Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the diverse chemotypes present in PPIs. Here, we developed a novel pharmacophore-based interactive screening technology that builds on the role anchor residues, or deeply buried hot spots, have in PPIs, and redesigns these entry points with anchor-biased virtual multicomponent reactions, delivering tens of millions of readily synthesizable novel compounds. Application of this approach to the MDM2/p53 cancer target led to high hit rates, resulting in a large and diverse set of confirmed inhibitors, and co-crystal structures validate the designed compounds. Our unique open-access technology promises to expand chemical space and the exploration of the human interactome by leveraging in-house small-scale assays and user-friendly chemistry to rationally design ligands for PPIs with known structure.
References
[1]
Edwards AM, Isserlin R, Bader GD, Frye SV, Willson TM, et al. (2011) Too many roads not taken. Nature 470: 163–165.
[2]
Fedorov O, Muller S, Knapp S (2010) The (un)targeted cancer kinome. Nat Chem Biol 6: 166–169.
[3]
Macarron R (2006) Critical review of the role of HTS in drug discovery. Drug discovery today 11: 277–279.
[4]
Shoichet BK (2004) Virtual screening of chemical libraries. Nature 432: 862.
[5]
Jacoby E, Boettcher A, Mayr LM, Brown N, Jenkins JL, et al. (2009) Chemogenomics: Methods and Applications. pp. 173–194. Springer Protocols.
[6]
Spencer RW (1998) High-throughput screening of historic collections: observations on file size, biological targets, and file diversity. Biotechnol Bioeng 61: 61–67.
[7]
Bleicher KH, Bohm HJ, Muller K, Alanine AI (2003) Hit and lead generation: beyond high-throughput screening. Nature Reviews Drug Discovery 2: 369–378.
[8]
Pritchard JF, Jurima-Romet M, Reimer MLJ, Mortimer E, Rolfe B, et al. (2003) Making Better Drugs: Decision Gates in Non-Clinical Drug Development. Nat Rev Drug Discov 2: 542–553.
[9]
Sperandio O, Reyn？s C, Camproux A, Villoutreix B (2010) Rationalizing the chemical space of protein-protein interaction inhibitors. Drug Discovery Today 15: 220–229.
[10]
Pagliaro L, Felding J, Audouze K, Nielsen SJ, Terry RB, et al. (2004) Emerging classes of protein-protein interaction inhibitors and new tools for their development. Current Opinion in Chemical Biology 8: 442–449.
[11]
Reynes C, Host H, Camproux AC, Laconde G, Leroux F, et al. (2010) Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods. PLoS computational biology 6: e1000695.
[12]
Czarna A, Beck B, Srivastava S, Popowicz GM, Wolf S, et al. (2010) Robust Generation of Lead Compounds for Protein–Protein Interactions by Computational and MCR Chemistry: p53/Hdm2 Antagonists. Angewandte Chemie 122: 5480–5484.
[13]
D？mling A (2008) Small molecular weight protein-protein interaction antagonists–an insurmountable challenge? Current Opinion in Chemical Biology 12: 281–291.
[14]
Rajamani D, Thiel S, Vajda S, Camacho CJ (2004) Anchor residues in protein-protein interactions. Proc Natl Acad Sci U S A 101: 11287–11292.
[15]
Weber L, Illgen K, Almstetter M (1999) Discovery of new multi component reactions with combinatorial methods. Synlett 3: 366–374.
[16]
Liddle J, Allen MJ, Borthwick AD, Brooks DP, Davies DE, et al. (2008) The discovery of GSK221149A: a potent and selective oxytocin antagonist. Bioorganic & medicinal chemistry letters 18: 90–94.
[17]
Grasberger BL, Lu T, Schubert C, Parks DJ, Carver TE, et al. (2005) Discovery and Cocrystal Structure of Benzodiazepinedione HDM2 Antagonists That Activate p53 in Cells. Journal of Medicinal Chemistry 48: 909–912.
[18]
Rothweiler U, Czarna A, Krajewski M, Ciombor J, Kalinski C, et al. (2008) Isoquinolin-1-one Inhibitors of the MDM2–p53 Interaction. ChemMedChem 3: 1118–1128.
[19]
D？mling A, Huang Y (2010) Piperazine Scaffolds via Isocyanide-Based Multicomponent Reactions. Synthesis 2010: 2859,2883.
[20]
Irwin JJ, Shoichet BK (2005) ZINC- A Free Database of Commercially Available Compounds for Virtual Screening. J Chem Inf Model 45: 177–182.
[21]
Wells JA, McClendon CL (2007) Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 450: 1001–1009.
[22]
Fesik SW (2005) Promoting apoptosis as a strategy for cancer drug discovery. Nat Rev Cancer 5: 876–885.
[23]
Zobel K, Wang L, Varfolomeev E, Franklin MC, Elliott LO, et al. (2006) Design, synthesis, and biological activity of a potent Smac mimetic that sensitizes cancer cells to apoptosis by antagonizing IAPs. ACS Chem Biol 1: 525–533.
[24]
Vassilev L, Vu B, Graves B, Carvajal D, Podlaski F, et al. (2004) In vivo activation of the p53 pathway by small-molecule antagonists of MDM2. Science 303: 844.
[25]
Ma B, Nussinov R (2007) Trp/Met/Phe hot spots in protein-protein interactions: potential targets in drug design. Curr Top Med Chem 7: 999–1005.
[26]
Kimura SR, Brower RC, Vajda S, Camacho CJ (2001) Dynamical view of the positions of key side chains in protein-protein recognition. Biophys J 80: 635–642.
[27]
Meireles LM, Domling 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: SupplW407–411.
[28]
Willett P (2006) Similarity-based virtual screening using 2D fingerprints. Drug Discovery Today 11: 1046–1053.
[29]
Warren GL, Andrews CW, Capelli AM, Clarke B, LaLonde J, et al. (2006) A critical assessment of docking programs and scoring functions. J Med Chem 49: 5912–5931.
[30]
Leach AR, Gillet VJ, Lewis RA, Taylor R (2009) Three-dimensional pharmacophore methods in drug discovery. Journal of medicinal chemistry 53: 539–558.
[31]
Koes DR, Camacho CJ (2011) Pharmer: Efficient and Exact Pharmacophore Search. J Chem Inf Model 51(6): 1307–1314.
[32]
Sheridan RP, Rusinko A, Nilakantan R, Venkataraghavan R (1989) Searching for pharmacophores in large coordinate data bases and its use in drug design. Proceedings of the National Academy of Sciences 86: 8165–8169.
[33]
Maass P, Schulz-Gasch T, Stahl M, Rarey M (2007) Recore: A fast and versatile method for scaffold hopping based on small molecule crystal structure conformations. J Chem Inf Model 47: 390–399.
[34]
Popowicz G, Czarna A, Holak T (2008) Structure of the human Mdmx protein bound to the p53 tumor suppressor transactivation domain. Cell Cycle 7: 2441–2443.
[35]
Kussie PH, Gorina S, Marechal V, Elenbaas B, Moreau J, et al. (1996) Structure of the MDM2 Oncoprotein Bound to the p53 Tumor Suppressor Transactivation Domain. Science 274: 948–953.
[36]
Popowicz GM, Czarna A, Wolf S, Wang K, Wang W, et al. (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: 1104–1111.
[37]
Moitessier N, Englebienne P, Lee D, Lawandi J, Corbeil CR (2008) Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go. British Journal of Pharmacology 153: 7.
[38]
Zwick MB, Saphire EO, Burton DR (2004) gp41: HIV's shy protein. Nat Med 10: 133–134.
[39]
Hacker H, Karin M (2006) Regulation and function of IKK and IKK-related kinases. Science's STKE : signal transduction knowledge environment 2006: re13.
[40]
Wang X, Rickert M, Garcia KC (2005) Structure of the quaternary complex of interleukin-2 with its alpha, beta, and gammac receptors. Science 310: 1159–1163.
[41]
Pasquale EB (2010) Eph receptors and ephrins in cancer: bidirectional signalling and beyond. Nat Rev Cancer 10: 165–180.
[42]
Halgren TA (1996) Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry 17: 490–519.
[43]
Czarna A, Popowicz GM, Pecak A, Wolf S, Dubin G, et al. (2009) High affinity interaction of the p53 peptide-analogue with human Mdm2 and Mdmx. Cell Cycle 8: 1176–1184.
