Highly Potent; Highly Targeted
A new mathematical model aims to improve drugs for cancer, viruses and bacteria
Peixuan Guo, Professor of the College of Pharmacy and Director of the University of Kentucky’s Nanobiotechnology Center, has antibacterial resistance in his sights. Moreover, he hopes to hit two birds with one stone by improving drug efficacy as well.
Guo and his colleagues have developed a method to target the multi-subunit complexes that viruses, bacteria and cancer need to function – and it could help develop more highly potent (and targeted) drugs.
The new approach has taken more than a decade to reach fruition but, in a nutshell, the team studied the relationship between the stoichiometry of a target component and inhibition efficiency, and developed a mathematical model that elucidates the potency of drug inhibition. Guo explains, “I found that virion assembly inhibition depends on the stoichiometry of the components. The unusual efficiency of inhibin primed me to investigate the mechanism of inhibition. It took more than 10 years to develop a mathematical model including Yan Hui Triangle and binomial distribution to elucidate the mechanism of inhibin. We found that the high efficiency of inhibin is due to K = 1; that is, binding of a drug to any one of the multiple subunit machines at any one of the locations will inactivate the entire biological machine or the complex.”
He compares it to a chain of Christmas lights on a serial circuit; breaking a single bulb stops the entire system, which inspired him to design a mathematical model to clarify the mechanism of this kind of potency. “Developing drugs by targeting vital components with high stoichiometry would lead to new drugs with higher potency, and I expect that the method will have broad applications for drug development in many biological systems,” says Guo. “Using this method is relatively simple. The drug developer can simply check published literature and find the multi-subunit machine as a drug target. The key, which is also the most challenging part of the entire project, is to identify a multi-subunit machine or functional complex with a structure or sequence that are unique to the pathogen species or different to its counterpart in normal cells to build-in selectivity.”
The inhibition data for the mathematical model are based on a bacterial virus that is not pathogenic, but Guo will continue the study through collaborations. Indeed, Guo indicated that biological systems contain a wide variety of functional complexes composed of multiple subunits. For example, AAA+ hexamerics are essential for, amongst other processes, DNA replication and repair, viral genome packaging, nuclear pore transport, and transport of drugs. “Finding a unique or mutant AAA+ hexameric complex in certain cancer cells is one way to go. If such a target was found, it would be an ideal substrate for highly effective anticancer drug development,” he says.
“I hope this work will help all medicine makers develop better drugs in the future.”
- D. Shu et al., “New Approach to Develop Ultra-High Inhibitory Drug Using the Power Function of the Stoichiometry of the Targeted Nanomachine or Biocomplex,” Nanomedicine 10 (12), 1881-1897 (2015).
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