Yale University chemists are reporting synthesis of beta-peptide bundles, proteins that do not occur naturally, hence resistant to degradation by enzymes inside the body. Such protein structures can be modeled into drugs that will resemble intrinsically occurring proteins, but will not be eliminated by enzymes or by the immune system.
Howard Hughes Medical Institute (HHMI) explains:
Schepartz and colleagues built the short protein, or peptide, from β-amino acids, which, although they exist in cells, are never found in ribosomally produced proteins. β-amino acids differ from the alpha-amino acids that compose natural proteins by the addition of a single chemical component–a methylene group–into the peptide backbone.
“The fundamental insight from this study is that β-peptides can assemble into structures that generally resemble natural proteins in shape and stability,” Schepartz said. She added that their findings about the structure of the molecule that she and her colleagues synthesized will help scientists construct more elaborate β-peptide assemblies and ones that possess true biologic function.
Such β-peptides could also be designed as pharmaceuticals that would be more effective than natural protein drugs, because the enzymes that degrade natural proteins would not affect them…
In their studies, Schepartz and colleagues synthesized a β-peptide they called Zwit1-F. They allowed the chain of β-amino acids to assemble into its own structure and then analyzed it with x-ray crystallography, a technique in which x-rays are directed through a crystal of a protein so that its structure can be deduced from the resulting diffraction pattern.
The researchers found that the Zwit1-F peptide folded into a bundle of coiled helices that resembled those in natural proteins. In particular, Schepartz noted that both natural proteins and the β-peptide bundle folded in ways that placed the “water-hating” hydrophobic segments of the molecule in the core of the structure. Other features, too, were remarkably similar to a coiled helix bundle formed of α-amino acids.
“What is interesting about the β-peptide bundle is its similarity to α-helical bundles when viewed from afar,” she said. “It has a massive hydrophobic core, parallel and antiparallel helices, and an array of polar side chains on the surface. Looking from a distance, you’d say this was a helical bundle protein.”
There were significant differences, however. “Only when you look at the details, does it become clear that there are differences between the β-peptide structure and natural helical bundle proteins,” Schepartz said. For example, when helices of natural peptides nestle against one another, often their “side chains” extend from the sides of each helix, fitting together like ridges in grooves. The α-peptide helices, however, are structured so that their side chains alternate like interlocking fingers.
Schepartz said that the discovery of the tertiary helical bundle structure of Zwit1-F offers a “structural blueprint” for the design of more complex β-peptides that would function like natural proteins. Natural proteins, for example, operate as enzymes that catalytically guide chemical reactions in the cell.
Schepartz and colleagues now want to try to bind metal ions to the Zwit1-F structure. Metal ion binding would enable the researchers to begin designing enzymes based on the β-peptide, she explained. “We’re also interested in generating versions that can assemble in membranes, as a first step toward making transmembrane proteins composed of β-amino acids,” she said.
One of the most exciting potential results of their finding could be design of β-peptide drugs. “There is growing interest in proteins as drugs,” said Schepartz. “And although certain proteins are very effective pharmaceuticals, protein drugs generally suffer from storage and stability problems outside the body and from degradation inside the body. β-peptides may be more stable than traditional protein drugs and would not be recognized by the proteases that destroy proteins in the cell.”
Teaching machines to learn? [insert joke about machines becoming self-aware and taking over the world] Being on the serious side, researchers at the Rensselaer Polytechnic Institute have developed a “machine learning” algorithm which can correctly determine appropriate radiation therapy in as little as 10 minutes.
The field of video games in medicine is a rapidly growing business and now there’s a new company that wants to throw their hat in the ring. MindHabits was founded by psychologist Mark Baldwin and CEO/Gaming Industry Titan Matthew Mather, that hopes to use their software to decrease stress and build self-esteem. Better yet, they have the clinical research to support their concept.
A graduate student and her colleagues from Scotland developed a new way to test artificial cardiac valves using curdled milk as a blood substitute. The results look encouraging:
Using blood outside the body, Martin says, is tricky. “Blood wants to clot when it’s exposed to air. To prevent it from doing that, you have to add an anticoagulant, and then you have to add a chemical right back into [the blood] before the experiment to initiate clotting,” she explains. At that point, “you’re no longer working with human blood in the native state.”
A new kind of nanoparticle, for possible diagnostic and therapeutic purposes, created by UC Davis researchers:
Calypso Medical, a Seattle, WA company, is reporting that its advanced system for “guiding radiation therapy delivery with continuous, objective, organ-motion sub-millimeter tracking accuracy” has been used for the first time in a commercial clinical setting at Seattle’s Swedish Cancer Institute.
As a result, when the product is available for use, it is expected to be dramatically simpler to locate the true treatment target and — for the first time — to objectively and efficiently manage patient alignment continuously without extra non-therapeutic x-ray dose.
