Artificial proteins: Team predicts structures
NYU (US) — A new method can predict the structures of artificial proteins, a breakthrough that may prove valuable for developing pharmaceuticals and other chemicals.
The work is detailed in the Proceedings of the National Academy of Sciences (PNAS).
The structures of natural proteins define their complex functions. Based on interactions between their amino acids, proteins can fold and twist into distinct, chemically directed shapes. The resulting structure dictates the proteins’ actions in the body, so accurate modeling of structure is vital to understanding their functions.
Peptoids, or synthetic proteins, follow similar design rules. Because peptoids are less vulnerable to chemical or metabolic breakdown than are proteins, they hold promise for pharmaceuticals and materials.
Scientists can now build and manipulate peptoid molecules with great precision. But to design peptoids for a specific function, researchers need to first untangle the complex relationship between a peptoid’s composition and its folded structure.
Past efforts to predict protein structure have had limited success, but the research team for the PNAS study demonstrated that a computer modeling approach similar to one used to predict protein structures can accurately predict peptoid conformations as well.
Kent Kirshenbaum, an associate professor in New York University’s chemistry department and one of the study’s co-authors, says some members of the research team “worked together on this truly difficult problem for almost 20 years. The researchers include both experimentalists and theorists who have been able to guide one another in discovering how these peptoid molecules fold.”
The researchers devised an innovative approach to make accurate predictions of peptoid folding—a “blind structure prediction” challenge.
This technique allows scientists to test the fidelity of their computational models by predicting the three-dimensional structure of a known molecule and then comparing their proposed structure to the X-ray crystallography results.
The predictions of the peptoid molecules did exceedingly well at calculating the actual folded conformations, suggesting that reliable structure prediction for complex three-dimensional folds is within reach and marking an enormous step forward on the path to reliable and efficient computational peptoid design.
The research was conducted by scientists at NYU, the US Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab), Stony Brook University, and Temple University.
The Department of Energy, Defense Threat Reduction Agency, National Science Foundation, and National Institutes of Health supported the work.