Download PDF
CC BY 4.0 · Pharmaceutical Fronts 2025; 07(01): e1-e8
DOI: 10.1055/a-2523-2174
Review Article

Undeveloped Region in Target-Strategies and Potential in Antiviral Drug Discovery

Shaoqing Du
1   Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
,
Xinyong Liu
1   Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
,
Xueping Hu
2   Institute of Frontier Chemistry, School of Chemistry and Chemical Engineering, Shandong University, Qingdao, People's Republic of China
,
Peng Zhan
1   Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, People's Republic of China
› Author Affiliations Funding This work was supported by the National Natural Science Foundation of China (Grant Nos. 22208191, 22273049), the Development Plan for Youth Innovation Team of Shandong Province (Grant No. 2023KJ011), the Major Basic Research Project of Shandong Provincial Natural Science Foundation (Grant No. ZR2021ZD17), and the Science Foundation for Outstanding Young Scholars of Shandong Province (Grant No. ZR2020JQ31).
› Further Information
Also available at
   Permissions and Reprints

Abstract

Drug resistance is a looming threat to global health security, undermining the effectiveness of current treatments and increasing treatment failures. To address this challenge, it is necessary to explore innovative strategies by identifying new binding mechanisms and targeting previously undeveloped therapeutic avenues. This paper reviewed the potential of leveraging undeveloped domains to combat drug resistance and proposes a range of methodologies to accurately identify those specific targets. There is also an extensive review of the challenges associated with targeting undeveloped areas and strategies to effectively address them. In this process, the application of artificial intelligence (AI) can effectively improve the efficiency of drug design, while appropriate attention should be paid to the physicochemical and drug-like properties of pharmaceutical compounds in the realm of drug discovery. Given the above, focusing on these undeveloped areas could provide a promising pathway to address drug resistance; however, achieving this objective necessitates sustained investigative efforts and inventive approaches.

Keywords

drug resistance - targeting undeveloped sites - antiviral drug design - target-based drug discovery


Publication History

Received: 29 September 2024

Accepted: 23 January 2025

Article published online:
24 February 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

 

  • References

  • 1 Clavel F, Hance AJ. HIV drug resistance. N Engl J Med 2004; 350 (10) 1023-1035
    CrossrefPubMedSearch in Google Scholar
  • 2 Andino R, Domingo E. Viral quasispecies. Virology 2015; 479-480: 46-51
    CrossrefPubMedSearch in Google Scholar
  • 3 Margeridon-Thermet S, Shulman NS, Ahmed A. et al. Ultra-deep pyrosequencing of hepatitis B virus quasispecies from nucleoside and nucleotide reverse-transcriptase inhibitor (NRTI)-treated patients and NRTI-naive patients. J Infect Dis 2009; 199 (09) 1275-1285
    CrossrefPubMedSearch in Google Scholar
  • 4 Du S, Hu X, Menéndez-Arias L, Zhan P, Liu X. Target-based drug design strategies to overcome resistance to antiviral agents: opportunities and challenges. Drug Resist Updat 2024; 73: 101053
    CrossrefPubMedSearch in Google Scholar
  • 5 Du J, Guo J, Kang D. et al. New techniques and strategies in drug discovery. Chin Chem Lett 2020; 31 (07) 1695-1708
    CrossrefSearch in Google Scholar
  • 6 Jiang X, Yu J, Zhou Z. et al. Molecular design opportunities presented by solvent-exposed regions of target proteins. Med Res Rev 2019; 39 (06) 2194-2238
    CrossrefPubMedSearch in Google Scholar
  • 7 Wang X, Wang YQ, Zhang Q, Yi CQ, Wang XQ. Research progress in cellular pharmacokinetics of nano-drug delivery systems. Yao Xue Xue Bao 2018; 53 (10) 1620-1629
    Search in Google Scholar
  • 8 Lu L, Su S, Yang H, Jiang S. Antivirals with common targets against highly pathogenic viruses. Cell 2021; 184 (06) 1604-1620
    CrossrefPubMedSearch in Google Scholar
  • 9 Wang J, Li F, Ma C. Recent progress in designing inhibitors that target the drug-resistant M2 proton channels from the influenza A viruses. Biopolymers 2015; 104 (04) 291-309
    CrossrefPubMedSearch in Google Scholar
  • 10 Hong M, DeGrado WF. Structural basis for proton conduction and inhibition by the influenza M2 protein. Protein Sci 2012; 21 (11) 1620-1633
    CrossrefPubMedSearch in Google Scholar
  • 11 Furuse Y, Suzuki A, Kamigaki T, Oshitani H. Evolution of the M gene of the influenza A virus in different host species: large-scale sequence analysis. Virol J 2009; 6: 67
    CrossrefPubMedSearch in Google Scholar
  • 12 Furuse Y, Suzuki A, Oshitani H. Large-scale sequence analysis of M gene of influenza A viruses from different species: mechanisms for emergence and spread of amantadine resistance. Antimicrob Agents Chemother 2009; 53 (10) 4457-4463
    CrossrefPubMedSearch in Google Scholar
  • 13 Gu RX, Liu LA, Wang YH, Xu Q, Wei DQ. Structural comparison of the wild-type and drug-resistant mutants of the influenza A M2 proton channel by molecular dynamics simulations. J Phys Chem B 2013; 117 (20) 6042-6051
    CrossrefPubMedSearch in Google Scholar
  • 14 Wang J, Wu Y, Ma C. et al. Structure and inhibition of the drug-resistant S31N mutant of the M2 ion channel of influenza A virus. Proc Natl Acad Sci U S A 2013; 110 (04) 1315-1320
    CrossrefPubMedSearch in Google Scholar
  • 15 Moghadasi SA, Heilmann E, Khalil AM. et al. Transmissible SARS-CoV-2 variants with resistance to clinical protease inhibitors. Sci Adv 2023; 9 (13) eade8778
    CrossrefPubMedSearch in Google Scholar
  • 16 Kang D, Fang Z, Li Z. et al. Design, synthesis, and evaluation of thiophene[3,2-d]pyrimidine derivatives as HIV-1 non-nucleoside reverse transcriptase inhibitors with significantly improved drug resistance profiles. J Med Chem 2016; 59 (17) 7991-8007
    CrossrefPubMedSearch in Google Scholar
  • 17 Bauman JD, Patel D, Dharia C. et al. Detecting allosteric sites of HIV-1 reverse transcriptase by X-ray crystallographic fragment screening. J Med Chem 2013; 56 (07) 2738-2746
    CrossrefPubMedSearch in Google Scholar
  • 18 Frey KM, Bollini M, Mislak AC. et al. Crystal structures of HIV-1 reverse transcriptase with picomolar inhibitors reveal key interactions for drug design. J Am Chem Soc 2012; 134 (48) 19501-19503
    CrossrefPubMedSearch in Google Scholar
  • 19 Wang Z, Sharma PP, Rathi B. et al. Escaping from flatland: Multiparameter optimization leads to the discovery of novel tetrahydropyrido[4,3-d]pyrimidine derivatives as human immunodeficiency virus-1 non-nucleoside reverse transcriptase inhibitors with superior antiviral activities against non-nucleoside reverse transcriptase inhibitor-resistant variants and favorable drug-like profiles. J Med Chem 2023; 66 (13) 8643-8665
    CrossrefPubMedSearch in Google Scholar
  • 20 Lockbaum GJ, Rusere LN, Henes M. et al. HIV-1 protease inhibitors with a P1 phosphonate modification maintain potency against drug-resistant variants by increased interactions with flap residues. Eur J Med Chem 2023; 257: 115501
    CrossrefPubMedSearch in Google Scholar
  • 21 Cihlar T, He GX, Liu X. et al. Suppression of HIV-1 protease inhibitor resistance by phosphonate-mediated solvent anchoring. J Mol Biol 2006; 363 (03) 635-647
    CrossrefPubMedSearch in Google Scholar
  • 22 Yang J, Liu S, Du L, Jiang S. A new role of neuraminidase (NA) in the influenza virus life cycle: implication for developing NA inhibitors with novel mechanism of action. Rev Med Virol 2016; 26 (04) 242-250
    CrossrefPubMedSearch in Google Scholar
  • 23 Loregian A, Mercorelli B, Nannetti G, Compagnin C, Palù G. Antiviral strategies against influenza virus: towards new therapeutic approaches. Cell Mol Life Sci 2014; 71 (19) 3659-3683
    CrossrefPubMedSearch in Google Scholar
  • 24 McClellan K, Perry CM. Oseltamivir: a review of its use in influenza. Drugs 2001; 61 (02) 263-283
    CrossrefPubMedSearch in Google Scholar
  • 25 Dunn CJ, Goa KL. Zanamivir: a review of its use in influenza. Drugs 1999; 58 (04) 761-784
    CrossrefPubMedSearch in Google Scholar
  • 26 Russell RJ, Haire LF, Stevens DJ. et al. The structure of H5N1 avian influenza neuraminidase suggests new opportunities for drug design. Nature 2006; 443 (7107): 45-49
    CrossrefPubMedSearch in Google Scholar
  • 27 Han N, Mu Y. Plasticity of 150-loop in influenza neuraminidase explored by Hamiltonian replica exchange molecular dynamics simulations. PLoS One 2013; 8 (04) e60995
    CrossrefPubMedSearch in Google Scholar
  • 28 Xie Y, Xu D, Huang B. et al. Discovery of N-substituted oseltamivir derivatives as potent and selective inhibitors of H5N1 influenza neuraminidase. J Med Chem 2014; 57 (20) 8445-8458
    CrossrefPubMedSearch in Google Scholar
  • 29 Zhang J, Murugan NA, Tian Y. et al. Structure-based optimization of N-substituted oseltamivir derivatives as potent anti-influenza A virus agents with significantly improved potency against oseltamivir-resistant N1–H274Y variant. J Med Chem 2018; 61 (22) 9976-9999
    CrossrefPubMedSearch in Google Scholar
  • 30 Jia R, Zhang J, Bertagnin C. et al. Discovery of highly potent and selective influenza virus neuraminidase inhibitors targeting 150-cavity. Eur J Med Chem 2021; 212: 113097
    CrossrefPubMedSearch in Google Scholar
  • 31 Tan B, Zhang X, Ansari A. et al. Design of a SARS-CoV-2 papain-like protease inhibitor with antiviral efficacy in a mouse model. Science 2024; 383 (6690): 1434-1440
    CrossrefPubMedSearch in Google Scholar
  • 32 Qin B, Wu C, Zhao B. et al. Design, synthesis, and biological evaluation of 1,2,4-oxadiazole derivatives containing an aryl carboxylic acid moiety as potent sarbecovirus papain-like protease inhibitors. J Med Chem 2024; 67 (12) 10211-10232
    CrossrefPubMedSearch in Google Scholar
  • 33 Liu M, Li J, Liu W. et al. The S1′–S3′ pocket of the SARS-CoV-2 main protease is critical for substrate selectivity and can be targeted with covalent inhibitors. Angew Chem Int Ed Engl 2023; 62 (41) e202309657
    CrossrefPubMedSearch in Google Scholar
  • 34 Yang M, Lee MK, Gao S. et al. Miniaturized modular click chemistry-enabled rapid discovery of unique SARS-CoV-2 Mpro inhibitors with robust potency and drug-like profile. Adv Sci (Weinh) 2024; 11 (43) e2404884
    CrossrefPubMedSearch in Google Scholar
  • 35 Zuzic L, Samsudin F, Shivgan AT. et al. Uncovering cryptic pockets in the SARS-CoV-2 spike glycoprotein. Structure 2022; 30 (08) 1062-1074.e4
    CrossrefPubMedSearch in Google Scholar
  • 36 Lu S, Ji M, Ni D, Zhang J. Discovery of hidden allosteric sites as novel targets for allosteric drug design. Drug Discov Today 2018; 23 (02) 359-365
    CrossrefPubMedSearch in Google Scholar
  • 37 Chen L, Fan Z, Chang J. et al. Sequence-based drug design as a concept in computational drug design. Nat Commun 2023; 14 (01) 4217
    CrossrefPubMedSearch in Google Scholar
  • 38 Pun FW, Liu BHM, Long X. et al. Identification of therapeutic targets for amyotrophic lateral sclerosis using PandaOmics – An AI-enabled biological target discovery platform. Front Aging Neurosci 2022; 14: 914017
    CrossrefPubMedSearch in Google Scholar
  • 39 Tanaka D, Tsuda Y, Shiyama T. et al. A practical use of ligand efficiency indices out of the fragment-based approach: ligand efficiency-guided lead identification of soluble epoxide hydrolase inhibitors. J Med Chem 2011; 54 (03) 851-857
    CrossrefPubMedSearch in Google Scholar
  • 40 Kotesova S, Shenvi RA. Inner- and outer-sphere cross-coupling of high Fsp3 fragments. Acc Chem Res 2023; 56 (21) 3089-3098
    CrossrefPubMedSearch in Google Scholar
  • 41 Johnson TW, Gallego RA, Edwards MP. Lipophilic efficiency as an important metric in drug design. J Med Chem 2018; 61 (15) 6401-6420
    CrossrefPubMedSearch in Google Scholar
  • 42 Kneller DW, Li H, Phillips G. et al. Covalent narlaprevir- and boceprevir-derived hybrid inhibitors of SARS-CoV-2 main protease. Nat Commun 2022; 13 (01) 2268
    CrossrefPubMedSearch in Google Scholar
  • 43 Unoh Y, Uehara S, Nakahara K. et al. Discovery of S-217622, a noncovalent oral SARS-CoV-2 3CL protease inhibitor clinical candidate for treating COVID-19. J Med Chem 2022; 65 (09) 6499-6512
    CrossrefPubMedSearch in Google Scholar
  • 44 Lansdon EB, Brendza KM, Hung M. et al. Crystal structures of HIV-1 reverse transcriptase with etravirine (TMC125) and rilpivirine (TMC278): implications for drug design. J Med Chem 2010; 53 (10) 4295-4299
    CrossrefPubMedSearch in Google Scholar
  • 45 Gao X, Qin B, Chen P. et al. Crystal structure of SARS-CoV-2 papain-like protease. Acta Pharm Sin B 2021; 11 (01) 237-245
    CrossrefPubMedSearch in Google Scholar