Protein-protein interaction inhibitors: advances in anticancer drug design

Expert Opinion on Drug Discovery

Volumn 11, Issue 10, 2016, Pages 957-968

  Ferreira, Leonardo G ^a   Oliva, Glaucius ^a   Andricopulo, Adriano D ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

cancer; hot spots; molecular docking; protein protein interactions; Structure based drug design; X ray crystallography

Indexed keywords

ANTINEOPLASTIC AGENT; PROTEIN MDM2; PROTEIN P53; LIGAND; PROTEIN; PROTEIN BINDING;

BINDING SITE; DRUG DESIGN; DRUG INDUSTRY; HUMAN; MOLECULAR DOCKING; MOLECULAR DYNAMICS; NONHUMAN; NUCLEAR MAGNETIC RESONANCE; PRIORITY JOURNAL; PROTEIN PROTEIN INTERACTION; PROTON NUCLEAR MAGNETIC RESONANCE; REVIEW; SURFACE AREA; X RAY CRYSTALLOGRAPHY; DRUG DEVELOPMENT; MEDICINAL CHEMISTRY; METABOLISM; NEOPLASMS; PROCEDURES;

ANTINEOPLASTIC AGENTS; CHEMISTRY, PHARMACEUTICAL; CRYSTALLOGRAPHY, X-RAY; DRUG DESIGN; DRUG DISCOVERY; HUMANS; LIGANDS; MOLECULAR DOCKING SIMULATION; NEOPLASMS; PROTEIN BINDING; PROTEINS;

EID: 84987719423     PISSN: 17460441     EISSN: 1746045X     Source Type: Journal    
DOI: 10.1080/17460441.2016.1223038     Document Type: Review

References (64)

1. L.Jin, W.Wang, G.Fang Targeting protein-protein interaction by small molecules. Annu Rev Pharmacol Toxicol. 2014;54:435–456. doi:10.1146/annurev-pharmtox-011613-140028.
2. V.Lounnas, T.Ritschel, J.Kelder, et al. Current progress in structure-based rational drug design marks a new mindset in drug discovery. Comput Struct Biotechnol J. 2013;5:e201302011. doi:10.5936/csbj.201302011.• This review focuses on the use of SBDD, emphasizing the integration between X-ray crystallography and molecular modeling in the discovery of high-affinity ligands for relevant target classes, such as G protein-coupled receptors and kinases.
3. B.Honarparvar, T.Govender, G.E.Maguire, et al. Integrated approach to structure-based enzymatic drug design:molecular modeling, spectroscopy, and experimental bioactivity. Chem Rev. 2014;114:493–537. doi:10.1021/cr300314q.
4. D.Alvarez-Garcia, X.Barril. Relationship between protein flexibility and binding:lessons for structure-based drug design. J Chem Theory Comput. 2014;10:2608–2614. doi:10.1021/ct500182z.
5. J.Eder, R.Sedrani, C.Wiesmann. The discovery of first-in-class drugs:origins and evolution. Nat Rev Drug Discov. 2014;13:577–587. doi:10.1038/nrd4336.• This article presents an analysis of the drug discovery strategies used in the development of first-in-class drugs and highlights the impact of SBDD in the Food and Drug Administration approvals between 1999 and 2013.
6. E.Valkov, T.Sharpe, M.Marsh, et al. Targeting protein-protein interactions and fragment-based drug discovery. Top Curr Chem. 2012;317:145–179. doi:10.1007/128_2011_265.
7. M.P.H.Stumpf, T.Thorne, E.de Silva, et al. Estimating the size of the human interactome. Proc Natl Acad Sci USA. 2008;105:6959–6964. doi:10.1073/pnas.0708078105.
8. M.R.Arkin, Y.Tang, J.A.Wells. Small-molecule inhibitors of protein-protein interactions:progressing toward the reality. Chem Biol. 2014;21:1102–1114. doi:10.1016/j.chembiol.2014.09.001.•• This review provides an overview of the progress made in the past decade in the discovery of PPI inhibitors and highlights relevant clinical trials in the field.
9. J.C.Fuller, N.J.Burgoyne, R.M.Jackson. Predicting druggable binding sites at the protein-protein interface. Drug Discov Today. 2009;14:155–161. doi:10.1016/j.drudis.2008.10.009.•• This article summarizes the algorithms for predicting protein–protein interaction-binding pockets with a focus on the key differences between PPI surfaces and binding sites that interact with small molecules.
10. R.Sable, S.Jois. Surfing the protein-protein interaction surface using docking methods:application to the design of PPI inhibitors. Molecules. 2015;20:11569–11603. doi:10.3390/molecules200611569.•• This review outlines recent examples on the use of molecular docking in PPI drug discovery along with the main challenges and limitations of this technique. In addition, the article approaches the identification of PPI inhibitors through the combination of improved scoring functions and experimental methods.
11. G.G.Xu, J.Guo, Y.Wu. Chemokine receptor CCR5 antagonist maraviroc:medicinal chemistry and clinical applications. Curr Top Med Chem. 2014;14:1504–1514.
12. Safety study of ABT-263 in combination with rituximab in lymphoid cancers. ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT00788684.
13. C.-M.Park, M.Bruncko, J.Adickes, et al. Discovery of an orally bioavailable small molecule inhibitor of prosurvival B-cell lymphoma 2 proteins. J Med Chem. 2008;51:6902–6915. doi:10.1021/jm800669s.
14. A study evaluating ABT-199 in combination with low-dose cytarabine in treatment-naïve subjects with acute myelogenous leukemia (AML). ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT02287233.
15. C.Touzeau, C.Dousset, S.Le Gouill, et al. The Bcl-2 specific BH3 mimetic ABT-199:a promising targeted therapy for t(11;14) multiple myeloma. Leukemia. 2014;28:210–212. doi:10.1038/leu.2013.216.
16. Open label study of single agent oral RG7388 in patients with polycythemia vera and essential thrombocythemia. ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT02407080.
17. Q.Ding, Z.Zhang, L.Jj, et al. Discovery of RG7388, a potent and selective p53-MDM2 inhibitor in clinical development. J Med Chem. 2013;56:5979–5983. doi:10.1021/jm400487c.
18. A phase 1b study evaluating AMG 232 alone and in combination with trametinib in acute myeloid leukemia. ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT02016729.
19. Phase 1 safety testing of SAR405838. ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT01636479.
20. S.Wang, W.Sun, Y.Zhao, et al. SAR405838:an optimized inhibitor of MDM2-p53 interaction that induces complete and durable tumor regression. Cancer Res. 2014;74:5855–5865. doi:10.1158/0008-5472.CAN-14-0799.
21. A phase I dose escalation study of CGM097 in adult patients with selected advanced solid tumors (CCGM097X2101). ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT01760525.
22. Effect of RVX000222 on time to major adverse cardiovascular events in high-risk T2DM subjects with CAD (BETonMACE). ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT02586155.
23. K.G.McLure, E.M.Gesner, L.Tsujikawa, et al. RVX-208, an inducer of ApoA-I in humans, is a BET bromodomain antagonist. PLoS One. 2013;8:e83190. doi:10.1371/journal.pone.0083190.
24. A dose escalation study to investigate the safety, pharmacokinetics (PK), pharmacodynamics (PD) and clinical activity of GSK525762 in subjects with relapsed, refractory hematologic malignancies. ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT01943851.
25. E.Nicodeme, K.L.Jeffrey, U.Schaefer, et al. Suppression of inflammation by a synthetic histone mimic. Nature. 2010;468:1119–1123. doi:10.1038/nature09589.
26. A phase 1 study evaluating CPI-0610 in patients with progressive lymphoma. ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT01949883.
27. A dose-finding study of OTX105/MK-8628, a small molecule inhibitor of the bromodomain and extra-terminal (BET) proteins, in adults with selected advanced solid tumors (MK-8628-003). ClinicalTrials.gov, 2016. [cited 2016 Apr03]. Available from:https://clinicaltrials.gov/ct2/show/NCT02259114.
28. M.M.Coudé, T.Braun, J.Berrou, et al. BET inhibitor OTX015 targets BRD2 and BRD4 and decreases c-MYC in acute leukemia cells. Oncotarget. 2015;6:17698–17712. doi:10.18632/oncotarget.4131.
29. L.G.Ferreira, R.N.Dos Santos, G.Oliva, et al. Molecular docking and structure-based drug design strategies. Molecules. 2015;20:13384–13421. doi:10.3390/molecules200713384.
30. J.Chen, X.Ma, Y.Yuan, et al. Protein-protein interface analysis and hot spots identification for chemical ligand design. Curr Pharm Des. 2014;20:1192–1200.
31. X.Zheng, L.Gan, E.Wang, et al. Pocket-based drug design:exploring pocket space. AAPS J. 2013;15:228–241. doi:10.1208/s12248-012-9426-6.•• This review explores the main methodologies that are used in computational analysis of PPI-binding pockets, some relevant case studies and perspectives for further developments in the field.
32. Y.Yuan, J.Pei, L.Lai. Binding site detection and druggability prediction of protein targets for structure-based drug design. Curr Pharm Des. 2013;19:2326–2333.
33. D.Rooklin, C.Wang, J.Katigbak, et al. AlphaSpace:Fragment-centric topographical mapping to target protein-protein interaction interfaces. J Chem Inf Model. 2015;55:1585–1599. doi:10.1021/acs.jcim.5b00103.
34. V.Le Guilloux, P.Schmidtke, P.Tuffery. Fpocket:an open source platform for ligand pocket detection. BMC Bioinf. 2009;10:168. doi:10.1186/1471-2105-10-168.
35. A.T.Laurie, R.M.Jackson. Q-SiteFinder:an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics. 2005;21:1908–1916. doi:10.1093/bioinformatics/bti315.
36. J.K.Dhanjal, S.Goyal, S.Sharma, et al. Mechanistic insights into mode of action of potent natural antagonists of BACE-1 for checking Alzheimer’s plaque pathology. Biochem Biophys Res Commun. 2014;443:1054–1059. doi:10.1016/j.bbrc.2013.12.088.
37. D.Méndez-Luna, M.Martínez-Archundia, R.C.Maroun, et al. Deciphering the GPER/GPR30-agonist and antagonists interactions using molecular modeling studies, molecular dynamics, and docking simulations. J Biomol Struct Dyn. 2015;33:2161–2172. doi:10.1080/07391102.2014.994102.
38. B.Zarzycka, T.Seijkens, S.B.Nabuurs, et al. Discovery of small molecule CD40-TRAF6 inhibitors. J Chem Inf Model. 2015;55:294–307. doi:10.1021/ci500631e.
39. L.M.Meireles, A.S.Dömling, C.J.Camacho. ANCHOR:a web server and database for analysis of protein-protein interaction binding pockets for drug discovery. Nucleic Acids Res. 2010;38:W407–11. doi:10.1093/nar/gkq502.
40. C.J.Camacho, C.Zhang. FastContact:rapid estimate of contact and binding free energies. Bioinformatics. 2005;21:2534–2536. doi:10.1093/bioinformatics/bti322.
41. A.M.Pedley, M.A.Lill, V.J.Davisson. Flexibility of PCNA-protein interface accommodates differential binding partners. PLoS One. 2014;9:e102481. doi:10.1371/journal.pone.0102481.
42. C.Dominguez, R.Boelens, A.M.Bonvin. HADDOCK:a protein-protein docking approach based on biochemical or biophysical information. J Am Chem Soc. 2003;125:1731–1737. doi:10.1021/ja026939x.
43. J.M.Planesas, V.I.Pérez-Nueno, J.I.Borrell, et al. Studying the binding interactions of allosteric agonists and antagonists of the CXCR4 receptor. J Mol Graph Model. 2015;60:1–14. doi:10.1016/j.jmgm.2015.05.004.
44. L.Ouyang, Z.Shi, S.Zhao, et al. Programmed cell death pathways in cancer:a review of apoptosis, autophagy and programmed necrosis. Cell Prolif. 2012;45:487–498. doi:10.1111/j.1365-2184.2012.00845.x.
45. N.Allocati, V.Graziano, C.Di Ilio, et al. Role of apoptosis in disease. Aging (Albany NY). 2012;4:330–349. doi:10.18632/aging.100459.
46. C.Bodur, H.Basaga. Bcl-2 inhibitors:emerging drugs in cancer therapy. Curr Med Chem. 2012;19:1804–1820.
47. R.M.Brady, A.Vom, M.J.Roy. De-novo designed library of benzoylureas as inhibitors of BCL-XL:synthesis, structural and biochemical characterization. J Med Chem. 2014;57:1323–1343. doi:10.1021/jm401948b.
48. N.F.Pelz, Z.Bian, B.Zhao, et al. Discovery of 2-Indole-acylsulfonamide myeloid cell leukemia 1 (Mcl-1) inhibitors using fragment-based methods. J Med Chem. 2016;59:2054–2066. doi:10.1021/acs.jmedchem.5b01660.
49. I.E.Wertz, S.Kusam, C.Lam, et al. Sensitivity to antitubulin chemotherapeutics is regulated by MCL1 and FBW7. Nature. 2011;471:110–114. doi:10.1038/nature09779.
50. S.H.Wei, K.Dong, F.Lin, et al. Inducing apoptosis and enhancing chemosensitivity to gemcitabine via RNA interference targeting Mcl-1 gene in pancreatic carcinoma cell. Cancer Chemother Pharmacol. 2008;62:1055–1064. doi:10.1007/s00280-008-0697-7.
51. A.Vazquez, E.E.Bond, A.J.Levine, et al. The genetics of the p53 pathway, apoptosis and cancer therapy. Nat Rev Drug Discov. 2008;7:979–987. doi:10.1038/nrd2656.
52. P.Chène. Inhibiting the p53-MDM2 interaction:an important target for cancer therapy. Nat Rev Cancer. 2003;3:102–109. doi:10.1038/nrc991.
53. K.H.Khoo, C.S.Verma, D.P.Lane. Drugging the p53 pathway:understanding the route to clinical efficacy. Nat Rev Drug Discov. 2014;13:217–236. doi:10.1038/nrd4236.
54. P.H.Kussie, S.Gorina, V.Marechal, et al. Structure of the MDM2 oncoprotein bound to the p53 tumor suppressor transactivation domain. Science. 1996;274:948–953.
55. F.Gessier, J.Kallen, E.Jacoby, et al. Discovery of dihydroisoquinolinone derivatives as novel inhibitors of the p53-MDM2 interaction with a distinct binding mode. Bioorg Med Chem Lett. 2015;25:3621–3625. doi:10.1016/j.bmcl.2015.06.058.
56. P.Holzer, K.Masuya, P.Furet, et al. Discovery of a dihydroisoquinolinone derivative (NVP-CGM097):a highly potent and selective MDM2 inhibitor undergoing phase 1 clinical trials in p53wt tumors. J Med Chem. 2015;58:6348–6358. doi:10.1021/acs.jmedchem.5b00810.
57. Y.Rew, D.Sun. Discovery of a small molecule MDM2 inhibitor (AMG 232) for treating cancer. J Med Chem. 2014;57:6332–6341. doi:10.1021/jm500627s.
58. E.Ferri, C.Petosa, C.E.McKenna. Bromodomains:structure, function and pharmacology of inhibition. Biochem Pharmacol. 2016;106:1–18. doi:10.1016/j.bcp.2015.12.005.
59. A.Dey, F.Chitsaz, A.Abbasi, et al. The double bromodomain protein Brd4 binds to acetylated chromatin during interphase and mitosis. Proc Natl Acad Sci USA. 2003;100:8758–8763. doi:10.1073/pnas.1433065100.
60. M.A.Dawson, R.K.Prinjha, A.Dittmann, et al. Inhibition of BET recruitment to chromatin as an effective treatment for MLL-fusion leukaemia. Nature. 2011;478:529–533. doi:10.1038/nature10509.
61. A.Wyce, G.Ganji, K.N.Smitheman, et al. BET inhibition silences expression of MYCN and BCL2 and induces cytotoxicity in neuroblastoma tumor models. PLoS One. 2013;8:e72967. doi:10.1371/journal.pone.0072967.
62. B.K.Albrecht, V.S.Gehling, M.C.Hewitt, et al. Identification of a benzoisoxazoloazepine inhibitor (CPI-0610) of the bromodomain and extra-terminal (BET) family as a candidate for human clinical trials. J Med Chem. 2016;59:1330–1339. doi:10.1021/acs.jmedchem.5b01882.
63. J.Seal, Y.Lamotte, F.Donche, et al. Identification of a novel series of BET family bromodomain inhibitors:binding mode and profile of I-BET151 (GSK1210151A). Bioorg Med Chem Lett. 2012;22:2968–2972. doi:10.1016/j.bmcl.2012.02.041.
64. X.Ran, Y.Zhao, L.Liu, et al. Structure-based design of γ-carboline analogues as potent and specific BET bromodomain inhibitors. J Med Chem. 2015;58:4927–4939. doi:10.1021/acs.jmedchem.5b00613.