The branch of medicine known as predictive therapeutics entails a variety of practices and tools that aim to predict the outcome of a treatment plan for a specific patient. One aspect of predictive therapeutics involves drug design, the development of novel pharmaceuticals. Drug design for viruses has captured recent attention because of the COVID-19 pandemic. Researchers were able to develop vaccines for the SARS-CoV-2 virus within months, far outpacing the speed of prior research [1]. Going forward, researchers are devising methods in anti-viral drug design to improve resilience against future viruses and viral strains.
One common approach is structure-based drug design, the creation of drug molecules based on known structures within a pathogen. By targeting the structures of specific viral proteins, researchers can design a drug that sterilizes or stunts the virus, effectively preventing its spread. For example, given information about the structure of HIV virions, researchers developed inhibitors for the HIV protease enzyme, an essential component of the virus’s growth and replication [2]. Absent treatments, structure-based vaccines can offer their own benefits. Influenza viruses are known to exhibit “antigenic drift,” a phenomenon where one viral strain undergoes many small mutations, until vaccines and natural infections cannot effectively immunize against the newly mutated strain. In one case, drug designers developed a nanoparticle-based influenza vaccine that elicited a wide immune response, prompting the patient’s body to create antibodies for many influenza strains [3]. An alternative approach for vaccine design is to use “virus-like particles,” macromolecules that resemble viral structures but without any viral genes [4]. Overall, structure-based methods promise targeted drugs that exploit a pathogen’s known weaknesses or maximize a potential host’s immune response.
A parallel approach, called virtual screening, leans heavily on computational biology. Virtual screening involves the automated search for small molecules that bind to a drug target, like a viral enzyme [5]. In practice, virtual screening has uncovered novel inhibitors for influenza, HIV, hepatitis C, yellow fever, and more. Although researchers rarely use virtual screening to develop whole compounds, novel computational methods might help widen the search space and reduce the development time for drugs that target novel viruses.
These structure-based methods follow the pattern of “one bug/one drug”: researchers design one highly tailored drug for every new pathogen. However, this approach is limited to those viruses with known structures. By the time scientists become aware of a new virus, it might already have begun to spread, risking a larger outbreak. Some drug design methods extrapolate from known viral structures, targeting viral components that are (or might become) common across multiple strains of viruses. One example inhibits viral RNA polymerase, which blocks viral replication across many RNA-based viruses [6]. Another example induces apoptosis in cells containing viral double-stranded RNA [7]. After further research, if these “broad-spectrum antivirals” gain government approval and public adoption, they might curtail future outbreaks involving unknown viruses.
The COVID-19 pandemic has underscored the need for a fast response to novel infectious diseases, including in the area of drug design. Some methods emphasize the rapid development of a novel drug or vaccine when a virus is detected. Other methods propose the adoption of broader antivirals that target common weaknesses across many viruses, including strains that are today unknown or nonexistent. However, these methods come with risks. For one, upon increased exposure to novel drugs, viruses might acquire increased antiviral resistance, leading to a viral “superbug” that modern medicine cannot easily curtail. For another, viruses comprise a significant portion of the human microbiome [8]. Any broad-spectrum antiviral must be carefully tuned to target undesirable viruses without damaging the microbiome.
References
[1] Vaccines for COVID-19. Centers for Disease Control and Prevention. Retrieved from https://www.cdc.gov/coronavirus/2019-ncov/vaccines/index.html.
[2] N. E. Kohl, et al. Active Human Immunodeficiency Virus Protease is Required for Viral Infectivity. Proceedings of the National Academy of Sciences 1988; 85: 13. URL: https://www.pnas.org/content/pnas/85/13/4686.full.pdf.
[3] M. Kanekiyo, et al. Self-assembling Influenza Nanoparticle Vaccines Elicit Broadly Neutralizing H1N1 Antibodies. Nature 2013; 499. DOI:10.1038/nature12202.
[4] A. Roldão, et al. Virus-like Particles in Vaccine Development. Expert Review of Vaccines 2010; 9: 10. DOI:10.1586/erv.10.115.
[5] M. S. Murgueitio, et al. In Silico Virtual Screening Approaches for Anti-viral Drug Discovery. Drug Discovery Today: Technologies 2012; 9: 3. DOI:10.1016/j.ddtec.2012.07.009.
[6] Y. Furuta, et al. Favipiravir (T-705), a Novel Viral RNA Polymerase Inhibitor. Antiviral Research 2013; 100: 2. DOI:10.1016/j.antiviral.2013.09.015.
[7] T. H. Rider, et al. Broad-spectrum Antiviral Therapeutics. PLOS One 2011. DOI:10.1371/journal.pone.0022572.
[8] S. R. Abeles and D. T. Pride. Molecular Bases and Role of Viruses in the Human Microbiome. Journal of Molecular Biology 2014; 426: 23. DOI:10.1016/j.jmb.2014.07.002.
