Alfaisal UniversityComputational modelling for discovering antiviral treatments

Computational modelling for discovering antiviral treatments

 Antiviral treatments

Alfaisal University’s College of Science is using computational modelling and artificial intelligence in the search for clinical treatments for Covid-19

Science has made great strides in the race to end the Covid-19 pandemic. Amid a worldwide state of emergency, research processes have been accelerated through increased funding and cross-disciplinary collaboration.

The pandemic has proved the maxim that no large, complex problem can be tackled by one branch of science acting alone. From a standing start, RNA vaccines have been developed and approved within a year. While there is still much to learn about Covid-19 and how it responds to clinical treatments, there is no shortage of data for researchers to interrogate.

At Alfaisal University in Riyadh, Saudi Arabia, one physicist and materials scientist is making good use of this data pool. Dr Souraya Goumri-Said, an associate professor of physics, has a primary research focus in computational materials science. In the battle against Covid-19, she deploys quantum methods and molecular simulations to observe the docking between molecules at the most basic scale, building modelling systems to test the efficacy of antiviral drugs and other therapeutics.

“We are so lucky to have access to all this data,” says Dr Goumri-Said. “Computational materials scientists and computational researchers need data. During this pandemic, everyone is working together. We are open; we are opening our labs all over the world. Scientists are spreading information across the scientific communities – doctors, medical scientists, chemists, biophysicists. With Covid, we were lucky to have access to the structure of the RNA, and from this we have the protein, and this is what we are targeting.”

With new Covid-19 mutations appearing, finding effective treatments that will complement medicine’s arsenal of vaccines will be critical to minimising the impact of the virus. Dr Goumri-Said’s methodology looks at how the chemical structure of the virus is affected by a drug to discover how the latter might thwart the progress of the virus.

Antiviral drugs operate differently from vaccines; where the vaccine is developed to stop infection, the antiviral is used once infection has been established, targeting specific proteins in the virus to inhibit its propagation through the body. 

“We are selecting structures and trying to understand how they can interact together and how the drug can bond with and cancel the danger of this virus,” says Dr Goumri-Said. “This is our target.” Her computational methods have certain advantages over in vivo testing. Investigations are safer and easier to conduct with the virus rendered on-screen because there is no need for personal protective equipment or laboratory safeguards that virologists must work under. Dr Goumri-Said can also enlist the help of Alfaisal’s student body as computational research is a key component of the curriculum. Undergraduate and postgraduate students with ambitions to pursue research careers are trained in computational methods so they can participate in the programme.

Dr Goumri-Said has access to databanks hosting the structure of SARS-CoV-2 and its variants, one of which catalogues potential pharmaceutical treatments at a molecular level. When modelling drug-virus interactions, she can alter any given component of the drug, adjust the model and observe the effects.

The set-up at Alfaisal will be familiar to anyone with experience in pharmaceutical research. “All pharmaceutical companies have this in their R&D facilities,” says Dr Goumri-Said. “They all have this computational component where they test the drugs on computers, on machines, and see how effective they are on the virus, cancers or tumours.”

Collaboration with industry, government and other third-party research institutions is always critical in sustaining research efforts and bringing solutions to market. Alfaisal University works with local health centres, sharing data and resources, and enjoys a close relationship with the King Faisal Specialist Hospital & Research Centre.

In Saudi Arabia, there is a tight-knit relationship between government and higher education, with the country leaning heavily on research for solutions to problems such as climate change, energy production and desertification.

Typically, Alfaisal University’s College of Science would get calls from all areas of government. In a sense, Covid-19 has jumped the queue, as it has done across the world, occupying much of science and research’s bandwidth. But perhaps its legacy will be felt in other areas of medicine, in the mRNA vaccines yet to be developed and in research methods, too.

Whatever the direction of science’s travel, artificial intelligence and machine learning will be fundamental to the research process and the roll-out of practical, real-world solutions. Presently, it is being used to track the status of Covid-19 patients, gathering, storing and making available data to help healthcare providers make better decisions.

For Dr Goumri-Said’s current research, AI is crucial. “I need artificial intelligence or deep learning to have an assessment of what I am targeting,” she says. “I have 1,000 samples, 1,000 results, about energy, about the situation. We can then assess them using artificial intelligence tools, and this will tell us if a drug is efficient, give us a percentage [of effectiveness], and our partners in pharmaceutical research can make a decision about it.” 

This computational model, in which an application can be studied and its efficacy demonstrated on a virtual level, can be employed in many different disciplines. “Artificial intelligence is now a normal step for any computational materials scientist,” says Dr Goumri-Said. “Right now, we have people working on energy, working on oil, working on polymers, working on different research topics.”

The hope is that scientific breakthroughs – new technologies, drugs and systems – can be proven theoretically and other researchers can build on their potential. “We can use artificial intelligence everywhere,” says Dr Goumri-Said. “[Researchers] want to show that their product is not limited to a simple application or patent for today; they want to show how the application can be used on a different level in the future.”

For Alfaisal University, this means investment in research infrastructure, developing new tools to build on its life science expertise, bringing biology and chemistry together with physics and materials science to tackle problems at scale. The pandemic is humanity’s most pressing problem right now. It will not be the last. 

Find out more about Alfaisal’s life sciences programme.

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