Say the word “scientist,” and many people will imagine researchers with wild hair and white lab coats, stirring beakers of bubbling chemicals. Trying and failing, trying and failing, trying and failing. Then, one day, eureka! The scientist makes an accidental discovery and changes the world.
Even as a child, I disliked this cinematic image of science as discovery-by-mistake. I wanted a dependable, methodical process for moving from a clear goal to an anticipated outcome. As a math-based, rational science, physics attracted me, but so did medicine. No surprise, then, that my PhD is in molecular biophysics, which involves understanding how diseases and their treatments work not solely through observation, but also at a molecular level.
Today, thanks to predictive, physics-based software, modeling of molecular biophysics has made great advances. These advances are accelerating the race to find a vaccine for SARS-CoV-2, more commonly known as COVID-19.
Since the virus became a pandemic early in 2020, I have closely watched the publications and social media posts of scientists who are proving every day that the answers to this scourge lie not in trial and error, but in a deep understanding of the virus’s molecular structure.
3D molecular modeling has helped many of these scientists accelerate the journey from hypothesis to drug design by allowing them to visualize the virus’s structure, helping to move promising treatments to the clinical trials stage in record time.
The most important features of the virus structure are too small to be visible, even with an electron microscope, so the software models the virus’s key constituent proteins and displays those results as scientifically accurate 3D models. The models help scientists visualize the mechanics of how the virus attaches to its host and replicates, causing infection. Armed with this insight, scientists can then use data on known molecules to identify the compounds or biologics most likely to prevent infection.
Because scientific evidence is compelling, I often seek to re-prove to myself that the algorithms that drive these models are as good as they can be. COVID-19 has provided a powerful opportunity to test their prowess.
A TRAIL OF LOGIC
By January 2020, the virus had been sequenced, and several research institutes quickly provided experimental structures of some the COVID-19 proteins. I read every scientific paper I could find on what scientists know about SARS, the class of viruses that includes COVID-19, looking for clues to attacking the protein at the heart of how the virus works.
3D molecular modeling has helped many scientists accelerate the journey from hypothesis to drug design by allowing them to visualize the COVID virus’s structure.
My goal was to write a blog that would demonstrate how 3D modeling could help scientists who do not have access to structure-based drug design better understand key protein targets involved in the infection process, and how these insights could be used to identify existing drugs with potential to be rationally repurposed against SARS-Cov-2. Like many scientists in pharmaceutical, biotechnology and university research labs worldwide, I focused on the main 3C-like protease, a protein that is key in virus replication. Introducing a small molecule-inhibitor that could bind to the protease, at what is known as its “active site,” would prevent the virus from replicating. Protease inhibitors have played a similar role in HIV and HCV therapeutics, so this is a well-established strategy.
From a library of all 2,684 FDA-approved drugs, the software quickly identified a small number of potentially effective compounds; several of the top scoring compounds are currently undergoing clinical trial as COVID-19 treatments.
The pandemic has created a unique scientific collaborative environment, where scientists are quickly sharing their results. Before this, I might have waited years to see my hypothesis proven or disproven. A few weeks after publishing my blog, however, several pre-prints and papers were published, documenting promising experimental results on some of the same compounds identified by my virtual experiments.
In science, a few weeks is a remarkably short time, demonstrating the amazing speed at which progress against the virus is advancing.
Beyond treatments for those who have contracted COVID-19, developing a vaccine to prevent infection is critical to controlling this pandemic. Here again, structural biology has proven that it can play a central role in developing a vaccine that can induce broadly neutralizing immune responses.
The sequence of the spike protein that enables the virus to enter human cells was published in January by Chinese scientists, which enabled scientists from around the world to build 3D atomic-level models in impressively short amounts of time. These structures were then used to rationally design stable mutants that could be used as a vaccine. These atomistic models also are crucial in understanding which antibodies could prevent the virus from entering human cells.
As I dreamed all those years ago, these treatments are being developed by collaborating scientists who started not with a theory and a blind hope, but with a solid understanding of the virus protein’s molecular makeup.
Anne Goupil-Lamy is a Science Council Fellow with BIOVIA, the molecular modeling and simulation brand of Dassault Systèmes. She received her doctorate in molecular biophysics from the University of Pierre and Marie Curie in Paris. At BIOVIA, she was in charge of contract research for many years, and today, she helps scientists apply BIOVIA’s software to their work. She also is involved in her own research projects, collaborating with academic teams and regularly publishing in peer review journals.