Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Overview of Protein-Protein Interactions and Small-Molecule Inhibitors Under Clinical Development Read chapter Read first chapter

2018 | OriginalPaper | Chapter

3. Hot Spot-Based Design of Small-Molecule Inhibitors for Protein-Protein Interactions

Author : Haitao Ji

Published in: Targeting Protein-Protein Interactions by Small Molecules

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Protein-protein interactions (PPIs) are important targets for the development of chemical probes and therapeutic agents. From the initial discovery of the existence of hot spots at PPI interfaces, it has been proposed that hot spots might provide the key for developing small-molecule PPI inhibitors. However, there has been no review on the ways in which the knowledge of hot spots can be used to achieve inhibitor design, nor critical examination of successful examples. This chapter discusses the characteristics of hot spots and the identification of druggable hot spot pockets. An analysis of four examples of hot spot-based design reveals the importance of this strategy in discovering potent and selective PPI inhibitors. A general procedure for hot spot-based design of PPI inhibitors is outlined.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
previous chapter High-Throughput Screening in the Discovery of Small-Molecule Inhibitors of Protein-Protein Interactions
next chapter Computational Methods Applicable to the Discovery of Small-Molecule Inhibitors of Protein-Protein Interactions
Literature
1.
Lo Conte L, Chothia C, Janin J (1999) The atomic structure of protein–protein recognition sites. J Mol Biol 285(5):2177–2198CrossRefPubMed
2.
Arkin MR, Wells JA (2004) Small-molecule inhibitors of protein-protein interactions: progressing towards the dream. Nat Rev Drug Discov 3(4):301–317CrossRefPubMed
3.
Wells JA, McClendon CL (2007) Reaching for high-hanging fruit in drug discovery at protein–protein interfaces. Nature 450(7172):1001–1009CrossRefPubMed
4.
Keskin O, Gursoy A, Ma B, Nussinov R (2008) Principles of protein-protein interactions: what are the preferred ways for proteins to interact? Chem Rev 108(4):1225–1244CrossRefPubMed
5.
Clackson T, Wells JA (1995) A hot spot of binding energy in a hormone-receptor interface. Science 267(5196):383–386CrossRefPubMed
6.
Bogan AA, Thorn KS (1998) Anatomy of hot spots in protein interfaces. J Mol Biol 280(1):1–9. doi:
7.
Hu Z, Ma B, Wolfson H, Nussinov R (2000) Conservation of polar residues as hot spots at protein interfaces. Proteins 39(4):331–342CrossRefPubMed
8.
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 USA 100(10):5772–5777CrossRefPubMed
9.
Carbonell P, Nussinov R, del Sol A (2009) Energetic determinants of protein binding specificity: insights into protein interaction networks. Proteomics 9(7):1744–1753CrossRefPubMed
10.
Keskin O, Ma B, Nussinov R (2005) Hot regions in protein–protein interactions: the organization and contribution of structurally conserved hot spot residues. J Mol Biol 345(5):1281–1294CrossRefPubMed
11.
Guo W, Wisniewski JA, Ji H (2014) Hot spot-based design of small-molecule inhibitors for protein–protein interactions. Bioorg Med Chem Lett 24(11):2546–2554CrossRefPubMed
12.
Reichmann D, Rahat O, Albeck S, Meged R, Dym O, Schreiber G (2005) The modular architecture of protein–protein binding interfaces. Proc Natl Acad Sci USA 102(1):57–62CrossRefPubMed
13.
Moza B, Buonpane RA, Zhu P, Herfst CA, Rahman AKMN-u, McCormick JK, Kranz, DM, Sundberg EJ (2006) Long-range cooperative binding effects in a T cell receptor variable domain. Proc Natl Acad Sci USA 103(26):9867–9872CrossRef
14.
Golden MS, Cote SM, Sayeg M, Zerbe BS, Villar EA, Beglov D, Sazinsky SL, Georgiadis RM, Vajda S, Kozakov D, Whitty A (2013) Comprehensive experimental and computational analysis of binding energy hot spots at the NF-κB essential modulator/IKKβ protein–protein interface. J Am Chem Soc 135(16):6242–6256CrossRefPubMedPubMedCentral
15.
Rajamani D, Thiel S, Vajda S, Camacho CJ (2004) Anchor residues in protein–protein interactions. Proc Natl Acad Sci USA 101(31):11287–11292CrossRefPubMed
16.
Meireles LMC, Dömling AS, Camacho CJ (2010) ANCHOR: a web server and database for analysis of protein–protein interaction binding pockets for drug discovery. Nucleic Acids Res 38:W407–W411CrossRefPubMedPubMedCentral
17.
Li X, Keskin O, Ma B, Nussinov R, Liang J (2004) Protein–protein interactions: hot spots and structurally conserved residues often locate in complemented pockets that pre-organized in the unbound states: implications for docking. J Mol Biol 344(3):781–795CrossRefPubMed
18.
19.
Kortemme T, Baker D (2002) A simple physical model for binding energy hot spots in protein–protein complexes. Proc Natl Acad Sci USA 99(22):14116–14121CrossRefPubMed
20.
Guerois R, Nielsen JE, Serrano L (2002) Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. J Mol Biol 320(2):369–387CrossRefPubMed
21.
Massova I, Kollman PA (1999) Computational alanine scanning to probe protein–protein interactions: a novel approach to evaluate binding free energies. J Am Chem Soc 121(36):8133–8143CrossRef
22.
Moreira IS, Fernandes PA, Ramos MJ (2007) Computational alanine scanning mutagenesis–an improved methodological approach. J Comput Chem 28(3):644–654CrossRefPubMed
23.
24.
Tuncbag N, Gursoy A, Keskin O (2009) Identification of computational hot spots in protein interfaces: combining solvent accessibility and inter-residue potentials improves the accuracy. Bioinformatics 25(12):1513–1520CrossRefPubMed
25.
26.
Xia J-F, Zhao X-M, Song J, Huang D-S (2010) APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility. BMC Bioinform 11:174CrossRef
27.
Zhu X, Mitchell JC (2011) KFC2: a knowledge-based hot spot prediction method based on interface solvation, atomic density, and plasticity features. Proteins 79(9):2671–2683CrossRefPubMed
28.
Masso M, Vaisman II (2008) Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis. Bioinformatics 24(18):2002–2009CrossRefPubMed
29.
Lise S, Archambeau C, Pontil M, Jones DT (2009) Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods. BMC Bioinform 10:365CrossRef
30.
Li J, Liu Q (2009) ‘Double water exclusion’: a hypothesis refining the O-ring theory for the hot spots at protein interfaces. Bioinformatics 25(6):743–750CrossRefPubMedPubMedCentral
31.
Liu Q, Li J (2010) Protein binding hot spots and the residue-residue pairing preference: a water exclusion perspective. BMC Bioinform 11:244CrossRef
32.
Moreira IS, Fernandes PA, Ramos MJ (2007) Hot spot occlusion from bulk water: a comprehensive study of the complex between the lysozyme HEL and the antibody FVD1.3. J Phys Chem B 111(10):2697–2706CrossRefPubMed
33.
Moreira IS, Ramos RM, Martins JM, Fernandes PA, Ramos MJ (2014) Are hot-spots occluded from water? J Biomol Struct Dyn 32(2):186–197CrossRefPubMed
34.
Li Z, Li J (2010) Geometrically centered region: a “wet” model of protein binding hot spots not excluding water molecules. Proteins 78(16):3304–3316CrossRefPubMed
35.
Fuller JC, Burgoyne NJ, Jackson RM (2009) Predicting druggable binding sites at the protein–protein interface. Drug Discov Today 14(3–4):155–161CrossRefPubMed
36.
Mattos C, Ringe D (1996) Locating and characterizing binding sites on proteins. Nat Biotechnol 14(5):595–599CrossRefPubMed
37.
Shuker SB, Hajduk PJ, Meadows RP, Fesik SW (1996) Discovering high-affinity ligands for proteins: SAR by NMR. Science 274(5292):1531–1534CrossRefPubMed
38.
Congreve M, Carr R, Murray C, Jhoti H (2003) A ‘rule of three’ for fragment base discovery. Drug Discov Today 8(19):876–877CrossRefPubMed
39.
DeLano WL, Ultsch MH, de Vos AM, Wells JA (2000) Convergent solutions to binding at a protein–protein interface. Science 287(5456):1279–1283CrossRefPubMed
40.
Zerbe BS, Hall DR, Vajda S, Whitty A, Kozakov D (2012) Relationship between hot spot residues and ligand binding hot spots in protein–protein interfaces. J Chem Inf Model 52(8):2236–2344CrossRefPubMedPubMedCentral
41.
Brenke R, Kozakov D, Chuang G-Y, Beglov D, Hall D, Landon MR, Mattos C, Vajda S (2009) Fragment-based identification of druggable ‘hot spots’ of proteins using Fourier domain correlation techniques. Bioinformatics 25(5):621–627CrossRefPubMedPubMedCentral
42.
Buhrman G, O’Connor C, Zerbe B, Kearney BM, Napoleon R, Kovrigina EA, Vajda S, Kozakov D, Kovrigin EL, Mattos C (2011) Analysis of binding site hot spots on the surface of Ras GTPase. J Mol Biol 413(4):773–789CrossRefPubMedPubMedCentral
43.
Hall DH, Grove LE, Yueh C, Ngan CH, Kozakov D, Vajda S (2011) Robust identification of binding hot spots using continuum electrostatics: application to hen egg-white lysozyme. J Am Chem Soc 133(51):20668–20671CrossRefPubMedPubMedCentral
44.
Winter A, Higueruelo AP, Marsh M, Sigurdardottir A, Pitt WR, Blundell TL (2012) Biophysical and computational fragment-based approaches to targeting protein–protein interactions: applications in structure-guided drug discovery. Q Rev Biophys 45(4):383–426CrossRefPubMed
45.
Erlanson DA, Braisted AC, Raphael DR, Randal M, Stroud RM, Gordon EM, Wells JA (2000) Site-directed ligand discovery. Proc Natl Acad Sci USA 97(17):9367–9372CrossRefPubMed
46.
Braisted AC, Oslob JD, Delano WL, Hyde J, McDowell RS, Waal N, Yu C, Arkin MR, Raimundo BC (2003) Discovery of a potent small molecule IL-2 inhibitor through fragment assembly. J Am Chem Soc 125(13):3714–3715CrossRefPubMed
47.
Scott DE, Ehebauer MT, Pukala T, Marsh M, Blundell TL, Venkitaraman AR, Abell C, Hyvönen M (2013) Using a fragment-based approach to target protein–protein interactions. ChemBioChem 14(3):332–342CrossRefPubMedPubMedCentral
48.
Mikuni J, Kato M, Taruya S, Tsuganezawa K, Mori M, Ogawa N, Honma T, Yokoyama S, Kojima H, Okabe T, Nagano T, Tanaka A (2010) A fluorescence correlation spectroscopy-based assay for fragment screening of slowly inhibiting protein-peptide interaction inhibitors. Anal Biochem 402(1):26–31CrossRefPubMed
49.
Davis BJ, Erlanson DA (2013) Learning from our mistakes: the ‘unknown knowns’ in fragment screening. Bioorg Med Chem Lett 23(10):2844–2852CrossRefPubMed
50.
Oltersdorf T, Elmore SW, Shoemaker AR, Armstrong RC, Augeri DJ, Belli BA, Bruncko M, Deckwerth TL, Dinges J, Hajduk PJ, Joseph MK, Kitada S, Korsmeyer SJ, Kunzer AR, Letai A, Li C, Mitten MJ, Nettesheim DG, Ng S, Nimmer PM, O’Connor JM, Oleksijew A, Petros AM, Reed JC, Shen W, Tahir SK, Thompson CB, Tomaselli KJ, Wang B, Wendt MD, Zhang H, Fesik SW, Rosenberg SH (2005) An inhibitor of Bcl-2 family proteins induces regression of solid tumours. Nature 435(7042):677–681CrossRefPubMed
51.
He MM, Smith AS, Oslob JD, Flanagan WM, Braisted AC, Whitty A, Cancilla MT, Wang J, Lugovskoy AA, Yoburn JC, Fung AD, Farrington G, Eldredge JK, Day ES, Cruz LA, Cachero TG, Miller SK, Friedman JE, Choong IC, Cunningham BC (2005) Small-molecule inhibition of TNF-α. Science 310(5750):1022–1025CrossRefPubMed
52.
Geppert T, Bauer S, Hiss JA, Conrad E, Reutlinger M, Schneider P, Weisel M, Pfeiffer B, Altmann K-H, Waibler Z, Schneider G (2012) Immunosuppressive small molecule discovered by structure-based virtual screening for inhibitors of protein–protein interactions. Angew Chem Int Ed 51(1):258–261CrossRef
53.
Petros AM, Dinges J, Augeri DJ, Baumeister SA, Betebenner DA, Bures MG, Elmore SW, Hajduk PJ, Joseph MK, Landis SK, Nettesheim DG, Rosenberg SH, Shen W, Thomas S, Wang X, Zanze I, Zhang H, Fesik SW (2006) Discovery of a potent inhibitor of the antiapoptotic protein Bcl-xL from NMR and parallel synthesis. J Med Chem 49(2):656–663CrossRefPubMed
54.
Wendt MD, Shen W, Kunzer A, McClellan WJ, Bruncko M, Oost TK, Ding H, Joseph MK, Zhang H, Nimmer PM, Ng S-C, Shoemaker AR, Petros AM, Oleksijew A, Marsh K, Bauch J, Oltersdorf T, Belli BA, Martineau D, Fesik SW, Rosenberg SH, Elmore SW (2006) Discovery and structure-activity relationship of antagonists of B-cell lymphoma 2 family proteins with chemopotentiation activity in vitro and in vivo. J Med Chem 49(3):1165–1181CrossRefPubMed
55.
Bruncko M, Oost TK, Belli BA, Ding H, Joseph MK, Kunzer A, Martineau D, McClellan WJ, Mitten M, Ng S-C, Nimmer PM, Oltersdorf T, Park C-M, Petros AM, Shoemaker AR, Song X, Wang X, Wendt MD, Zhang H, Fesik SW, Rosenberg SH, Elmore SW (2007) Studies leading to potent, dual inhibitors of Bcl-2 and Bcl-xL. J Med Chem 50(4):641–662CrossRefPubMed
56.
Park C-M, Bruncko M, Adickes J, Bauch J, Ding H, Kunzer A, Marsh KC, Nimmer P, Shoemaker AR, Song X, Tahir SK, Tse C, Wang X, Wendt MD, Yang X, Zhang H, Fesik SW, Rosenberg SH, Elmore SW (2008) Discovery of an orally bioavailable small molecule inhibitor of prosurvival B-cell lymphoma 2 proteins. J Med Chem 51(21):6902–6915CrossRefPubMed
57.
Hopkins AL, Groom CR, Alex A (2004) Ligand efficiency: a useful metric for lead selection. Drug Discov Today 9(10):430–431CrossRefPubMed
58.
Hajduk PJ, Huth JR, Fesik SW (2005) Druggability indices for protein targets derived from NMR-based screening data. J Med Chem 48(7):2518–2525CrossRefPubMed
59.
Cheng AC, Coleman RG, Smyth KT, Cao Q, Soulard P, Caffrey DR, Salzberg AC, Huang ES (2007) Structure-based maximal affinity model predicts small-molecule druggability. Nat Biotechnol 25(1):71–75CrossRefPubMed
60.
Schmidtke P, Barril X (2010) Understanding and predicting druggability. A high-throughput method for detection of drug binding sites. J Med Chem 53(15):5858–5867CrossRefPubMed
61.
Pettit FK, Bowie JU (1999) Protein surface roughness and small molecular binding sites. J Mol Biol 285(4):1377–1382CrossRefPubMed
62.
Soga S, Shirai H, Kobori M, Hirayama N (2007) Use of amino acid composition to predict ligand-binding sites. J Chem Inf Model 47(2):400–406CrossRefPubMed
63.
Li Y, Liu Z, Han L, Li C, Wang R (2013) Mining the characteristic interaction patterns on protein–protein binding interfaces. J Chem Inf Model 53(9):2437–2447CrossRefPubMed
64.
Metz A, Pfleger C, Kopitz H, Pfeiffer-Marek S, Baringhaus K-H, Gohlke H (2012) Hot spots and transient pockets: predicting the determinants of small-molecule binding to a protein–protein interface. J Chem Inf Model 52(1):120–133CrossRefPubMed
65.
Eyrisch S, Helms V (2007) Transient pockets on protein surfaces involved in protein–protein interaction. J Med Chem 50(15):3457–3464CrossRefPubMed
66.
Johnson DK, Karanicolas J (2013) Druggable protein interaction sites are more predisposed to surface pocket formation than the rest of the protein surface. PLoS Comput Biol 9(3):e1002951CrossRefPubMedPubMedCentral
67.
Kozakov D, Hall DR, Chuang G-Y, Cencic R, Brenke R, Grove LE, Beglov D, Pelletier J, Whitty A, Vajda S (2011) Structural conservation of druggable hot spots in protein–protein interfaces. Proc Natl Acad Sci USA 108(33):13528–13533CrossRefPubMed
68.
Ding K, Lu Y, Nikolovska-Coleska Z, Qiu S, Ding Y, Gao W, Stuckey J, Krajewski K, Roller PP, Tomita Y, Parrish DA, Deschamps JR, Wang S (2005) Structure-based design of potent non-peptide MDM2 inhibitors. J Am Chem Soc 127(29):10130–10131CrossRefPubMed
69.
Ding K, Lu Y, Nikolovska-Coleska Z, Wang G, Qiu S, Shangary S, Gao W, Qin D, Stuckey J, Krajewski K, Roller PP, Wang S (2006) Structure-based design of spiro-oxindoles as potent, specific small-molecule inhibitors of the MDM2–p53 interaction. J Med Chem 49(12):3432–3435CrossRefPubMed
70.
Shangary S, Qin D, McEachern D, Liu M, Miller RS, Qiu S, Nikolovska-Coleska Z, Ding K, Wang G, Chen J, Bernard D, Zhang J, Lu Y, Gu Q, Shah RB, Pienta KJ, Ling X, Kang S, Guo M, Sun Y, Yang D, Wang S (2008) Temporal activation of p53 by a specific MDM2 inhibitor is selectively toxic to tumors and leads to complete tumor growth inhibition. Proc Natl Acad Sci USA 105(10):3933–3938CrossRefPubMed
71.
Zhao Y, Liu L, Sun W, Lu J, McEachern D, Li X, Yu S, Bernard D, Ochsenbein P, Ferey V, Carry J-C, Deschamps JR, Sun D, Wang S (2013) Diastereomeric spirooxindoles as highly potent and efficacious MDM2 inhibitors. J Am Chem Soc 135(19):7223–7234CrossRefPubMedPubMedCentral
72.
Zhao Y, Yu S, Sun W, Liu L, Lu J, McEachern D, Shargary S, Bernard D, Li X, Zhao T, Zou P, Sun D, Wang S (2013) A potent small-molecule inhibitor of the MDM2–p53 interaction (MI-888) achieved complete and durable tumor regression in mice. J Med Chem 56(13):5553–5561CrossRefPubMed
73.
Czarna A, Beck B, Srivastava S, Popowicz GM, Wolf S, Huang Y, Bista M, Holak TA, Dömling A (2010) Robust generation of lead compounds for protein–protein interactions by computational and MCR chemistry: p53/Hdm2 antagonists. Angew Chem Int Ed 49(31):5352–5356CrossRef
74.
Popowicz GM, Czarna A, Wolf S, Wang K, Wang W, Dömling A, Holak TA (2010) Structures of low molecular weight inhibitors bound to MDMX and MDM2 reveal new approaches for p53-MDMX/MDM2 antagonist drug discovery. Cell Cycle 9(6):1104–1111CrossRefPubMed
75.
Koes D, Khoury K, Huang Y, Wang W, Bista M, Popowicz GM, Wolf S, Holak TA, Dömling A, Camacho CJ (2012) Enabling large-scale design, synthesis and validation of small molecule protein–protein antagonists. PLoS ONE 7(3):e32839CrossRefPubMedPubMedCentral
76.
Huang Y, Wolf S, Beck B, Köhler L-M, Khoury K, Popowicz GM, Goda SK, Subklewe M, Twarda A, Holak TA, Dömling A (2014) Discovery of highly potent p53-MDM2 antagonists and structural basis for anti-acute myeloid leukemia activities. ACS Chem Biol 9(3):802–811CrossRefPubMedPubMedCentral
77.
Huang Y, Wolf S, Koes D, Popowicz GM, Camacho CJ, Holak TA, Dömling A (2012) Exhaustive fluorine scanning toward potent p53–Mdm2 antagonists. ChemMedChem 7(1):49–52CrossRefPubMed
78.
Bista M, Wolf S, Khoury K, Kowalska K, Huang Y, Wrona E, Arciniega M, Popowicz GM, Holak TA, Dömling A (2013) Transient protein states in designing inhibitors of the MDM2–p53 interaction. Structure 21(12):2143–2151CrossRefPubMedPubMedCentral
79.
Buckley DL, Van Molle I, Gareiss PC, Tae HS, Michel J, Noblin DJ, Jorgensen WL, Ciulli A, Crews CM (2012) Targeting the von Hippel-Lindau E3 ubiquitin ligase using small molecules to disrupt the VHL/HIF-1α interaction. J Am Chem Soc 134(10):4465–4468CrossRefPubMedPubMedCentral
80.
Van Molle I, Thomann A, Buckley DL, So EC, Lang S, Crews CM, Ciulli A (2012) Dissecting fragment-based lead discovery at the von Hippel-Lindau protein:hypoxia inducible factor 1α protein–protein interface. Chem Biol 19(10):1300–1312CrossRefPubMedPubMedCentral
81.
82.
Buckley DL, Gustafson JL, Van Molle I, Roth AG, Tae HS, Gareiss PC, Jorgensen WL, Ciulli A, Crews CM (2012) Small-molecule inhibitors of the interaction between the E3 ligase VHL and HIF1α. Angew Chem Int Ed 51(46):11463–11467CrossRef
83.
Ji H, Stanton BZ, Igarashi J, Li H, Martásek P, Roman LJ, Poulos TL, Silverman RB (2008) Minimal pharmacophoric elements and fragment hopping, an approach directed at molecular diversity and isozyme selectivity. Design of selective neuronal nitric oxide synthase inhibitors. J Am Chem Soc 130(12):3900–3914CrossRefPubMedPubMedCentral
84.
Ji H, Li H, Martásek P, Roman LJ, Poulos TL, Silverman RB (2009) Discovery of highly potent and selective inhibitors of neuronal nitric oxide synthase by fragment hopping. J Med Chem 52(3):779–797CrossRefPubMedPubMedCentral
85.
86.
Yu B, Huang Z, Zhang M, Dillard DR, Ji H (2013) Rational design of small-molecule inhibitors for β-catenin/T-cell factor protein–protein interactions by bioisostere replacement. ACS Chem Biol 8(3):524–529CrossRefPubMed
87.
Reynès C, Host H, Camproux A-C, Laconde G, Leroux F, Mazars A, Deprez B, Fahraeus R, Villoutreix BO, Sperandio O (2010) Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods. PLoS Comput Biol 6(3):e1000695CrossRefPubMedPubMedCentral
88.
Hamon V, Brunel JM, Combes S, Basse MJ, Roche P, Morelli X (2013) 2P2Ichem: focused chemical libraries dedicated to orthosteric modulation of protein–protein interactions. MedChemComm 4(5):797–809CrossRef
89.
Smith MC, Gestwicki JE (2012) Features of protein-protein interactions that translate into potent inhibitors: topology, surface area and affinity. Expert Rev Mol Med 14:e16CrossRefPubMedPubMedCentral
90.
Cesa LC, Patury S, Komiyama T, Ahmad A, Zuiderweg ERP, Gestwicki JE (2013) Inhibitors of difficult protein-protein interactions identified by high-throughput screening of multiprotein complexes. ACS Chem Biol 8(9):1988–1997CrossRefPubMedPubMedCentral
91.
(a) Venkatesan K, Rual J-F, Vazquez A, Stelzl U, Lemmens I, Hirozane-Kishikawa T, Hao T, Zenkner M, Xin X, Goh K-I, Yildirim MA, Simonis N, Heinzmann K, Gebreab F, Sahalie JM, Cevik S, Simon C, de Smet A-S, Dann E, Smolyar A, Vinayagam A, Yu H, Szeto D, Borick H, Dricot A, Klitgord N, Murray RR, Lin C, Lalowski M, Timm J, Rau K, Boone C, Braun P, Cusick ME, Roth FP, Hill DE, Tavernier J, Wanker EE, Barabási A-L, Vidal M (2009) An empirical framework for binary interactome mapping. Nat Methods 6(1):83–90; (b) Zhang QC, Petrey D, Deng L, Qiang L, Shi Y, Thu CA, Bisikirska B, Lefebvre C, Accili D, Hunter T, Maniatis T, Califano A, Honig B (2012) Structure-based prediction of protein-protein interactions on a genome-wide scale. Nature 490(7421):556–560
92.
Yildirim MA, Goh K-I, Cusick ME, Barabási A-L, Vidal M (2007) Drug-target network. Nat Biotechnol 25(10):1119–1126CrossRefPubMed
93.
Huang Z, Zhang M, Burton SD, Katsakhyan LN, Ji H (2014) Targeting the Tcf4 G13ANDE17 binding site to selectively disrupt β-catenin/T-cell factor protein–protein interactions. ACS Chem Biol 9(1):193–201CrossRefPubMed
94.
Levin KB, Dym O, Albeck S, Magdassi S, Keeble AH, Kleanthous C, Tawfik DS (2009) Following evolutionary paths to protein-protein interactions with high affinity and selectivity. Nat Struct Mol Biol 16(10):1049–1055CrossRefPubMed
95.
Meenan NA, Sharma A, Fleishman SJ, Macdonald CJ, Morel B, Boetzel R, Moore GR, Baker D, Kleanthous C (2010) The structural and energetic basis for high selectivity in a high-affinity protein-protein interaction. Proc Natl Acad Sci USA 107(22):10080–10085CrossRefPubMed
96.
Kosloff M, Travis AM, Bosch DE, Siderovski DP, Arshavsky VY (2011) Integrating energy calculations with functional assays to decipher the specificity of G protein-RGS protein interactions. Nat Struct Mol Biol 18(7):846–853CrossRefPubMedPubMedCentral
Metadata
Title
Hot Spot-Based Design of Small-Molecule Inhibitors for Protein-Protein Interactions
Author
Haitao Ji
Copyright Year
2018
Publisher
Springer Singapore
Book
Targeting Protein-Protein Interactions by Small Molecules

Print ISBN: 978-981-13-0772-0

Electronic ISBN: 978-981-13-0773-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-13-0773-7_3