BUFFALO, N.Y. — One class of drugs that has shown promise in treating diseases ranging from lung cancer to COVID-19 are targeted covalent inhibitors (TCIs). These small molecule drugs form covalent bonds with their target proteins, allowing them to bind and inhibit activity with exceptional potency.
A major metric for TCIs is an inactivation efficiency rate that measures how quickly they bind to a target and inactivate it.
However, a faster rate will only get you so far, according to a new University at Buffalo study.
Researchers found that an increased inactivation efficiency rate was linked to greater drug potency, but only to a certain point. Eventually, as the TCIs worked faster, their potency plateaued, and the binding time was no longer a good indicator of whether they were a promising drug candidate.
Published Aug. 13 in the American Chemical Society's Journal of Medicinal Chemistry , the team's proposed TCI design process emphasizes balancing — rather than simply maximizing — a compound's inactivation efficiency rate among a set of other parameters.
"This is a potential pitfall that really has not been discussed and is not as obvious as you might think it would be," says the study's lead author, David Heppner, PhD, Jere Solo Assistant Professor of Medicinal Chemistry in the UB College of Arts and Sciences. "If you simply followed the inactivation efficiency rate, you could end up selecting the wrong compound. We want to give drug developers an additional check on how to figure out the best compound before they get too far down the road."
The study is part of the team's ongoing work, supported by the National Institutes of Health, to streamline the costly and time-consuming drug discovery process.
"Drug discovery is hard. Making good decisions early on is really important," Heppner says. "Sometimes that requires going back to the drawing board, as we did in this study, to generate an effective workflow."
Speed must be balanced with selectivity
Conventional wisdom is that drugs have to be made from molecules that are very sticky when they bind their target. This increases the odds that enough molecules will bind to enough targets within a cell to be effective.
TCIs upend this. They don't have to be made from inherently sticky molecules because the covalent bond between itself and its target does the heavy lifting.
This bond is the result of a chemical reaction between specific residues of the target protein and a reactive chemical group attached to the TCI's scaffolding, known as a "warhead."
"The warhead allows you to make a TCI out of a molecule that has a weak binding profile," says the study's first author, Tahereh Damghani, a postdoctoral researcher in Heppner's lab. "You can essentially develop a new drug that otherwise would be ineffective."
Heppner's team took 14 advanced molecules and tested their ability as TCIs on the epidermal growth factor receptor (EGFR), a protein that helps cells grow and where a mutation can make cells grow too much and cause cancer. TCIs have already shown to be effective at binding to and inhibiting mutated EGFRs, making it a good testing ground.
"We observed that as TCIs got faster, their cellular effects became better, which makes sense," Heppner says. "But once they reached a certain speed, we stopped seeing that correlate to better cellular effects. This is a big problem because if you have a lot of very fast TCIs all with roughly the same potency, you don't know which ones to prioritize for new drugs."
They even included a problematic metabolite of a clinically approved molecule among the 14 molecules. Relying on the inactivation efficiency rate alone couldn't identify it from the pack.
Thus, they propose a two-step design process that first emphasizes increasing the inactivation efficiency rate but then considers a broader set of parameters, such as target selectivity; this measures how well a drug binds to its intended target as opposed to unintended targets.
"We mention selectivity because we directly measured that, but it could be one of many different parameters," Heppner says. "The crucial thing is understanding that inactivation efficiency rates eventually stop providing valuable information and you have to figure out an additional way to differentiate promising from unpromising compounds."
Other authors include PhD students Omobolanle Abiodun, Surbhi Chitnis and Kishan Patel and undergraduate students Abigail Lantry, Kaly Lin and Emily Ouellette.
