image: Purdue University researchers have come up with a novel way to do 3D mapping of proteins and their shapes. This image shows the mapping of protein 3D shapes. Each dot represents a protein shape. The distance of proteins in the map represents similarity of their shapes. view more
Credit: Purdue University/Daisuke Kihara
WEST LAFAYETTE, Ind. - Proteins can provide a detailed look inside the human body and how it protects itself from many diseases. Proteins, which make up about 15% of body mass, are the most abundant solid substances in the human body. They are important working molecules of the immune system, metabolism, brain function, body motion, and any physically and chemically functional parts in a body. Each protein has a specific function under the direction of its own gene.
Now, Purdue University researchers have come up with a novel way to classify proteins and their shapes, which lays the foundation of how we understand protein structures and functions. The shapes are important because they determine the role and effectiveness of the proteins. The research is published in the April edition of PLOS Computational Biology.
"We developed a new way to view and classify protein 3D shapes, which provides our basic understanding of protein shapes and will become a foundation of artificial protein design and other applications of proteins," said Daisuke Kihara, a professor of biological sciences and computer science in Purdue's College of Science, who leads the research team.
Kihara said proteins were conventionally classified by conformations of protein chains, a rather detailed level of structural features. They currently classify proteins by their overall surface shapes, which would be more directly relevant to how they interact with other proteins and compounds in a cell.
The Purdue team maps and classifies 3D surface shapes of proteins within a certain space inside the body. Surface shapes of proteins are represented with 3D Zernike descriptors, mathematical moment-based invariants, which have previously been demonstrated effective for biomolecular structure similarity search.
They also have analyzed the shape space occupied by protein complexes. The mapping provides data into the relationship between shapes, main-chain folds and complex formation.
"This work is in the area of bioinformatics," Kihara said. "Bioinformatics is not only useful for processing biological data or developing computational tools, but it is also helpful for providing a unique view and framework that can change the way people view and understand the biomolecular world."
Kihara has worked with the Purdue Research Foundation Office of Technology Commercialization on some of his research and technology.
His team's work aligns with Purdue's Giant Leaps celebration, celebrating the global advancements in health research and technology as part of Purdue's 150th anniversary. Health is one of the four themes of the yearlong celebration's Ideas Festival, designed to showcase Purdue as an intellectual center solving real-world issues.
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About Purdue Research Foundation Office of Technology Commercialization
The Purdue Research Foundation Office of Technology Commercialization operates one of the most comprehensive technology transfer programs among leading research universities in the U.S. Services provided by this office support the economic development initiatives of Purdue University and benefit the university's academic activities. The office is managed by the Purdue Research Foundation, which received the 2016 Innovation and Economic Prosperity Universities Award for Innovation from the Association of Public and Land-grant Universities. For more information about funding and investment opportunities in startups based on a Purdue innovation, contact the Purdue Foundry at foundry@prf.org. For more information on licensing a Purdue innovation, contact the Office of Technology Commercialization at otcip@prf.org. The Purdue Research Foundation is a private, nonprofit foundation created to advance the mission of Purdue University.
Writer: Chris Adam, 765-588-3341, cladam@prf.org
Source: Daisuke Kihara, dkihara@purdue.edu
Journal
PLoS Computational Biology