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Fifty years after the discovery that a protein’s three-dimensional structure is determined solely by the sequence of its amino acids, an international team of researchers is taking a major step toward fulfilling the tantalizing promise of predicting the structure of a protein from its DNA alone.
The team at Harvard Medical School (HMS), Politecnico di Torino / Human
The results were published December 7, 2011 in the journal PLoS ONE.
In molecular biology and biomedical engineering, knowing the shape of protein molecules is key to understanding how they perform the work of repairing cells, and the mechanisms of disease - essential for drug design.
Normally the shape of protein molecules is determined by expensive and complicated experiments, and for most proteins, experiments have not been done. Computing the shape from genetic information alone is possible in principle. But despite success for some smaller proteins, the challenge remains essentially undone. The difficulty is the enormous complexity of the astronomically large number of possible shapes. It would take a super-computer years to work out all possible shapes for even a small protein.
“Experimental structure determination has a hard time keeping up with the explosion in genetic sequence information,” said Debora Marks, a mathematical biologist in the Department of Systems Biology at HMS, working closely with Lucy Colwell, a mathematician, Cambridge University. They collaborated with physicists Riccardo Zecchina and Andrea Pagnani in Torino, and computational biologist Chris Sander of the Computational Biology Program at MSKCC.
“Collaboration was key,” Sander said. “As with many important discoveries in science, no one could provide the answer in isolation.”
The international team tested a bold idea - that evolution can provide a roadmap to how proteins fold. Beginning with DNA sequence patterns seen throughout evolution, they then combined two other key elements: data from high-throughput genetic sequencing, and a method from statistical physics known as “maximum entropy” (co-developed with Martin Weigt from the University of Paris).
Evolutionary information revealed sequences for thousands of proteins that the team grouped into families by similar protein folding patterns. They then created an algorithm to determine which areas will touch in a specific protein shape. Using a principle from statistical physics called “maximum entropy” they then were able to extract microscopic interactions. The team used standard molecular simulation software developed by Axel Brunger at Stanford University to generate these atomic details of protein shapes.
“The protein folding problem has been a huge combinatorial challenge for decades,” said Zecchina, “but our statistical methods turned out to be surprisingly effective in extracting essential information from the evolutionary record.”
This is the first time scientists have been able to compute accurate shapes from DNA sequence information alone for a test set of 15 diverse proteins, with no protein size limit, and with unprecedented accuracy.
“Alone, none of the individual pieces are completely novel, but apparently nobody had put all of them together to predict 3D protein structure,” Colwell said.
The researchers caution that experimental structures are generally more accurate in atomic detail. Also, at this time the method only works for predicting protein folding in large families of proteins. The next step, the researchers say, is to predict the structures of unsolved proteins currently under investigation, before exploring the largest uncharted territory - unknown protein structures.
“Synergy between computational prediction and experimental determination of structures is likely to yield increasingly valuable insight into the large universe of protein shapes that crucially determine their function and evolutionary dynamics,” Sander said.
The National Cancer Institute; the Engineering and Physical Sciences Research Council of the United Kingdom
Citation: PLoS ONE, December 7, 2011
Harvard Medical School (http://hms.harvard.edu) has more than 7,500 full-time faculty working in 11 academic departments located at the School’s Boston campus or in one of 47 hospital-based clinical departments at 17 Harvard-affiliated teaching hospitals and research institutes. Those affiliates include Beth Israel Deaconess Medical Center, Brigham and Women¹s Hospital, Cambridge Health Alliance, Children¹s Hospital Boston, Dana-Farber Cancer Institute, Forsyth Institute, Harvard Pilgrim Health Care, Hebrew SeniorLife, Joslin Diabetes Center, Judge Baker Children¹s Center, Massachusetts Eye and Ear Infirmary, Massachusetts General Hospital, McLean Hospital, Mount Auburn Hospital, Schepens Eye Research Institute, Spaulding Rehabilitation Hospital, and VA Boston Healthcare System.
Original article: http://www.focushms.com/features/evolution-reveals-missing-link-between-dna-and-protein-shape/