First-in-Class Small Molecule BTLA Inhibitors as Potential Cancer Therapies
Authors
Brian Kuo
Share
Annotation
Modern cancer treatments have developed to a great extent — however, various factors such as cancer types and resistance continue to make effective treatments difficult to create for many cancers. Among different cancer treatments, immunotherapy shows promise because of its utilization of one’s own body’s immune system in fighting off cancerous cells. Immune checkpoints instruct the body to stop producing anti-cancer cells, and blocking these checkpoints can be effective in reactivating an immune system. B and T Lymphocyte Attenuator (BTLA) is an immune checkpoint that shows promise as an immunotherapy target, but current clinical trials focus solely on large monoclonal antibodies that can have severe side effects and other limitations due to larger molecular size. By identifying small molecule BTLA inhibitors, the development of anti-cancer immunotherapy treatments could be vastly improved. In this paper I utilize a variety of experiments to virtually screen small molecules and identify potential BTLA inhibitors. First, I located suitable binding sites in BTLA using 3 different methods (geometric, energetic, and machine learning methods). I identified compounds using virtual screening in two different experiments, by identifying HVEM B-chain pharmacophore maps, then scanning the ZINC compound library for matches. Then, I verified the compounds’ site binding on BTLA with molecular docking in SwissDock. Finally, the druggability of the remaining compounds were evaluated twice, for drug properties and for toxicity, in SwissADME and ProTox 3.0 respectively. In the end, two promising compounds with favorable energetic interactions with BTLA, strong drug properties according to Lipinski’s rule, and low toxicity were identified as drug candidates for different applications, which hold potential for being pivotal milestones in the field of cancer therapy.
Keywords
Authors
Brian Kuo
Share
References:
Hossain MB, Haldar Neer AH. Chemotherapy. Cancer Treat Res. 2023;185:49-58.
Jaffray DA, Gospodarowicz MK. Radiation Therapy for Cancer. In: Gelband H, Jha P, Sankaranarayanan R, Horton S, editors. Cancer: Disease Control Priorities, Third Edition (Volume 3). Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2015 Nov 1. Chapter 14.
Bayat Mokhtari R, Homayouni TS, Baluch N, Morgatskaya E, Kumar S, Das B, Yeger H. Combination therapy in combating cancer. Oncotarget. 2017 Jun 6;8(23):38022-38043.
Barot S, Patel H, Yadav A, Ban I. Recent advancement in targeted therapy and role of emerging technologies to treat cancer. Med Oncol. 2023 Oct 7;40(11):324.
Esfahani K, Roudaia L, Buhlaiga N, Del Rincon SV, Papneja N, Miller WH Jr. A review of cancer immunotherapy: from the past, to the present, to the future. Curr Oncol. 2020 Apr;27(Suppl 2):S87-S97.
Shahid K., Khalife M., Dabney R., Phan A.T. Immunotherapy and targeted therapy—the new roadmap in cancer treatment. Ann. Transl. Med. 2019;7 doi: 10.21037/ATM.2019.05.58. 595–595.
Lee L, Gupta M, Sahasranaman S. Immune Checkpoint inhibitors: An introduction to the next-generation cancer immunotherapy. J Clin Pharmacol. 2016 Feb;56(2):157-69.
Zhang H, Dai Z, Wu W, Wang Z, Zhang N, Zhang L, Zeng WJ, Liu Z, Cheng Q. Regulatory mechanisms of immune checkpoints PD-L1 and CTLA-4 in cancer. J Exp Clin Cancer Res. 2021 Jun 4;40(1):184.
Padmanee Sharma, Bilal A. Siddiqui, Swetha Anandhan, Shalini S. Yadav, Sumit K. Subudhi, Jianjun Gao, Sangeeta Goswami, James P. Allison; The Next Decade of Immune Checkpoint Therapy. Cancer Discov 1 April 2021; 11 (4): 838–857.
Pilard C, Ancion M, Delvenne P, Jerusalem G, Hubert P, Herfs M. Cancer immunotherapy: it's time to better predict patients' response. Br J Cancer. 2021 Sep;125(7):927-938.
Sedy JR, Gavrieli M, Potter KG, Hurchla MA, Lindsley RC, Hildner K, et al. B and T lymphocyte attenuator regulates T cell activation through interaction with herpesvirus entry mediator. Nat Immunol. 2005;6(1):90–8.
Ning Z, Liu K, Xiong H. Roles of BTLA in Immunity and Immune Disorders. Front Immunol. 2021 Mar 29;12:654960
Watanabe N, Gavrieli M, Sedy JR, Yang J, Fallarino F, Loftin SK, et al. BTLA is a lymphocyte inhibitory receptor with similarities to CTLA-4 and PD-1. Nat Immunol. 2003;4(7):670–9.
Oya Y, Watanabe N, Owada T, Oki M, Hirose K, Suto A, et al. Development of autoimmune hepatitis-like disease and production of autoantibodies to nuclear antigens in mice lacking B and T lymphocyte attenuator. Arthritis Rheum. 2008;58(8):2498–510.
Andrzejczak, A., Karabon, L. BTLA biology in cancer: from bench discoveries to clinical potentials. Biomark Res 12, 8 (2024).
Qin, S., Xu, L., Yi, M. et al. Novel immune checkpoint targets: moving beyond PD-1 and CTLA-4. Mol Cancer 18, 155 (2019).
Schöning-Stierand, K.; Diedrich, K.; Ehrt, C.; Flachsenberg, F.; Graef, J.; Sieg, J.; Penner, P.; Poppinga, M.; Ungethüm, A.; Rarey, M. (2022). ProteinsPlus: a comprehensive collection of web-based molecular modeling tools. Nucleic Acids Research, 50:W611-W615.
Volkamer, A.; Griewel, A.; Grombacher, T.; Rarey, M., Analyzing the topology of active sites: on the prediction of pockets and subpockets. J Chem Inf Model 2010, 50 (11), 2041-52.
Kozakov D, Grove LE, Hall DR, Bohnuud T, Mottarella SE, Luo L, Xia B, Beglov D, Vajda S The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins Nature Protocols 2015 10(5):733-755.
Dávid Jakubec, Petr Škoda, Radoslav Krivák, Marian Novotný and David Hoksza. PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures. Nucleic Acids Research. May 2022.
David Ryan Koes, Carlos J. Camacho, Small-molecule inhibitor starting points learned from protein–protein interaction inhibitor structure, Bioinformatics, Volume 28, Issue 6, March 2012, Pages 784–791.
David Ryan Koes, Carlos J. Camacho, ZINCPharmer: pharmacophore search of the ZINC database, Nucleic Acids Research, Volume 40, Issue W1, 1 July 2012, Pages W409–W414.
Kufareva I, Abagyan R. Methods of protein structure comparison. Methods Mol Biol. 2012;857:231-57.
