Chemical Biology in Drug Discovery

Annual Reports in Medicinal Chemistry - Tập 50 - Trang 335-370 - 2017
M. Paola Castaldi1, Andrea Zuhl1, Piero Ricchiuto2, J. Adam Hendricks1
1Discovery Sciences, IMED Biotech Unit, AstraZeneca, Waltham, MA, United States
2Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cambridge, United Kingdom

Tài liệu tham khảo

Bucci, 2010, A Decade of Chemical Biology, Nat. Chem. Biol., 6, 847, 10.1038/nchembio.489 Cohen, 2007, A Clickable Inhibitor Reveals Context-Dependent Autoactivation of p90 RSK, Nat. Chem. Biol., 3, 156, 10.1038/nchembio859 Bunnage, 2013, Target Validation Using Chemical Probes, Nat. Chem. Biol., 9, 195, 10.1038/nchembio.1197 Bunnage, 2011, Getting Pharmaceutical R&D Back on Target, Nat. Chem. Biol., 7, 335, 10.1038/nchembio.581 Martinez Molina, 2013, Monitoring Drug Target Engagement in Cells and Tissues Using the Cellular Thermal Shift Assay, Science, 341, 84, 10.1126/science.1233606 Bunnage, 2015, Know Your Target, Know Your Molecule, Nat. Chem. Biol., 11, 368, 10.1038/nchembio.1813 Schirle, 2012, Mass Spectrometry-Based Proteomics in Preclinical Drug Discovery, Chem. Biol., 19, 72, 10.1016/j.chembiol.2012.01.002 Lee, 2013, Target Deconvolution Techniques in Modern Phenotypic Profiling, Curr. Opin. Chem. Biol., 17, 118, 10.1016/j.cbpa.2012.12.022 Zinn, 2012, Mass Spectrometry Approaches to Monitor Protein-Drug Interactions, Methods, 57, 430, 10.1016/j.ymeth.2012.05.008 Huang, 2009, Tankyrase Inhibition Stabilizes Axin and Antagonizes Wnt Signalling, Nature, 461, 614, 10.1038/nature08356 Dale, 2015, A Selective Chemical Probe for Exploring the Role of CDK8 and CDK19 in Human Disease, Nat. Chem. Biol., 11, 973, 10.1038/nchembio.1952 Ito, 2010, Identification of a Primary Target of Thalidomide Teratogenicity, Science, 327, 1345, 10.1126/science.1177319 Bantscheff, 2007, Quantitative Chemical Proteomics Reveals Mechanisms of Action of Clinical ABL Kinase Inhibitors, Nat. Biotechnol., 25, 1035, 10.1038/nbt1328 Médard, 2015, Optimized Chemical Proteomics Assay for Kinase Inhibitor Profiling, J. Proteome Res., 14, 1574, 10.1021/pr5012608 Bantscheff, 2011, Chemoproteomics Profiling of HDAC Inhibitors Reveals Selective Targeting of HDAC Complexes, Nat. Biotechnol., 29, 255, 10.1038/nbt.1759 Yang, 2015, Activity-Based Protein Profiling: Recent Advances in Probe Development and Applications, Chembiochem, 16, 712, 10.1002/cbic.201402582 Sanman, 2014, Activity-Based Profiling of Proteases, Annu. Rev. Biochem., 83, 249, 10.1146/annurev-biochem-060713-035352 Martell, 2014, Applications of Copper-Catalyzed Click Chemistry in Activity-Based Protein Profiling, Molecules, 19, 1378, 10.3390/molecules19021378 Rostovtsev, 2002, A Stepwise Huisgen Cycloaddition Process: Copper(I)-Catalyzed Regioselective “Ligation” of Azides and Terminal Alkynes, Angew. Chem. Int. Ed. Engl., 41, 2596, 10.1002/1521-3773(20020715)41:14<2596::AID-ANIE2596>3.0.CO;2-4 Arastu-Kapur, 2008, Identification of Proteases that Regulate Erythrocyte Rupture by the Malaria Parasite Plasmodium falciparum, Nat. Chem. Biol., 4, 203, 10.1038/nchembio.70 Leung, 2003, Discovering Potent and Selective Reversible Inhibitors of Enzymes in Complex Proteomes, Nat. Biotechnol., 21, 687, 10.1038/nbt826 Adibekian, 2012, Confirming Target Engagement for Reversible Inhibitors in vivo by Kinetically Tuned Activity-Based Probes, J. Am. Chem. Soc., 134, 10345, 10.1021/ja303400u Lapinsky, 2015, Recent Developments and Applications of Clickable Photoprobes in Medicinal Chemistry and Chemical Biology, Future Med. Chem., 7, 2143, 10.4155/fmc.15.136 Smith, 2015, Photoaffinity Labeling in Target- and Binding-Site Identification, Future Med. Chem., 7, 159, 10.4155/fmc.14.152 Zuhl, 2016, Chemoproteomic Profiling Reveals that Cathepsin D Off-Target Activity Drives Ocular Toxicity of β-Secretase Inhibitors, Nat. Commun., 7, 13042, 10.1038/ncomms13042 Niphakis, 2015, A Global Map of Lipid-Binding Proteins and Their Ligandability in Cells, Cell, 161, 1668, 10.1016/j.cell.2015.05.045 Koutsoukas, 2011, From In Silico Target Prediction to Multi-Target Drug Design: Current Databases, Methods and Applications, J. Proteomics, 74, 2554, 10.1016/j.jprot.2011.05.011 Guney, 2016, Network-Based In Silico Drug Efficacy Screening, Nat. Commun., 7, 10.1038/ncomms10331 Lamb, 2007, The Connectivity Map: A New Tool for Biomedical Research, Nat. Rev. Cancer, 7, 54, 10.1038/nrc2044 Rognan, 2010, Structure-Based Approaches to Target Fishing and Ligand Profiling, Mol. Inf., 29, 176, 10.1002/minf.200900081 Keiser, 2009, Predicting New Molecular Targets for Known Drugs, Nature, 462, 175, 10.1038/nature08506 Nidhi, 2006, Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases, J. Chem. Inf. Model., 46, 1124, 10.1021/ci060003g Li, 2006, TarFisDock: A Web Server for Identifying Drug Targets With Docking Approach, Nucleic Acids Res., 34, W219, 10.1093/nar/gkl114 Cheng, 2011, Identifying Compound-Target Associations by Combining Bioactivity Profile Similarity Search and Public Databases Mining, J. Chem. Inf. Model., 51, 2440, 10.1021/ci200192v Simon, 1996, Chemical Similarity Using Physiochemical Property Descriptors, J. Chem. Inf. Comput. Sci., 36, 118, 10.1021/ci950274j Hull, 2001, Latent Semantic Structure Indexing (LaSSI) for Defining Chemical Similarity, J. Med. Chem., 44, 1177, 10.1021/jm000393c Durant, 2002, Reoptimization of MDL Keys for Use in Drug Discovery, J. Chem. Inf. Comput. Sci., 42, 1273, 10.1021/ci010132r Schuffenhauer, 2003, Similarity Metrics for Ligands Reflecting the Similarity of the Target Proteins, J. Chem. Inf. Comput. Sci., 43, 391, 10.1021/ci025569t Roy, 2012, Electrotopological State Atom (E-State) Index in Drug Design, QSAR, Property Prediction and Toxicity Assessment, Curr. Comput. Aided Drug Des., 8, 135, 10.2174/157340912800492366 Kawabata, 2003, MATRAS: A Program for Protein 3D Structure Comparison, Nucleic Acids Res., 31, 3367, 10.1093/nar/gkg581 Lo, 2016, 3D Chemical Similarity Networks for Structure-Based Target Prediction and Scaffold Hopping, ACS Chem. Biol., 11, 2244, 10.1021/acschembio.6b00253 Hendlich, 2003, Relibase: Design and Development of a Database for Comprehensive Analysis of Protein-Ligand Interactions, J. Mol. Biol., 326, 607, 10.1016/S0022-2836(02)01408-0 Sheridan, 1994, Extending the Trend Vector: The Trend Matrix and Sample-Based Partial Least Squares, J. Comput. Aided Mol. Des., 8, 323, 10.1007/BF00126749 Miller, 1994, FLOG: A System to Select ‘quasi-flexible’ Ligands Complementary to a Receptor of Known Three-Dimensional Structure, J. Comput. Aided Mol. Des., 8, 153, 10.1007/BF00119865 Poroikov, 2002, How to Acquire New Biological Activities in Old Compounds by Computer Prediction, J. Comput. Aided Mol. Des., 16, 819, 10.1023/A:1023836829456 Geronikaki, 2004, Design of New Cognition Enhancers: From Computer Prediction to Synthesis and Biological Evaluation, J. Med. Chem., 47, 2870, 10.1021/jm031086k Chen, 2001, Ligand-Protein Inverse Docking and Its Potential Use in the Computer Search of Protein Targets of a Small Molecule, Proteins, 43, 217, 10.1002/1097-0134(20010501)43:2<217::AID-PROT1032>3.0.CO;2-G Deng, 2004, Structural Interaction Fingerprint (SIFt): A Novel Method for Analyzing Three-Dimensional Protein-Ligand Binding Interactions, J. Med. Chem., 47, 337, 10.1021/jm030331x Sliwoski, 2014, Computational Methods in Drug Discovery, Pharmacol. Rev., 66, 334, 10.1124/pr.112.007336 Reker, 2014, Identifying the Macromolecular Targets of De Novo-Designed Chemical Entities Through Self-Organizing Map Consensus, Proc. Natl. Acad. Sci. U. S. A., 111, 4067, 10.1073/pnas.1320001111 Dunkel, 2008, SuperPred: Drug Classification and Target Prediction, Nucleic Acids Res., 36, W55, 10.1093/nar/gkn307 Gfeller, 2013, Shaping the Interaction Landscape of Bioactive Molecules, Bioinformatics, 29, 3073, 10.1093/bioinformatics/btt540 Yamanishi, 2014, DINIES: Drug-Target Interaction Network Inference Engine Based on Supervised Analysis, Nucleic Acids Res., 42, W39, 10.1093/nar/gku337 Xiao, 2015, iDrug-Target: Predicting the Interactions Between Drug Compounds and Target Proteins in Cellular Networking Via Benchmark Dataset Optimization Approach, J. Biomol. Struct. Dyn., 33, 2221, 10.1080/07391102.2014.998710 Patterson, 1996, Neighborhood Behavior: A Useful Concept for Validation of “Molecular Diversity” Descriptors, J. Med. Chem., 39, 3049, 10.1021/jm960290n Engel, 2006, Basic Overview of Chemoinformatics, J. Chem. Inf. Model., 46, 2267, 10.1021/ci600234z Yan, 2016, Chemical Structure Similarity Search for Ligand-Based Virtual Screening: Methods and Computational Resources, Curr. Drug Targets, 17, 1580, 10.2174/1389450116666151102095555 Cross, 2012, GRID-Based Three-Dimensional Pharmacophores I: FLAPpharm, a Novel Approach for Pharmacophore Elucidation, J. Chem. Inf. Model., 52, 2587, 10.1021/ci300153d Bajorath, 2017, Molecular Similarity Concepts for Informatics Applications, Methods Mol. Biol., 1526, 231, 10.1007/978-1-4939-6613-4_13 Downs, 1995 Peter, 1998, Chemical Similarity Searching, J. Chem. Inf. Comput. Sci., 38, 983, 10.1021/ci9800211 Bajorath, 2001, Selected Concepts and Investigations in Compound Classification, Molecular Descriptor Analysis, and Virtual Screening, J. Chem. Inf. Comput. Sci., 41, 233, 10.1021/ci0001482 Cheng, 2002, Computation of the Physio-Chemical Properties and Data Mining of Large Molecular Collections, J. Comput. Chem., 23, 172, 10.1002/jcc.1164 Schuur, 1996, The Coding of the Three-Dimensional Structure of Molecules by Molecular Transforms and Its Application to Structure-Spectra Correlations and Studies of Biological Activity, J. Chem. Inf. Comput. Sci., 36, 334, 10.1021/ci950164c Ginn, 2000 Huang, 2012, Proteochemometric Modeling of the Bioactivity Spectra of HIV-1 Protease Inhibitors by Introducing Protein-Ligand Interaction Fingerprint, PLoS One, 7, 10.1371/journal.pone.0041698 Humbeck, 2017, What Can We Learn From Bioactivity Data? Chemoinformatics Tools and Applications in Chemical Biology Research, ACS Chem. Biol., 12, 23, 10.1021/acschembio.6b00706 Koutsoukas, 2013, In Silico Target Predictions: Defining a Benchmarking Data Set and Comparison of Performance of the Multiclass Naïve Bayes and Parzen-Rosenblatt Window, J. Chem. Inf. Model., 53, 1957, 10.1021/ci300435j Mervin, 2015, Target Prediction Utilising Negative Bioactivity Data Covering Large Chemical Space, J. Chem., 7, 51, 10.1186/s13321-015-0098-y Gaulton, 2012, ChEMBL: A Large-Scale Bioactivity Database for Drug Discovery, Nucleic Acids Res., 40, D1100, 10.1093/nar/gkr777 Hudson, 1996, Parameter Based Methods for Compound Selection From Chemical Databases, Quant. Struct. Act. Relat., 15, 285, 10.1002/qsar.19960150402 Gobbi, 2003, DISE: Directed Sphere Exclusion, J. Chem. Inf. Comput. Sci., 43, 317, 10.1021/ci025554v Pantoliano, 2001, High-Density Miniaturized Thermal Shift Assays as a General Strategy for Drug Discovery, J. Biomol. Screen., 6, 429, 10.1177/108705710100600609 Lo, 2004, Evaluation of Fluorescence-Based Thermal Shift Assays for Hit Identification in Drug Discovery, Anal. Biochem., 332, 153, 10.1016/j.ab.2004.04.031 Liu, 2012, Iniparib Nonselectively Modifies Cysteine-Containing Proteins in Tumor Cells and Is Not a Bona Fide PARP Inhibitor, Clin. Cancer Res., 18, 510, 10.1158/1078-0432.CCR-11-1973 Peppard, 2003, Development of a High-Throughput Screening Assay for Inhibitors of Aggrecan Cleavage Using Luminescent Oxygen Channeling (AlphaScreen), J. Biomol. Screen., 8, 149, 10.1177/1087057103252308 Eglen, 2008, The Use of AlphaScreen Technology in HTS: Current Status, Curr. Chem. Genomics, 1, 2, 10.2174/1875397300801010002 Almqvist, 2016, CETSA Screening Identifies Known and Novel Thymidylate Synthase Inhibitors and Slow Intracellular Activation of 5-Fluorouracil, Nat. Commun., 7, 11040, 10.1038/ncomms11040 Longley, 2003, 5-Fluorouracil: Mechanisms of Action and Clinical Strategies, Nat. Rev. Cancer, 3, 330, 10.1038/nrc1074 Savitski, 2014, Tracking Cancer Drugs in Living Cells by Thermal Profiling of the Proteome, Science, 346, 1255784, 10.1126/science.1255784 Gelot, 2013, Vemurafenib: An Unusual UVA-Induced Photosensitivity, Exp. Dermatol., 22, 297, 10.1111/exd.12119 Becher, 2016, Thermal Profiling Reveals Phenylalanine Hydroxylase as an Off-Target of Panobinostat, Nat. Chem. Biol., 12, 908, 10.1038/nchembio.2185 Reinhard, 2015, Thermal Proteome Profiling Monitors Ligand Interactions with Cellular Membrane Proteins, Nat. Methods, 12, 1129, 10.1038/nmeth.3652 Huber, 2015, Proteome-Wide Drug and Metabolite Interaction Mapping by Thermal-Stability Profiling, Nat. Methods, 12, 1055, 10.1038/nmeth.3590 Lea, 2011, Fluorescence Polarization Assays in Small Molecule Screening, Expert Opin. Drug Discovery, 6, 17, 10.1517/17460441.2011.537322 Parker, 2000, Development of High Throughput Screening Assays Using Fluorescence Polarization: Nuclear Receptor-Ligand-Binding and Kinase/Phosphatase Assays, J. Biomol. Screen., 5, 77, 10.1177/108705710000500204 Dubach, 2014, In Vivo Imaging of Specific Drug-Target Binding at Subcellular Resolution, Nat. Commun., 5, 3946, 10.1038/ncomms4946 Dubach, 2017, Quantitating Drug-Target Engagement in Single Cells in vitro and In Vivo, Nat. Chem. Biol., 13, 168, 10.1038/nchembio.2248 Kumar, 2011, FLIM FRET Technology for Drug Discovery: Automated Multiwell-Plate High-Content Analysis, Multiplexed Readouts and Application In Situ, Chemphyschem, 12, 609, 10.1002/cphc.201000874 Zimmermann, 2013, Small Molecule Inhibition of the KRAS-PDEδ Interaction Impairs Oncogenic KRAS Signalling, Nature, 497, 638, 10.1038/nature12205 Machleidt, 2015, NanoBRET—A Novel BRET Platform for the Analysis of Protein-Protein Interactions, ACS Chem. Biol., 10, 1797, 10.1021/acschembio.5b00143 Robers, 2015, Target Engagement and Drug Residence Time Can Be Observed in Living Cells With BRET, Nat. Commun., 6, 10.1038/ncomms10091 Ito, 2011, Real-Time Imaging of Histone H4K12-Specific Acetylation Determines the Modes of Action of Histone Deacetylase and Bromodomain Inhibitors, Chem. Biol., 18, 495, 10.1016/j.chembiol.2011.02.009 Kaniskan, 2015, A Potent, Selective and Cell-Active Allosteric Inhibitor of Protein Arginine Methyltransferase 3 (PRMT3), Angew. Chem. Int. Ed. Engl., 54, 5166, 10.1002/anie.201412154 Schulze, 2015, Cell-Based Protein Stabilization Assays for the Detection of Interactions Between Small-Molecule Inhibitors and BRD4, J. Biomol. Screen., 20, 180, 10.1177/1087057114552398 Butler, 2009, Proteomic Identification of Multitasking Proteins in Unexpected Locations Complicates Drug Targeting, Nat. Rev. Drug Discov., 8, 935, 10.1038/nrd2945 Lai, 2017, Induced Protein Degradation: An Emerging Drug Discovery Paradigm, Nat. Rev. Drug Discov., 16, 101, 10.1038/nrd.2016.211 Boutros, 2008, The Art and Design of Genetic Screens: RNA Interference, Nat. Rev. Genet., 9, 554, 10.1038/nrg2364 Cong, 2013, Multiplex Genome Engineering Using CRISPR/Cas Systems, Science, 339, 819, 10.1126/science.1231143 Haurwitz, 2010, Sequence- and Structure-Specific RNA Processing by a CRISPR Endonuclease, Science, 329, 1355, 10.1126/science.1192272 Wood, 2011, Targeted Genome Editing Across Species Using ZFNs and TALENs, Science, 333, 307, 10.1126/science.1207773 Sander, 2011, Selection-Free Zinc-Finger-Nuclease Engineering by Context-Dependent Assembly (CoDA), Nat. Methods, 8, 67, 10.1038/nmeth.1542 Schenone, 2013, Target Identification and Mechanism of Action in Chemical Biology and Drug Discovery, Nat. Chem. Biol., 9, 232, 10.1038/nchembio.1199 Zengerle, 2015, Selective Small Molecule Induced Degradation of the BET Bromodomain Protein BRD4, ACS Chem. Biol., 10, 1770, 10.1021/acschembio.5b00216 Kettle, 2016, Potent and Selective Inhibitors of MTH1 Probe Its Role in Cancer Cell Survival, J. Med. Chem., 59, 2346, 10.1021/acs.jmedchem.5b01760 Gad, 2014, MTH1 Inhibition Eradicates Cancer by Preventing Sanitation of the dNTP Pool, Nature, 508, 215, 10.1038/nature13181 Petrocchi, 2016, Identification of Potent and Selective MTH1 Inhibitors, Bioorg. Med. Chem. Lett., 26, 1503, 10.1016/j.bmcl.2016.02.026