The new platform helped UC San Diego scientists synthesize 32 potential multi-target cancer drugs.
Scientists at UC San Diego have developed a machine learning algorithm to simulate the time-consuming chemistry involved in the earliest phases of drug discovery, which could significantly streamline the process and open doors for never-before-seen treatments. Identifying candidate drugs for further optimization typically involves thousands of individual experiments, but the new artificial intelligence (AI) platform could potentially give the same results in a fraction of the time.
The researchers used the new tool, described today (May 6) in Nature Communications, to synthesize 32 new drug candidates for cancer.
The Shift Toward AI in Pharmaceuticals
The technology is part of a new but growing trend in pharmaceutical science of using AI to improve drug discovery and development.
“A few years ago, AI was a dirty word in the pharmaceutical industry, but now the trend is definitely the opposite, with biotech startups finding it difficult to raise funds without addressing AI in their business plan,” said senior author Trey Ideker, professor in the Department of Medicine at UC San Diego School of Medicine and adjunct professor of bioengineering and computer science at the UC San Diego Jacobs School of Engineering. “AI-guided drug discovery has become a very active area in industry, but unlike the methods being developed in companies, we’re making our technology open source and accessible to anybody who wants to use it.”
Advantages of Multi-Target Drug Discovery
The new platform, called POLYGON, is unique among AI tools for drug discovery in that it can identify molecules with multiple targets, while existing drug discovery protocols currently prioritize single target therapies. Multi-target drugs are of major interest to doctors and scientists because of their potential to deliver the same benefits as combination therapy, in which several different drugs are used together to treat cancer, but with fewer side effects.
“It takes many years and millions of dollars to find and develop a new drug, especially if we’re talking about one with multiple targets.” said Ideker. “The rare few multi-target drugs we do have were discovered largely by chance, but this new technology could help take chance out of the equation and kickstart a new generation of precision medicine.”
How POLYGON Works
The researchers trained POLYGON on a database of over a million known bioactive molecules containing detailed information about their chemical properties and known interactions with protein targets. By learning from patterns found in the database, POLYGON is able to generate original chemical formulas for new candidate drugs that are likely to have certain properties, such as the ability to inhibit specific proteins.
“Just like AI is now very good at generating original drawings and pictures, such as creating pictures of human faces based off desired properties like age or sex, POLYGON is able to generate original molecular compounds based off of desired chemical properties,” said Ideker. “In this case, instead of telling the AI how old we want our face to look, we’re telling it how we want our future drug to interact with disease proteins.”
Study co-author Katherine Licon, photographed here at the bench, is lab manager for the Ideker Lab at UC San Diego, which combines computational and traditional wet-lab techniques to answer fundamental questions about disease biology and discover new ways to enhance precision medicine. Credit: Erik Jepsen/UC San Diego
Testing and Results
To put POLYGON to the test, the researchers used it to generate hundreds of candidate drugs that target various pairs of cancer-related proteins. Of these, the researchers synthesized 32 molecules that had the strongest predicted interactions with the MEK1 and mTOR proteins, a pair of cellular signaling proteins that are a promising target for cancer combination therapy. These two proteins are what scientists call synthetically lethal, which means that inhibiting both together is enough to kill cancer cells even if inhibiting one alone is not.
The researchers found that the drugs they synthesized had significant activity against MEK1 and mTOR, but had few off-target reactions with other proteins. This suggests that one or more of the drugs identified by POLYGON could be able to target both proteins as a cancer treatment, providing a list of choices for fine-tuning by human chemists.
“Once you have the candidate drugs, you still need to do all the other chemistry it takes to refine those options into a single, effective treatment,” said Ideker. “We can’t and shouldn’t try to eliminate human expertise from the drug discovery pipeline, but what we can do is shorten a few steps of the process.”
Future of AI in Drug Discovery
Despite this caution, the researchers are optimistic that the possibilities of AI for drug discovery are only just being explored.
“Seeing how this concept plays out over the next decade, both in academia and in the private sector, is going to be very exciting,” said Ideker. “The possibilities are virtually endless.”
Reference: 6 May 2024,
Co-authors of the study include: Brenton Munson, Michael Chen, Audrey Bogosian, Jason Kreisberg, Katherine Licon, Abagyan Ruben and Brent Kuenzi, all at UC San Diego.
This study was funded, in part, by the National Institutes of Health (Grants CA274502, GM103504, ES014811, CA243885, CA212456).
![](https://www.nanoappsmedical.com/wp-content/uploads/2017/05/spacer.jpg)
News
Breakthrough in Antimicrobial Technology with Cinnamon-Based Nanokiller
The need for innovative antimicrobial agents has become increasingly urgent due to the rise of antibiotic-resistant pathogens and the persistent threat of infections acquired during hospital stays. Traditional antibiotics and antiseptics are often ineffective [...]
The Silent Battle Within: How Your Organs Choose Between Mom and Dad’s Genes
Research reveals that selective expression of maternal or paternal X chromosomes varies by organ, driven by cellular competition. A new study published today (July 26) in Nature Genetics by the Lymphoid Development Group at the MRC [...]
Study identifies genes increasing risk of severe COVID-19
Whether or not a person becomes seriously ill with COVID-19 depends, among other things, on genetic factors. With this in mind, researchers from the University Hospital Bonn (UKB) and the University of Bonn, in [...]
Small regions of the brain can take micro-naps while the rest of the brain is awake and vice versa
Sleep and wake: They're totally distinct states of being that define the boundaries of our daily lives. For years, scientists have measured the difference between these instinctual brain processes by observing brain waves, with [...]
Redefining Consciousness: Small Regions of the Brain Can Take Micro-Naps While the Rest of the Brain Is Awake
The study broadly reveals how fast brain waves, previously overlooked, establish fundamental patterns of sleep and wakefulness. Scientists have developed a new method to analyze sleep and wake states by detecting ultra-fast neuronal activity [...]
AI Reveals Health Secrets Through Facial Temperature Mapping
Researchers have found that different facial temperatures correlate with chronic illnesses like diabetes and high blood pressure, and these can be detected using AI with thermal cameras. They highlight the potential of this technology [...]
Breakthrough in aging research: Blocking IL-11 extends lifespan and improves health in mice
In a recent study published in the journal Nature, a team of researchers used murine models and various pharmacological and genetic approaches to examine whether pro-inflammatory signaling involving interleukin (IL)-11, which activates signaling molecules such [...]
Promise for a universal influenza vaccine: Scientists validate theory using 1918 flu virus
New research led by Oregon Health & Science University reveals a promising approach to developing a universal influenza vaccine—a so-called "one and done" vaccine that confers lifetime immunity against an evolving virus. The study, [...]
New Projects Aim To Pioneer the Future of Neuroscience
One study will investigate the alterations in brain activity at the cellular level caused by psilocybin, the psychoactive substance found in “magic mushrooms.” How do neurons respond to the effects of magic mushrooms? What [...]
Decoding the Decline: Scientific Insights Into Long COVID’s Retreat
Research indicates a significant reduction in long COVID risk, largely due to vaccination and the virus’s evolution. The study analyzes data from over 441,000 veterans, showing lower rates of long COVID among vaccinated individuals compared [...]
Silicon Transformed: A Breakthrough in Laser Nanofabrication
A new method enables precise nanofabrication inside silicon using spatial light modulation and laser pulses, creating advanced nanostructures for potential use in electronics and photonics. Silicon, the cornerstone of modern electronics, photovoltaics, and photonics, [...]
Caught in the actinium: New research could help design better cancer treatments
The element actinium was first discovered at the turn of the 20th century, but even now, nearly 125 years later, researchers still don't have a good grasp on the metal's chemistry. That's because actinium [...]
Innovative Light-Controlled Drugs Could Revolutionize Neuropathic Pain Treatment
A team of researchers from the Institute for Bioengineering of Catalonia (IBEC) has developed light-activated derivatives of the anti-epileptic drug carbamazepine to treat neuropathic pain. Light can be harnessed to target drugs to specific [...]
Green Gold: Turning E-Waste Into a Treasure Trove of Rare Earth Metals
Scientists are developing a process inspired by nature that efficiently recovers europium from old fluorescent lamps. The approach could lead to the long-awaited recycling of rare earth metals. A small molecule that naturally serves [...]
Cambridge Study: AI Chatbots Have an “Empathy Gap,” and It Could Be Dangerous
A new study suggests a framework for “Child Safe AI” in response to recent incidents showing that many children perceive chatbots as quasi-human and reliable. A study has indicated that AI chatbots often exhibit [...]
Nanoparticle-based delivery system could offer treatment for diabetics with rare insulin allergy
Up to 3% of people with diabetes have an allergic reaction to insulin. A team at Forschungszentrum Jülich has now studied a method that could be used to deliver the active substance into the [...]