Abstract
We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.
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References
Shoemaker BA, Panchenko AR, Bryant SH (2006) Finding biologically relevant protein domain interactions: conserved binding mode analysis. Protein Sci 15(2):352–361
Aloy P, Russell RB (2004) Ten thousand interactions for the molecular biologist. Nat Biotechnol 22(10):1317–1321
Rolland T, Tasan M, Charloteaux B et al (2014) A proteome-scale map of the human interactome network. Cell 159(5):1212–1226
Yates CM, Sternberg MJ (2013) The effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on protein-protein interactions. J Mol Biol 425(21):3949–3963
Teng S, Madej T, Panchenko A, Alexov E (2009) Modeling effects of human single nucleotide polymorphisms on protein-protein interactions. Biophys J 96(6):2178–2188
Li M, Goncearenco A, Panchenko AR (2017) Annotating mutational effects on proteins and protein interactions: designing novel and revisiting existing protocols. Methods Mol Biol 1550:235–260
Filippakopoulos P, Qi J, Picaud S et al (2010) Selective inhibition of BET bromodomains. Nature 468(7327):1067–1073
Smith BJ, Lee EF, Checco JW et al (2013) Structure-guided rational design of alpha/beta-peptide foldamers with high affinity for BCL-2 family prosurvival proteins. Chembiochem 14(13):1564–1572
Zhao Y, Aguilar A, Bernard D, Wang S (2015) Small-molecule inhibitors of the MDM2-p53 protein-protein interaction (MDM2 Inhibitors) in clinical trials for cancer treatment. J Med Chem 58(3):1038–1052
Haase HS, Peterson-Kaufman KJ, Lan Levengood SK et al (2012) Extending foldamer design beyond alpha-helix mimicry: alpha/beta-peptide inhibitors of vascular endothelial growth factor signaling. J Am Chem Soc 134(18):7652–7655
Basse MJ, Betzi S, Morelli X, Roche P (2016) 2P2Idb v2: update of a structural database dedicated to orthosteric modulation of protein-protein interactions. Database (Oxford) 2016
Aloy P, Ceulemans H, Stark A, Russell RB (2003) The relationship between sequence and interaction divergence in proteins. J Mol Biol 332(5):989–998
Ma B, Elkayam T, Wolfson H, Nussinov R (2003) Protein-protein interactions: structurally conserved residues distinguish between binding sites and exposed protein surfaces. Proc Natl Acad Sci U S A 100(10):5772–5777
Valdar WS, Thornton JM (2001) Protein-protein interfaces: analysis of amino acid conservation in homodimers. Proteins 42(1):108–124
Guharoy M, Chakrabarti P (2005) Conservation and relative importance of residues across protein-protein interfaces. Proc Natl Acad Sci U S A 102(43):15447–15452
Goncearenco A, Shaytan AK, Shoemaker BA, Panchenko AR (2015) Structural perspectives on the evolutionary expansion of unique protein-protein binding sites. Biophys J 109(6):1295–1306
Goncearenco A, Shoemaker BA, Zhang D et al (2014) Coverage of protein domain families with structural protein-protein interactions: current progress and future trends. Prog Biophys Mol Biol 116(2–3):187–193
Petrey D, Honig B (2014) Structural bioinformatics of the interactome. Annu Rev Biophys 43:193–210
Mosca R, Ceol A, Aloy P (2013) Interactome3D: adding structural details to protein networks. Nat Methods 10(1):47–53
Tyagi M, Hashimoto K, Shoemaker BA et al (2012) Large-scale mapping of human protein interactome using structural complexes. EMBO Rep 13(3):266–271
Shoemaker BA, Zhang D, Thangudu RR et al (2010) Inferred Biomolecular Interaction Server—a web server to analyze and predict protein interacting partners and binding sites. Nucleic Acids Res 38(Database issue):D518–D524
Shoemaker BA, Zhang D, Tyagi M et al (2012) IBIS (Inferred Biomolecular Interaction Server) reports, predicts and integrates multiple types of conserved interactions for proteins. Nucleic Acids Res 40(Database issue):D834–D840
Kim S, Thiessen PA, Bolton EE et al (2016) PubChem Substance and Compound databases. Nucleic Acids Res 44(D1):D1202–D1213
Wang Y, Bryant SH, Cheng T (2017) PubChem BioAssay: 2017 update. Nucleic Acids Res 45(D1):D955–D963
Li M, Simonetti FL, Goncearenco A, Panchenko AR (2016) MutaBind estimates and interprets the effects of sequence variants on protein-protein interactions. Nucleic Acids Res 44(W1):W494–W501
Li M, Petukh M, Alexov E, Panchenko AR (2014) Predicting the impact of missense mutations on protein? Protein binding affinity. J Chem Theor Comput 10(4):1770–1780
Yang W, Soares J, Greninger P (2013) Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res 41(Database issue):D955–D961
Gilson MK, Liu T, Baitaluk M, Nicola G et al (2016) BindingDB in 2015: a public database for medicinal chemistry, computational chemistry and systems pharmacology. Nucleic Acids Res 44(D1):D1045–D1053
Petukh M, Dai L, Alexov E (2016) SAAMBE: webserver to predict the charge of binding free energy caused by amino acids mutations. Int J Mol Sci 17(4):547
Cukuroglu E, Gursoy A, Keskin O (2012) HotRegion: a database of predicted hot spot clusters. Nucleic Acids Res 40(Database issue):D829–D833
Estrada-Ortiz N, Neochoritis CG, Domling A (2016) How to design a successful p53-MDM2/X interaction inhibitor: a thorough overview based on crystal structures. ChemMedChem 11(8):757–772
Shangary S, Wang S (2009) Small-molecule inhibitors of the MDM2-p53 protein-protein interaction to reactivate p53 function: a novel approach for cancer therapy. Annu Rev Pharmacol Toxicol 49:223–241
Cinatl J, Speidel D, Hardcastle I, Michaelis M (2014) Resistance acquisition to MDM2 inhibitors. Biochem Soc Trans 42(4):752–757
Thangudu RR, Bryant SH, Panchenko AR, Madej T (2012) Modulating protein-protein interactions with small molecules: the importance of binding hotspots. J Mol Biol 415(2):443–453
Davis FP, Sali A (2010) The overlap of small molecule and protein binding sites within families of protein structures. PLoS Comput Biol 6(2):e1000668
Marchler-Bauer A, Derbyshire MK, Gonzales NR et al (2015) CDD: NCBI’s conserved domain database. Nucleic Acids Res 43(D1):D222–D226
Wells JA, McClendon CL (2007) Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 450(7172):1001–1009
Bogan AA, Thorn KS (1998) Anatomy of hot spots in protein interfaces. J Mol Biol 280(1):1–9
Graves B, Thompson T, Xia M, Janson C (2012) Activation of the p53 pathway by small-molecule-induced MDM2 and MDMX dimerization. Proc Natl Acad Sci U S A 109(29):11788–11793
Ribeiro CJ, Rodrigues CM, Moreira R, Santos MM (2016) Chemical variations on the p53 reactivation theme. Pharmaceuticals (Basel) 9(2)
Perez-Sanchez H, Rezaei V, Mezhuyev V et al (2016) Developing science gateways for drug discovery in a grid environment. Spring 5(1):1300
Beisken S, Meinl T, Wiswedel B et al (2013) KNIME-CDK: workflow-driven cheminformatics. BMC Bioinformatics 14:257
Truszkowski A, Jayaseelan KV, Neumann S et al (2011) New developments on the cheminformatics open workflow environment CDK-Taverna. J Cheminform 3:54
Mazanetz MP, Marmon RJ, Reisser CB, Morao I (2012) Drug discovery applications for KNIME: an open source data mining platform. Curr Top Med Chem 12(18):1965–1979
Nicola G, Berthold MR, Hedrick MP, Gilson MK (2015) Connecting proteins with drug-like compounds: open source drug discovery workflows with BindingDB and KNIME. Database (Oxford) 2015
Wolstencroft K, Haines R, Fellows D et al (2013) The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud. Nucleic Acids Res 41(Web Server issue):W557–W561
Goble CA, Bhagat J, Aleksejevs S et al (2010) myExperiment: a repository and social network for the sharing of bioinformatics workflows. Nucleic Acids Res 38(Web Server issue):W677–W682
Bhagat J, Tanoh F, Nzuobontane E et al (2010) BioCatalogue: a universal catalogue of web services for the life sciences. Nucleic Acids Res 38(Web Server):W689–W694
Acknowledgments
This work was supported by the Intramural Research Program of the National Library of Medicine. We thank Sunghwan Kim for helpful discussions about PubChem.
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Goncearenco, A., Li, M., Simonetti, F.L., Shoemaker, B.A., Panchenko, A.R. (2017). Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows. In: Lazar, I., Kontoyianni, M., Lazar, A. (eds) Proteomics for Drug Discovery. Methods in Molecular Biology, vol 1647. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7201-2_15
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DOI: https://doi.org/10.1007/978-1-4939-7201-2_15
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