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Computationally guided discovery of novel non-steroidal AR-GR dual antagonists demonstrating potency against antiandrogen resistance

Acta Pharmacologica Sinica volume 44, pages 1500–1518 (2023)Cite this article

Abstract

As a major class of medicine for treating the lethal type of castration-resistant prostate cancer (PCa), long-term use of androgen receptor (AR) antagonists commonly leads to antiandrogen resistance. When AR signaling pathway is blocked by AR-targeted therapy, glucocorticoid receptor (GR) could compensate for AR function especially at the late stage of PCa. AR-GR dual antagonist is expected to be a good solution for this situation. Nevertheless, no effective non-steroidal AR-GR dual antagonist has been reported so far. In this study, an AR-GR dual binder H18 was first discovered by combining structure-based virtual screening and biological evaluation. Then with the aid of computationally guided design, the AR-GR dual antagonist HD57 was finally identified with antagonistic activity towards both AR (IC50 = 0.394 μM) and GR (IC50 = 17.81 μM). Moreover, HD57 could effectively antagonize various clinically relevant AR mutants. Further molecular dynamics simulation provided more atomic insights into the mode of action of HD57. Our research presents an efficient and rational strategy for discovering novel AR-GR dual antagonists, and the new scaffold provides important clues for the development of novel therapeutics for castration-resistant PCa.

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Fig. 1: SBVS of AR and GR antagonists.
Fig. 2: H18 directly binds to AR and GR.
Fig. 3: Biological evaluation of the compound H18 identified by SBVS.
Fig. 4: MD simulations and key residues in the AR LBD and GR LBD for the binding of H18.
Fig. 5: Biological evaluation of H18 analogs.
Fig. 6: MD simulations and key residues in the AR LBD and GR LBD for the binding of HD57.
Fig. 7: Study on AR mutants.
Fig. 8: Regulation of AR LBD-ligand interactions by T877G and W741C mutations.

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References

  1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. Ca-Cancer J Clin. 2021;71:7–33.

    Article  PubMed  Google Scholar 

  2. Huggins C, Stevens RE, Hodges CV. Studies on prostate cancer II. The effects of castration on advanced carcinoma of the prostate gland. Arch Surg. 1941;43:209–23.

    Article  CAS  Google Scholar 

  3. Kumar R. Emerging role of glucocorticoid receptor in castration resistant prostate cancer: a potential therapeutic target. J Cancer. 2020;11:696–701.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Suh JH, Chattopadhyay A, Sieglaff DH, Storer Samaniego C, Cox MB, Webb P. Similarities and distinctions in actions of surface-directed and classic androgen receptor antagonists. PLoS One. 2015;10:e0137103.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Waltering KK, Urbanucci A, Visakorpi T. Androgen receptor (AR) aberrations in castration-resistant prostate cancer. Mol Cell Endocrinol. 2012;360:38–43.

    Article  CAS  PubMed  Google Scholar 

  6. Schmidt KT, Huitema ADR, Chau CH, Figg WD. Resistance to second-generation androgen receptor antagonists in prostate cancer. Nat Rev Urol. 2021;18:209–26.

    Article  CAS  PubMed  Google Scholar 

  7. Rice MA, Malhotra SV, Stoyanova T. Second-generation antiandrogens: from discovery to standard of care in castration resistant prostate cancer. Front Oncol. 2019;9:801.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Veldscholte J, Ris-Stalpers C, Kuiper GG, Jenster G, Berrevoets C, Claassen E, et al. A mutation in the ligand binding domain of the androgen receptor of human LNCaP cells affects steroid binding characteristics and response to anti-androgens. Biochem Biophys Res Commun. 1990;173:534–40.

    Article  CAS  PubMed  Google Scholar 

  9. Xie N, Cheng H, Lin D, Liu L, Yang O, Jia L, et al. The expression of glucocorticoid receptor is negatively regulated by active androgen receptor signaling in prostate tumors. Int J Cancer. 2015;136:E27–38.

    Article  CAS  PubMed  Google Scholar 

  10. Arora VK, Schenkein E, Murali R, Subudhi SK, Wongvipat J, Balbas MD, et al. Glucocorticoid receptor confers resistance to antiandrogens by bypassing androgen receptor blockade. Cell. 2013;155:1309–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Isikbay M, Otto K, Kregel S, Kach J, Cai Y, Vander Griend DJ, et al. Glucocorticoid receptor activity contributes to resistance to androgen-targeted therapy in prostate cancer. Horm Cancer. 2014;5:72–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Mitani Y, Lin SH, Pytynia KB, Ferrarotto R, El-Naggar AK. Reciprocal and autonomous glucocorticoid and androgen receptor activation in salivary duct carcinoma. Clin Cancer Res. 2020;26:1175–84.

    Article  CAS  PubMed  Google Scholar 

  13. Yemelyanov A, Czwornog J, Gera L, Joshi S, Chatterton RT Jr., Budunova I. Novel steroid receptor phyto-modulator compound a inhibits growth and survival of prostate cancer cells. Cancer Res. 2008;68:4763–73.

    Article  CAS  PubMed  Google Scholar 

  14. De Bosscher K, Vanden Berghe W, Beck IM, Van Molle W, Hennuyer N, Hapgood J, et al. A fully dissociated compound of plant origin for inflammatory gene repression. Proc Natl Acad Sci USA. 2005;102:15827–32.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Wu M, Xie Y, Cui X, Huang C, Zhang R, He Y, et al. Rational drug design for androgen receptor and glucocorticoids receptor dual antagonist. Eur J Med Chem. 2019;166:232–42.

    Article  CAS  PubMed  Google Scholar 

  16. Rosette C, Agan FJ, Rosette N, Mazzetti A, Moro L, Gerloni M. The dual androgen receptor and glucocorticoid receptor antagonist CB-03-10 as potential treatment for tumors that have acquired GR-mediated resistance to AR blockade. Mol Cancer Ther. 2020;19:2256–66.

    Article  CAS  PubMed  Google Scholar 

  17. Schoch GA, D’Arcy B, Stihle M, Burger D, Bar D, Benz J, et al. Molecular switch in the glucocorticoid receptor: active and passive antagonist conformations. J Mol Biol. 2010;395:568–77.

    Article  CAS  PubMed  Google Scholar 

  18. Hu X, Pang J, Zhang J, Shen C, Chai X, Wang E, et al. Discovery of novel GR ligands toward druggable GR antagonist conformations identified by MD simulations and Markov state model analysis. Adv Sci. 2022;9:e2102435.

    Article  Google Scholar 

  19. Case DC, Cheateham T, Darden T, Duke R, Giese T, Gohlke H, et al. AMBER 18. San Francisco: University of California; 2018.

  20. Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C. ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. J Chem Theory Comput. 2015;11:3696–713.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Wang JM, Wolf RM, Caldwell JW, Kollman PA, Case DA. Development and testing of a general amber force field. J Comput Chem. 2004;25:1157–74.

    Article  CAS  PubMed  Google Scholar 

  22. Pang JP, Hu XP, Wang YX, Liao JN, Chai X, Wang XW, et al. Discovery of a novel nonsteroidal selective glucocorticoid receptor modulator by virtual screening and bioassays. Acta Pharmacol Sin. 2022;43:2429–38.

  23. Gotz AW, Williamson MJ, Xu D, Poole D, Le Grand S, Walker RC. Routine microsecond molecular dynamics simulations with AMBER on GPUs. 1. Generalized born. J Chem Theory Comput. 2012;8:1542–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Lambrakos SG, Boris JP, Oran ES, Chandrasekhar I, Nagumo M. A modified shake algorithm for maintaining rigid bonds in molecular-dynamics simulations of large molecules. J Comput Phys. 1989;85:473–86.

    Article  Google Scholar 

  25. Sun H, Duan L, Chen F, Liu H, Wang Z, Pan P, et al. Assessing the performance of MM/PBSA and MM/GBSA methods. 7. Entropy effects on the performance of end-point binding free energy calculation approaches. Phys Chem Chem Phys. 2018;20:14450–60.

    Article  CAS  PubMed  Google Scholar 

  26. Wang E, Weng G, Sun H, Du H, Zhu F, Chen F, et al. Assessing the performance of the MM/PBSA and MM/GBSA methods. 10. Impacts of enhanced sampling and variable dielectric model on protein-protein Interactions. Phys Chem Chem Phys. 2019;21:18958–69.

    Article  CAS  PubMed  Google Scholar 

  27. Wang EC, Sun HY, Wang JM, Wang Z, Liu H, Zhang JZH, et al. End-point binding free energy calculation with MM/PBSA and MM/GBSA: strategies and applications in drug design. Chem Rev. 2019;119:9478–508.

    Article  CAS  PubMed  Google Scholar 

  28. Hou T, Wang J, Li Y, Wang W. Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking. J Comput Chem. 2011;32:866–77.

    Article  CAS  PubMed  Google Scholar 

  29. Onufriev A, Bashford D, Case DA. Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins. 2004;55:383–94.

    Article  CAS  PubMed  Google Scholar 

  30. Zhou W, Duan M, Fu W, Pang J, Tang Q, Sun H, et al. Discovery of novel androgen receptor ligands by structure-based virtual screening and bioassays. Genom Proteom Bioinform. 2018;16:416–27.

    Article  Google Scholar 

  31. Chai X, Sun H, Zhou W, Chen C, Shan L, Yang Y, et al. Discovery of N-(4-(Benzyloxy)-phenyl)-sulfonamide derivatives as novel antagonists of the human androgen receptor targeting the activation function 2. J Med Chem. 2022;65:2507–21.

    Article  CAS  PubMed  Google Scholar 

  32. Sun C, Shi Y, Xu LL, Nageswararao C, Davis LD, Segawa T, et al. Androgen receptor mutation (T877A) promotes prostate cancer cell growth and cell survival. Oncogene. 2006;25:3905–13.

    Article  CAS  PubMed  Google Scholar 

  33. Paul N, Carabet LA, Lallous N, Yamazaki T, Gleave ME, Rennie PS, et al. Cheminformatics modeling of adverse drug responses by clinically relevant mutants of human androgen receptor. J Chem Inform Model. 2016;56:2507–16.

    Article  CAS  Google Scholar 

  34. Hara T, Miyazaki J, Araki H, Yamaoka M, Kanzaki N, Kusaka M, et al. Novel mutations of androgen receptor: a possible mechanism of bicalutamide withdrawal syndrome. Cancer Res. 2003;63:149–53.

    CAS  PubMed  Google Scholar 

  35. Korpal M, Korn JM, Gao X, Rakiec DP, Ruddy DA, Doshi S, et al. An F876L mutation in androgen receptor confers genetic and phenotypic resistance to MDV3100 (enzalutamide). Cancer Discov. 2013;3:1030–43.

    Article  CAS  PubMed  Google Scholar 

  36. Joseph JD, Lu N, Qian J, Sensintaffar J, Shao G, Brigham D, et al. A clinically relevant androgen receptor mutation confers resistance to second-generation antiandrogens enzalutamide and ARN-509. Cancer Discov. 2013;3:1020–9.

    Article  CAS  PubMed  Google Scholar 

  37. Liu N, Zhou W, Guo Y, Wang J, Fu W, Sun H, et al. Molecular dynamics simulations revealed the regulation of ligands to the interactions between androgen receptor and its coactivator. J Chem Inform Model. 2018;58:1652–61.

    Article  CAS  Google Scholar 

  38. Hu X, Chai X, Wang X, Duan M, Pang J, Fu W, et al. Advances in the computational development of androgen receptor antagonists. Drug Discov Today. 2020;25:1453–61.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This research was supported by National Key R&D Program of China (2019YFE0111300), National Natural Science Foundation of China (22220102001, 22273049), and Zhejiang Provincial Natural Science Foundation of China (LD22H300001).

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Author notes

  1. These authors contributed equally: Xin Chai, Xue-ping Hu

Authors and Affiliations

  1. Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China

    Xin Chai, Xin-yue Wang, Hua-ting Wang, Jin-ping Pang, Wen-fang Zhou, Jia-ning Liao, Ting-jun Hou & Dan Li

  2. Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, Zhejiang, China

    Xin Chai & Hong-guang Xia

  3. Institute of Molecular Sciences and Engineering, Institute of Frontier and Interdisciplinary Science, Shandong University, Qingdao, 266237, Shandong, China

    Xue-ping Hu

  4. Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China

    Lu-hu Shan & Xiao-hong Xu

  5. Department of Biochemistry & Research Center of Clinical Pharmacy of The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China

    Lei Xu

  6. Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China

    Hong-guang Xia

  7. Jinhua Institute of Zhejiang University, Jinhua, 321099, Zhejiang, China

    Dan Li

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Contributions

DL, TJH, and HGX initiated and supervised the research. XC and XH conducted virtual screening, compound validations and biological assays. XYW, HTW, JPP, JNL, LHS, XHX, and LX performed part of in vitro experiments and interpreted part of the data. WFZ performed part of in silico experiments. XC, XPH, TJH, and DL wrote the manuscript, and other authors contributed specific parts of the manuscript. HGX, TJH, and DL assume responsibility for the manuscript in its entirety. All authors have given approval to the final version of the manuscript.

Corresponding authors

Correspondence to Hong-guang Xia, Ting-jun Hou or Dan Li.

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Chai, X., Hu, Xp., Wang, Xy. et al. Computationally guided discovery of novel non-steroidal AR-GR dual antagonists demonstrating potency against antiandrogen resistance. Acta Pharmacol Sin 44, 1500–1518 (2023). https://doi.org/10.1038/s41401-022-01038-7

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