Finding a Cure for Humanity’s Worst Nightmare — the Novel Coronavirus
A New Global Epidemic
“Coronavirus Live Updates: Fears of Global Spread as Cases Accelerate in Iran”
“The coronavirus just killed a 29-year-old doctor who postponed his wedding to fight the disease”
This is just a small sampling of some of the headlines of articles that have been published every hour of every day for the past few weeks.
In Yuval Noah Harari’s book Homo Deus, Yuval strongly emphasizes that humanity has surpassed primitive problems that involve epidemics, disease, war and massive instability, and that our future involves moving toward human divinity and an ultimate level of control over our lives through technological innovation.
But with headlines like those having come out, it looks like we might be going back to square one.
But there is a difference. When we faced the black plague in the 14th century, we were completely defenseless. We had to wait for centuries for the spreading to fade away, and ultimately it came down to luck. Pure luck. If it wasn’t for that luck, some of us might not be here today.
So there is a difference between now and then.
The Coronavirus Timeline
The Coronavirus started as nothing more than several pneumonia cases in China at the end of December. The fact is that the coronavirus (both the 2019-nCoV and previous strains) actually belong to the family of viruses that cause common colds.
But this time was different. Treatment didn’t seem to be helping conditions, and the WHO eventually identified the viral strain as a novel one.
This cascaded into alerts of viral symptoms coming from Thailand and Japan, and eventually, we realized that the virus had spread around the world — within the first few days after the globally reported cases, United States, Nepal, France, Australia, Malaysia, Singapore, South Korea, Vietnam and Taiwan all confirmed cases.
Are we entirely defenseless against the virus — probably not.
Options for Therapeutics
You’ve probably heard about the Coronavirus all over the news, and it deserves its place there as it’s spread to more than 25 countries and 40,000 people.
Nevertheless, the most important question remains. How are we currently attempting to both cure and prevent the disease?
When most people think of viruses, vaccines are what normally come to mind, but it’s important to realize the distinction between curing those who have already contracted the illness and preventing it from spreading.
When initially thinking about this problem, I could rattle off different technologies that we could use to solve this problem including gene editing and gene (oligo) therapy.
- Gene Editing: Using CRISPR Cas9 or other base editors to remove or modify genes.
- Gene Therapy: Using silencing RNAs called miRNAs/siRNAs to mark genes for degradation.
Interesting research is also being conducted in vaccine design as well. In fact, a few days ago, researchers at UT Austin were able to map the 3D atomic scale structure of the spike glycoprotein, a key structural feature of the 2019-nCoV.
Many of these solutions would likely be efficacious… but the main problem is that time is of the essence. Most of the solutions involving involving gene therapies and editing have not been optimized yet and while vaccines would buy us time in preventing the spread of the disease but wouldn’t actually cure it.
The most time-effective solution (cure) right now would involve creating small molecule drugs that bind into the pockets of selected drug targets.
With traditional drug development, we normally have to distill the potential drug candidates from a space of more than 10¹⁵ molecules, but since the coronavirus protein targets are very similar to the antiviral targets in SARS (Severe Acute Respiratory Syndrome), MERS (Middle East Respiratory Syndrome), and HIV, we can limit the space of the molecules that we need to search by finding variations of the molecules that already bind strongly to target proteins in the other strains of the coronavirus.
According to a recently published paper, potential targets of the coronavirus include non-structural proteins that play a key role in the viral life cycle, including …
- 3-chymotrypsin-like protease and papain-like protease: These are both enzymes in viruses that break down proteins.
- Helicase: These proteins play a key role in separating priming strands of RNA for transcription and subsequent translation into a product.
- RNA-dependent RNA polymerase: These proteins transcribe RNA from a pre-existing RNA template.
The obvious structural similarity with a low RMSD (root mean square deviation) allows us to use drugs that were efficacious for these viruses as a template.
In other words, by taking fragments of drugs that have strong binding affinities to the catalytic sites of both the SARS and MERS coronavirus strains and creating variations of these, we can very quickly generate numerous potential drug candidates for the 2019-nCOV.
If you think as the small molecule drug as a key and the protein targets as a lock, we’re generating variations or the ridges on the keys that cured SARS and MERS, so that we can fit previous drugs into the lock of the steel barrier of the coronavirus target!
In fact, this has already been done at a smaller scale by the NIH. Scientists were able to identify a drug Remdesivir that both significantly cured and prevented the spread of the illness in Rhesus Macaque monkeys. And they did this by repurposing and generating variations of an older drug called Alafenamide that acted as an HIV reverse transcriptase inhibitor (It basically inhibited the enzyme that allows HIV to reproduce!). The drug has very quickly moved into stage three clinical trials, which were initiated at the beginning of February.
Though it’s true that an infodemic full of fake news and false information is simultaneously occurring alongside the epidemic, putting all the noise aside, the factual information still remains: the coronavirus is spreading to countless countries beyond China, and death rates are higher than reported.
While efforts to develop efficient vaccines are underway, let’s do our best to develop life-saving cures. How though? The normal drug discovery process takes 1–2 decades and more than 3 billion dollars.
The past decades have been filled with fascination by technologies such as artificial intelligence and quantum computing.
I look forward to using machine learning LSTM models to generate potential novel drugs that could treat and cure patients!
Thanks for reading! Feel free to check out my other articles on Medium and connect with me on LinkedIn!
If you’d like to discuss any of the topics above, I’d love to get in touch with you! I’m actually currently trying to optimize ML models to make predictions about efficient drugs for coronavirus protein targets. Keep on the lookout for another article soon. (Send me an email at mukundh.murthy@icloud.com or message me on LinkedIn)
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