Harvard Chemists Adapt COVID-19 Testing Strategy to Accelerate Drug Finding
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A novel approach to chemical research, inspired by the group testing methods used during the height of the COVID-19 pandemic, is poised to dramatically speed up the development of new drugs and valuable chemicals.
The crisis of 2020, when COVID-19 testing kits where scarce, forced laboratories to innovate. They began pooling samples from multiple patients and running a single test. A negative result cleared everyone in the pool, while a positive result triggered targeted follow-up tests. This strategy, known as group testing, conserved valuable time, money, and resources. Now, researchers at Harvard University, in collaboration wiht scientists at Merck, have adapted this same principle to accelerate the complex process of identifying effective chemical catalysts.
From Public Health to Chemical Innovation
A team led by Eric Jacobsen, Sheldon Emery Professor of Chemistry in the Department of Chemistry and Chemical Biology, detailed their findings in a recent nature paper. The research outlines an experimental and computational framework that leverages pooled tests to identify cooperative interactions between catalysts – substances that accelerate chemical reactions and lower the energy required for transformation.
This new method significantly reduces the number of individual reactions chemists need to perform while still effectively revealing which combinations yield the best results.”This idea of bringing two different catalysts together and seeing if the combination might do something especially powerful-either in a reactivity context or a selectivity context-has been engaging to me and many other chemists for a long time,” Jacobsen stated. “We’ve now found an efficient approach to uncovering unanticipated manifestations of cooperativity.”
The teamS approach, termed “pooling-deconvolution,” involves systematically combining catalysts in various mixtures and then analyzing the results to deduce which combinations are most effective. “We developed an algorithm to analyze the data,” Jacobsen clarified. “We were able to develop code to predict the best pooling strategies for evaluating different combinations of catalysts.”
A key challenge lay in the inherent complexity of chemical systems. unlike a COVID test with a clear positive or negative result,chemical reactions are nuanced. Catalysts can both enhance and inhibit reactions,depending on the surrounding chemical surroundings. “Catalysts can cooperate with each other, but they can also inhibit each other,” Jacobsen noted. “You could just ask,’If cooperativity is so significant,why don’t you just throw every catalyst in one flask and see if that soup does better than the individuals?’ The problem is,if you add all the catalysts you know in a soup,you’re guaranteed to get mud. They cancel each other out.”
to validate their approach, the researchers frist tested the pooling-deconvolution strategy on simulated data. The algorithm consistently and accurately identified the true cooperative pairs, filtering out misleading signals.
Real-World Submission and Enduring Chemistry
Encouraged by these results, the team applied their algorithm to a real-world challenge identified by co-author Richard liu, assistant professor of chemistry and chemical biology: a palladium-catalyzed decarbonylative cross-coupling reaction. These reactions are crucial for building complex molecules, including potential pharmaceutical compounds. The algorithm successfully identified several ligand pairs that outperformed individual ligands.
Reducing catalyst loading and energy consumption are central goals of sustainable chemistry, especially when utilizing precious metals.Though, the authors emphasize that the value of their framework extends far beyond any single chemical transformation.
“I think it’s a very complementary approach to what you might consider the more rational design approach of using our mechanistic understanding to impose the effects we’re looking for,” Jacobsen said.
Looking forward, the researchers aim to expand their approach to explore ternary and higher-order cooperativity, where three or more catalysts or ligands work in concert. “Coming up with powerful strategies for looking for interesting chemistry, in this case cooperativity, through high-throughput experimentation and realy strategic analysis can open up an enormous amount,” Jacobsen concluded. “We’re going to learn a lot of chemistry in the coming years.”
This research received partial funding from grants from the National Institutes of Health and the National Science Foundation.
