BUFFALO, N.Y. -- Just as conventional libraries are only as good as the books on their shelves, chemical libraries synthesized by pharmaceutical scientists are only as useful as the new compounds they generate.
A new drug-discovery method being developed by University at Buffalo researchers may be able to turn those chemical libraries, arrays of compounds synthesized in the lab, into molecular "habitats" where only the most desirable drug candidates survive.
Based on the application of Darwinian principles of evolution to a chemical system, the method is designed to endow compounds in chemical libraries with the extraordinary ability to evolve into the best potential drug candidate for a particular molecular target.
Called dynamic combinatorial chemistry, the new method could mean major cost savings for pharmaceutical companies because it has the potential to identify numerous promising drug leads in just days, as compared to months or years using current techniques.
It was described today (Tuesday, May 19) in a presentation by Alexey V. Eliseev, Pharm.D., UB assistant professor of medicinal chemistry, at the 39th annual UB Medicinal Chemistry Symposium.
The research is published in the current issue of Chemistry: A European Journal (Vol. 4, No. 5, pp. 825-834).
The article is available at http://www.wiley-vch.de/vch/journals/2111/index.html
The system differs from traditional combinatorial chemistry, where chemical libraries synthesize as many different compounds as possible, which then are screened individually for potency against specific disease molecules.
"In combinatorial chemistry, the goal is to produce many possible combinations and then screen the compounds individually," said Eliseev.
"In our method we combine the steps."
Doing both in one step would be extremely cost-effective, Eliseev explained.
"Our libraries can potentially be generated up to two orders of magnitude faster than is possible with traditional combinatorial chemistry," he said.
The new method synthesizes many different compounds at once in complex mixtures. Then, because of the presence of a molecular target, its components naturally will evolve into the best candidate molecules.
"This method employs basic principles of Darwinian evolution," said Eliseev. "It's survival of the fittest. Our method increases the amount of the desirable compounds and decreases the amount of the undesirable ones."
Unlike other combinatorial methods, the UB method works by using molecular recognition -- the ability of molecules to bind to a target -- to simultaneously form and screen mixtures of many chemicals for the best ones.
During a stage the scientists call equilibration, or variation, the components of these mixtures are manipulated by the presence of the molecular target to "evolve" higher fractions of the best compounds.
"Our mixture circulates through two chromatographic columns," explained Eliseev. "In one of them, which we call the selection chamber, the effective components bind to the immobilized target compound. In the other one, the remaining mixture is brought to an equilibrium, where the mixture regenerates the fraction of the effective binders it just lost."
In the same way that natural evolution plays out over the course of many generations, chemical evolution occurs over the course of many repeated cycles during which the chemical library continually reforms itself, evolving a much larger subset of effective components.
These components then are isolated from the mixture and analyzed to identify potential drug leads.
The method has been proven in a model system.
The UB scientists are using it to develop drug candidates against the enzyme pepsin, which is found in the stomach and involved in the formation of ulcers.
The above post is reprinted from materials provided by University At Buffalo. Note: Content may be edited for style and length.
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