Abstract
Protein-protein interaction leads to stable interface for specific biochemical or regulatory function. This is accompanied by binding free energy at the interface between interacting proteins. High energy interface residues are referred as hot spots. They have critical role in protein-protein binding. Hot spots participate in strong and energetically favorable side chain-side chain interactions. They help to efficiently distinguish specific from non-specific protein-protein interactions. We document some basic information on hot spots in the context of protein-protein interactions.
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References
Gao Y, Wang R, Lai L. Structure-based method for analyzing protein-protein interfaces. J Mol Model. 2004;10(1):44–54.
Thorn KS, Bogan AA. ASEdb: a database of alanine mutations and their effects on the free energy of binding in protein interactions. Bioinformatics. 2001;17(3):284–5.
Li L, Zhao B, Cui Z, Gan J, Sakharkar MK, Kangueane P. Identification of hot spot residues at protein-protein interface. Bioinformation. 2006;1(4):121–6.
Sobolev V, Wade RC, Vriend G, Edelman M. Molecular docking using surface complementarity. Proteins. 1996;25(1):120–9.
Segura J, Fernandez-Fuentes N. PCRPi-DB: a database of computationally annotated hot spots in protein interfaces. Nucleic Acids Res. 2011;39(Database issue):D755–60.
Guney E, Tuncbag N, Keskin O, Gursoy A. HotSprint: database of computational hot spots in protein interfaces. Nucleic Acids Res. 2008;36(Database issue):D662–6.
Fischer TB, Arunachalam KV, Bailey D, Mangual V, Bakhru S, Russo R, et al. The binding interface database (BID): a compilation of amino acid hot spots in protein interfaces. Bioinformatics. 2003;19(11):1453–4.
Xia JF, Zhao XM, Song J, Huang DSAPIS. Accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility. BMC Bioinform. 2010;11:174.
Chen R, Zhang Z, Wu D, Zhang P, Zhang X, Wang Y, et al. Prediction of protein interaction hot spots using rough set-based multiple criteria linear programming. J Theor Biol. 2011;269(1):174–80.
Li Z, Wong L, Li J. DBAC: a simple prediction method for protein binding hot spots based on burial levels and deeply buried atomic contacts. BMC Syst Biol. 2011;5(Suppl 1): S5.
Wang L, Liu ZP, Zhang XS, Chen L. Prediction of hot spots in protein interfaces using a random forest model with hybrid features. Protein Eng Des Sel. 2012;25(3):119–26.
Deng L, Guan J, Wei X, Yi Y, Zhang QC, Zhou S. Boosting prediction performance of protein-protein interaction hot spots by using structural neighborhood properties. J Comput Biol. 2013;20(11):878–91.
Wang L, Zhang W, Gao Q, Xiong C. Prediction of hot spots in protein interfaces using extreme learning machines with the information of spatial neighbor residues. IET Syst Biol. 2014;8(4):184–90.
SS H, Chen P, Wang B, Li J. Protein binding hot spots prediction from sequence only by a new ensemble learning method. Amino Acids. 2017;
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Exercises
Exercises
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1.
Define protein interface hot spots.
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2.
Illustrate favorable contacts using an example.
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3.
Illustrate side chain-side chain interaction mean distribution at the interface.
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4.
Name some hot spots database.
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5.
Name some hot spot prediction models.
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6.
Discuss improvements in hot spot prediction.
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7.
Expand ASEdb.
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8.
What are the energy range for hot spots, warm residues, and unimportant residues?
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9.
State the atom level chemical properties used to describe favorable contacts.
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10.
Illustrate interatomic favorable and unfavorable contacts in matrix format.
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Kangueane, P., Nilofer, C. (2018). Hot Spots at the Protein-Protein Interface. In: Protein-Protein and Domain-Domain Interactions. Springer, Singapore. https://doi.org/10.1007/978-981-10-7347-2_7
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DOI: https://doi.org/10.1007/978-981-10-7347-2_7
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