein - protein interactions&oldid = 100996341


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