Exploring new targets and chemical space with affinity selection-mass spectrometry

Abstract

Affinity selection-mass spectrometry (AS-MS) is a high-throughput screening (HTS) technique for drug discovery that enables rapid screening of large collections of compounds to identify ligands for a specific biomolecular target. AS-MS is a binding assay that is insensitive to the functional effects a ligand might have, which is important because it lets us identify novel ligands irrespective of their binding site. This approach is gaining popularity, notably due to its role in the emergence of useful agents for targeted protein degradation. This Perspective highlights the use of AS-MS techniques to explore broad chemical space and identify small-molecule ligands for biological targets that have proven challenging to address with other screening paradigms. We present chemical structures of reported AS-MS hits to illustrate the potential of this screening approach to deliver high-quality hits for further optimization. AS-MS has, thus, evolved from being an infrequent alternative to traditional HTS or DNA-encoded library strategies to now firmly establishing itself as a HTS approach for drug discovery.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: General workflow of SEC AS-MS screening for protein–ligand identification.
Fig. 2: Natural-product-inspired AS-MS collection.

References

  1. 1.

    Mignani, S., Huber, S., Tomás, H., Rodrigues, J. & Majoral, J.-P. Why and how have drug discovery strategies in pharma changed? What are the new mindsets? Drug Discov. Today 21, 239–249 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  2. 2.

    Erlanson, D. A., McDowell, R. S. & O’Brien, T. Fragment-based drug discovery. J. Med. Chem. 47, 3463–3482 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  3. 3.

    Erlanson, D. A., Fesik, S. W., Hubbard, R. E., Jahnke, W. & Jhoti, H. Twenty years on: the impact of fragments on drug discovery. Nat. Rev. Drug Discov. 15, 605–619 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  4. 4.

    Yuen, L. H. & Franzini, R. M. Achievements, challenges, and opportunities in DNA-encoded library research: an academic point of view. ChemBioChem 18, 829–836 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  5. 5.

    Annis, D. A. et al. An affinity selection–mass spectrometry method for the identification of small molecule ligands from self-encoded combinatorial libraries: Discovery of a novel antagonist of E. coli dihydrofolate reductase. Int. J. Mass. Spectrom. 238, 77–83 (2004).

    CAS  Google Scholar 

  6. 6.

    Schreiber, S. L. A chemical biology view of bioactive small molecules and a binder-based approach to connect biology to precision medicines. Isr. J. Chem. 59, 52–59 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  7. 7.

    Toure, M. & Crews, C. M. Small-molecule PROTACS: new approaches to protein degradation. Angew. Chem. Int. Ed. Engl. 55, 1966–1973 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  8. 8.

    No Authors Listed. Retooling chemical probes. Nat. Chem. Biol. 6, 157 (2010).

    Article  CAS  Google Scholar 

  9. 9.

    Annis, D. A., Nickbarg, E., Yang, X., Ziebell, M. R. & Whitehurst, C. E. Affinity selection-mass spectrometry screening techniques for small molecule drug discovery. Curr. Opin. Chem. Biol. 11, 518–526 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  10. 10.

    Bergsdorf, C. & Ottl, J. Affinity-based screening techniques: their impact and benefit to increase the number of high quality leads. Expert Opin. Drug Discov. 5, 1095–1107 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  11. 11.

    Andrews, C. L., Ziebell, M. R., Nickbarg, E. & Yang, X. in Protein and Peptide Mass Spectrometry in Drug Discovery Ch. 10 (eds Gross, M. L., Chen G. & Pramanik, B. N.) 253–286 (Wiley, 2011).

  12. 12.

    Flusberg, D. A. et al. Identification of G-quadruplex-binding inhibitors of Myc expression through affinity selection–mass spectrometry. SLAS Discov. 24, 142–157 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Zehender, H., Le Goff, F., Lehmann, N., Filipuzzi, I. & Mayr, L. M. SpeedScreen: the “missing link” between genomics and lead discovery. J. Biomol. Screen. 9, 498–505 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  14. 14.

    Zehender, H. & Mayr, L. M. Application of high-throughput affinity-selection mass spectrometry for screening of chemical compound libraries in lead discovery. Expert Opin. Drug Discov. 2, 285–294 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  15. 15.

    Annis, A., Chuang, C.-C. & Nazef, N. in Mass Spectrometry in Medicinal Chemistry Ch. 3 (eds Wanner, K. T. & Höfner, G.) (Wiley, 2007).

  16. 16.

    Comess, K. M. et al. An ultraefficient affinity-based high-throughput screening process: application to bacterial cell wall biosynthesis enzyme MurF. J. Biomol. Screen. 11, 743–754 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  17. 17.

    Comess, K. M. et al. Kinase drug discovery by affinity selection/mass spectrometry (ASMS): application to DNA damage checkpoint kinase Chk1. J. Biomol. Screen. 11, 755–764 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  18. 18.

    Schriemer, D. C., Bundle, D. R., Li, L. & Hindsgaul, O. Micro-scale frontal affinity chromatography with mass spectrometric detection: a new method for the screening of compound libraries. Angew. Chem. Int. Ed. 37, 3383–3387 (1999).

    Article  Google Scholar 

  19. 19.

    Slon-Usakiewicz, J. J., Ng, W., Dai, J. R., Pasternak, A. & Redden, P. R. Frontal affinity chromatography with MS detection (FAC-MS) in drug discovery. Drug Discov. Today 10, 409–416 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  20. 20.

    Rush, M. D., Walker, E. M., Burton, T. & van Breemen, R. B. Magnetic microbead affinity selection screening (MagMASS) of botanical extracts for inhibitors of 15-lipoxygenase. J. Nat. Prod. 79, 2898–2902 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Rush, M. D., Walker, E. M., Prehna, G., Burton, T. & van Breemen, R. B. Development of a magnetic microbead affinity selection screen (MagMASS) using mass spectrometry for ligands to the retinoid X receptor-α. J. Am. Soc. Mass. Spectrom. 28, 479–485 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  22. 22.

    Lu, Y. et al. Accelerating the throughput of affinity mass spectrometry-based ligand screening toward a G protein-coupled receptor. Anal. Chem. 91, 8162–8169 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. 23.

    Qin, S. et al. High-throughput identification of G protein-coupled receptor modulators through affinity mass spectrometry screening. Chem. Sci. 9, 3192–3199 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. 24.

    Chen, X. et al. Identification of inhibitors of the antibiotic-resistance target New Delhi metallo-β-lactamase 1 by both nanoelectrospray ionization mass spectrometry and ultrafiltration liquid chromatography/mass spectrometry approaches. Anal. Chem. 85, 7957–7965 (2013).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  25. 25.

    Chen, X. et al. A ligand-observed mass spectrometry approach integrated into the fragment based lead discovery pipeline. Sci. Rep. 5, 8361 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. 26.

    VanderPorten, E. C., Scholle, M. D., Sherrill, J., Tran, J. C. & Liu, Y. Identification of small-molecule noncovalent binders utilizing SAMDI technology. SLAS Discov. 22, 1211–1217 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Qin, S. et al. Multiple ligand detection and affinity measurement by ultrafiltration and mass spectrometry analysis applied to fragment mixture screening. Anal. Chim. Acta 886, 98–106 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  28. 28.

    Fu, X. et al. Novel chemical ligands to Ebola virus and Marburg virus nucleoproteins identified by combining affinity mass spectrometry and metabolomics approaches. Sci. Rep. 6, 29680 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Siu, T. et al. Discovery of a novel cGAMP competitive ligand of the inactive form of STING. ACS Med. Chem. Lett. 10, 92–97 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Petrilli, W. L. et al. From screening to targeted degradation: strategies for the discovery and optimization of small molecule ligands for PCSK9. Cell Chem. Biol. 27, 32–40 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  31. 31.

    Valeur, E. et al. New modalities for challenging targets in drug discovery. Angew. Chem. Int. Ed. Engl. 56, 10294–10323 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  32. 32.

    Shoichet, B. K. Virtual screening of chemical libraries. Nature 432, 862–865 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33.

    Zhang, T. et al. Definitive metabolite identification coupled with automated ligand identification system (ALIS) technology: a novel approach to uncover structure–activity relationships and guide drug design in a factor IXa inhibitor program. J. Med. Chem. 59, 1818–1829 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  34. 34.

    Zhang, B. et al. A novel G protein-biased and subtype-selective agonist for a G protein-coupled receptor discovered from screening herbal extracts. ACS Cent. Sci. 6, 213–225 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. 35.

    Annis, D. A. et al. Inhibitors of the lipid phosphatase SHIP2 discovered by high throughput affinity selection-mass spectrometry screening of combinatorial libraries. Comb. Chem. High Throughput Screen. 12, 760–771 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Zhang, H. Acoustic dispensing-mass spectrometry: the next high throughput bioanalytical platform for early drug discovery. Bioanalysis 9, 1619–1621 (2017).

    PubMed  Article  CAS  Google Scholar 

  37. 37.

    Jenkins, J. & Cook, M. Mosquito®: An accurate nanoliter dispensing technology. JALA 9, 257–261 (2004).

    CAS  Google Scholar 

  38. 38.

    Makara, G. M., Nash, H., Zheng, Z., Orminati, J. P. A. & Wintner, E. A. A reagent-based strategy for the design of large combinatorial libraries: a preliminary experimental validation. Mol. Divers. 7, 3–14 (2003).

    CAS  PubMed  Article  Google Scholar 

  39. 39.

    Gesmundo, N. J. et al. Nanoscale synthesis and affinity ranking. Nature 557, 228–232 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  40. 40.

    Kumar, K. & Waldmann, H. Synthesis of natural product inspired compound collections. Angew. Chem. Int. Ed. 48, 3224–3242 (2009).

    CAS  Article  Google Scholar 

  41. 41.

    Nelson, A. & Roche, D. Innovative approaches to the design and synthesis of small molecule libraries. Bioorg. Med. Chem. 23, 2613 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  42. 42.

    Oprea, T. I., Davis, A. M., Teague, S. J. & Leeson, P. D. Is there a difference between leads and drugs? A historical perspective. J. Chem. Inf. Comput. Sci. 41, 1308–1315 (2001).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  43. 43.

    Polinsky, A. in The Practice of Medicinal Chemistry 3rd edn (ed. Wermuth, C. G.) 244–254 (Elsevier, 2008).

  44. 44.

    MacArrón, R. & Luengo, J. I. Yin and Yang in medicinal chemistry: what does drug-likeness mean? Future Med. Chem. 3, 505–507 (2011).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  45. 45.

    Oprea, T. I. Current trends in lead discovery: are we looking for the appropriate properties? Mol. Divers. 5, 199–208 (2000).

    CAS  Article  Google Scholar 

  46. 46.

    Lipinski, C. A., Lombardo, F., Dominy, B. W. & Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 46, 3–25 (2012).

    Article  Google Scholar 

  47. 47.

    Lipinski, C. A. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov. Today Technol. 1, 337–341 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  48. 48.

    Kuenemann, M. A., Labbé, C. M., Cerdan, A. H. & Sperandio, O. Imbalance in chemical space: how to facilitate the identification of protein–protein interaction inhibitors. Sci. Rep. 6, 23815 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49.

    Ran, X. & Gestwicki, J. E. Inhibitors of protein–protein interactions (PPIs): an analysis of scaffold choices and buried surface area. Curr. Opin. Chem. Biol. 44, 75–86 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  50. 50.

    Doak, B. C., Zheng, J., Dobritzsch, D. & Kihlberg, J. How beyond rule of 5 drugs and clinical candidates bind to their targets. J. Med. Chem. 59, 2312–2327 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  51. 51.

    Wilson, A. J. Inhibition of protein–protein interactions using designed molecules. Chem. Soc. Rev. 38, 3289–3300 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  52. 52.

    Lovering, F., Bikker, J. & Humblet, C. Escape from flatland: Increasing saturation as an approach to improving clinical success. J. Med. Chem. 52, 6752–6756 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  53. 53.

    Quartararo, A. J. et al. Ultra-large chemical libraries for the discovery of high-affinity peptide binders. Nat. Commun. 11, 3183 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. 54.

    Lam, K. S. et al. A new type of synthetic peptide library for identifying ligand-binding activity. Nature 354, 82–84 (1991).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  55. 55.

    Furka, Á., Sebestyén, F., Asgedom, M. & Dibó, G. General method for rapid synthesis of multicomponent peptide mixtures. Int. J. Pept. Protein Res. 37, 487–493 (1991).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  56. 56.

    Fu, Y. et al. Affinity selection-based two-dimensional chromatography coupled with high-performance liquid chromatography-mass spectrometry for discovering xanthine oxidase inhibitors from Radix Salviae Miltiorrhizae. Anal. Bioanal. Chem. 406, 4987–4995 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  57. 57.

    Fei, F. et al. Rapid screening and identification of bioactive compounds specifically binding to beta 2-adrenoceptor from San-ao decoction using affinity magnetic fine particles coupled with high-performance liquid chromatography–mass spectrometry. Chin. Med. 13, 49 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  58. 58.

    Sun, Y. et al. Ultrafiltration tandem mass spectrometry of estrogens for characterization of structure and affinity for human estrogen receptors. J. Am. Soc. Mass. Spectrom. 16, 271–279 (2005).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  59. 59.

    Wang, Z. et al. Efficient ligand discovery from natural herbs by integrating virtual screening, affinity mass spectrometry and targeted metabolomics. Analyst 144, 2881–2890 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  60. 60.

    Malmqvist, M. BIACORE: an affinity biosensor system for characterization of biomolecular interactions. Biochem. Soc. Trans. 27, 335–340 (1999).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  61. 61.

    Rich, R. L. & Myszka, D. G. Advances in surface plasmon resonance biosensor analysis. Curr. Opin. Biotechnol. 11, 54–61 (2000).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  62. 62.

    Comess, K. M. et al. Discovery and characterization of non-ATP site inhibitors of the mitogen activated protein (MAP) kinases. ACS Chem. Biol. 6, 234–244 (2011).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  63. 63.

    Su, H.-P. et al. Structural characterization of nonactive site, TrkA-selective kinase inhibitors. Proc. Natl Acad. Sci. USA 114, E297–E306 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  64. 64.

    Song, X. S. et al. Identification of DGAT2 inhibitors using mass spectrometry. J. Biomol. Screen. 21, 117–126 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  65. 65.

    Walker, S. S. et al. Affinity selection–mass spectrometry identifies a novel antibacterial RNA polymerase inhibitor. ACS Chem. Biol. 12, 1346–1352 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  66. 66.

    Coburn, C. A. et al. Identification of a small molecule nonpeptide active site β-secretase inhibitor that displays a nontraditional binding mode for aspartyl proteases. J. Med. Chem. 47, 6117–6119 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  67. 67.

    Pantoliano, M. W. et al. Large increases in general stability for subtilisin BPN′ through incremental changes in the free energy of unfolding. Biochemistry 28, 7205–7213 (1989).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  68. 68.

    Brown, N. et al. A chemoinformatics analysis of hit lists obtained from high-throughput affinity-selection screening. J. Biomol. Screen. 11, 123–130 (2006).

    PubMed  Article  PubMed Central  Google Scholar 

  69. 69.

    Feng, B. Y. & Shoichet, B. K. A detergent-based assay for the detection of promiscuous inhibitors. Nat. Protoc. 1, 550–553 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  70. 70.

    Jadhav, A. et al. Quantitative analyses of aggregation, autofluorescence, and reactivity artifacts in a screen for inhibitors of a thiol protease. J. Med. Chem. 53, 37–51 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  71. 71.

    Whitehurst, C. E. et al. Application of affinity selection-mass spectrometry assays to purification and affinity-based screening of the chemokine receptor CXCR4. Comb. Chem. High Throughput Screen. 15, 473–485 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  72. 72.

    Whitehurst, C. E. et al. Discovery and characterization of orthosteric and allosteric muscarinic M2 acetylcholine receptor ligands by affinity selection–mass spectrometry. J. Biomol. Screen. 11, 194–207 (2006).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  73. 73.

    Gabriel, J., Höfner, G. & Wanner, K. T. A library screening strategy combining the concepts of MS binding assays and affinity selection mass spectrometry. Front. Chem. 7, 665 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  74. 74.

    Igonet, S. et al. Enabling STD-NMR fragment screening using stabilized native GPCR: a case study of adenosine receptor. Sci. Rep. 8, 8142 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  75. 75.

    Matsui, M. & Corey, D. R. Non-coding RNAs as drug targets. Nat. Rev. Drug Discov. 16, 167–179 (2017).

    CAS  PubMed  Article  Google Scholar 

  76. 76.

    Rizvi, N. F. et al. Discovery of selective RNA-binding small molecules by affinity-selection mass spectrometry. ACS Chem. Biol. 13, 820–831 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  77. 77.

    Rizvi, N. F. et al. Targeting RNA with small molecules: identification of selective, RNA-binding small molecules occupying drug-like chemical space. SLAS Discov. 25, 384–396 (2020).

    CAS  PubMed  Google Scholar 

  78. 78.

    Petersen, D. N. et al. A small-molecule anti-secretagogue of PCSK9 targets the 80S ribosome to inhibit PCSK9 protein translation. Cell Chem. Biol. 23, 1362–1371 (2016).

    CAS  PubMed  Article  Google Scholar 

  79. 79.

    Maria, J. P. S. et al. Linking high-throughput screens to identify MoAs and novel inhibitors of Mycobacterium tuberculosis dihydrofolate reductase. ACS Chem. Biol. 12, 2448–2456 (2017).

    Article  CAS  Google Scholar 

  80. 80.

    Yang, X.-X. et al. Development of a mitochondria-based centrifugal ultrafiltration/liquid chromatography/mass spectrometry method for screening mitochondria-targeted bioactive constituents from complex matrixes: herbal medicines as a case study. J. Chromatogr. A 1413, 33–46 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  81. 81.

    Tao, Y., Yan, J. & Cai, B. Label-free bio-affinity mass spectrometry for screening and locating bioactive molecules. Mass Spectrom. Rev. https://doi.org/10.1002/mas.21613 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  82. 82.

    Kutilek, V. D. et al. Integration of affinity selection–mass spectrometry and functional cell-based assays to rapidly triage druggable target space within the NF-κB pathway. J. Biomol. Screen. 21, 608–619 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  83. 83.

    Motoyaji, T. Revolution of small molecule drug discovery by affinity selection-mass spectrometry technology. Chem. Pharm. Bull. 68, 191–193 (2020).

    CAS  Article  Google Scholar 

  84. 84.

    Salcius, M. et al. SEC-TID: a label-free method for small-molecule target identification. J. Biomol. Screen. 19, 917–927 (2014).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  85. 85.

    McMillan, E. A. et al. Chemistry-first approach for nomination of personalized treatment in lung cancer. Cell. 173, 864–878 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  86. 86.

    Musetti, C. et al. High-throughput assessment of structural continuity in biologics. Anal. Chem. 90, 2970–2975 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  87. 87.

    Wei, J. N., Belanger, D., Adams, R. P. & Sculley, D. Rapid prediction of electron-ionization mass spectrometry using neural networks. ACS Cent. Sci. 5, 700–708 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  88. 88.

    Domingo-Almenara, X. et al. The METLIN small molecule dataset for machine learning-based retention time prediction. Nat. Commun. 10, 5811 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  89. 89.

    Boström, J., Brown, D. G., Young, R. J. & Keserü, G. M. Expanding the medicinal chemistry synthetic toolbox. Nat. Rev. Drug Discov. 10, 709–727 (2018).

    Article  CAS  Google Scholar 

  90. 90.

    Piper, D. E. et al. The crystal structure of PCSK9: a regulator of plasma LDL-cholesterol. Structure 15, 545–552 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  91. 91.

    Dai, J. et al. Structure of the intramolecular human telomeric G-quadruplex in potassium solution: a novel adenine triple formation. Nucleic Acids Res. 35, 2440–2450 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  92. 92.

    Howe, J. A. et al. Selective small-molecule inhibition of an RNA structural element. Nature 526, 672–677 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  93. 93.

    Klaholz, B. P. et al. Structure of the Escherichia coli ribosomal termination complex with release factor 2. Nature 421, 90–94 (2003).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank Calixar for their generous gift of purified native target to investigate the A2AR receptor.

Author information

Affiliations

Authors

Contributions

All authors contributed equally to the preparation of this manuscript.

Corresponding author

Correspondence to Didier Roche.

Ethics declarations

Competing interests

J.-Y.O. and D.R. are cofounders, and R.P. is an employee of Edelris SAS, which has developed the commercial AS-MS service ‘EDEN platform’.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Prudent, R., Annis, D.A., Dandliker, P.J. et al. Exploring new targets and chemical space with affinity selection-mass spectrometry. Nat Rev Chem (2020). https://doi.org/10.1038/s41570-020-00229-2

Download citation

Search

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing