It's a Perfect Protein Match


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Dr. Gideon Schreiber. Improving affinity


Searching for a soul mate, new friends, or just fresh contacts? Turns out that proteins have similar "goals." However, shaking off their single status generally doesn't come easy.

Biochemist turned protein matchmaker Dr. Gideon Schreiber took their fate to heart. Working with doctoral student Tziki Seltzer and other colleagues at the Weizmann Institute's Biological Chemistry Department, they developed a computer algorithm that calculates the rate at which two proteins associate, using it to fashion proteins with increased affinity -- of a hundred times or more. Their achievement, appearing in Nature Structural Biology, holds much promise for the pharmaceutical and food industries, since protein complexes are fundamental to many life processes.

Protein affinity is defined by the rate at which two proteins associate with each other to form a complex, divided by the rate at which this complex dissociates. To improve affinity one can either intervene to reduce protein "break-up" statistics or, alternatively, increase protein association rates. Dr. Schreiber chose the latter.

Since association rates are influenced by the protein's (genetically determined) design, the scientists used this relationship as their guiding principle, developing an algorithm capable of determining the genetic changes necessary to boost association rates.

As it turns out, the "decision" whether to connect or not to connect is up to amino acids -- the protein's building blocks. "A protein's shape, properties, and biological role are determined by the nature and sequence of its amino acid ingredients," explains Schreiber. "For instance, the protein association rate is determined only by electrically charged amino acids (only four out of the twenty commonly occurring amino acids)." This is why the new algorithm operates by determining how to genetically change the charge of specific amino acids within a protein, so as to enhance its bonding capacity.


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But it goes one step further. A unique feature of the algorithm is that the changes it calls for do not need to affect the protein binding region itself (which would risk affecting the protein's properties). Rather, the algorithm essentially suggests ways to create the perfect ambience to cement the match.

"When put into solution, proteins generally float around aimlessly, binding from time to time. Our evidence suggests that when proteins pass one another quite close to the conformation in which they could bind, the criterion that actually guides and directs the formation of the protein complex is the electrical charge surrounding the binding region, called an attraction field. In nature, this feature is particularly prevalent in proteins that need to perform very quickly, such as anti-clotting proteins or ribonuclease inhibitors. What the new algorithm does is suggest the genetic changes needed to improve the attraction field of diverse proteins, thus optimizing their binding conformation," says Schreiber.

Computer simulations are far more efficient in pinpointing potentially successful complexes than the conventional approach, which is based on creating a large pool of mutations and discovering the optimal complex through trial and error. Using the algorithm, the Weizmann Institute researchers increased the formation rate of a specific complex (B-lactamase protein and its inhibitor) by a factor of 250 and significantly enhanced its binding strength.

The new protein match-up system may lead to diverse medicinal applications based on increasing or inhibiting protein activity, as well as to new diagnostic procedures, including antibody detection.
Ilustration: Protein looking for a match