Their findings, appearing in a recent issue of the Journal of the American Chemical Society, could drastically decrease the time it takes to move potential biopharmaceuticals from the drawing board to the drug store. In this study, the researchers modeled a peptide (a chain of amino acids, such as a protein or protein fragment) called Compstatin, which prevents the autoimmune-mediated damage of organs during transplantation, and various inflammatory diseases. The computer modeling and optimization process cut down on trial and error and created a version of Compstatin seven times more efficient and stable than the original.
Since the function of a peptide depends on its form, the researchers modeled the effects of substituting each of Compstatin's 13 amino acid subunits with a different amino acid. The novel in silico sequence design method could then model how the altered amino acid sequence folds together in comparison to the original peptide.
"It is a major challenge to design new peptides and proteins that exhibit the desired function such as improved inhibition for the complement system. The challenge centers around the problem of selecting promising sequences from the huge number of possible combinations and making sure those sequences will have the desired three-dimensional structure," said Christodoulos A. Floudas, PhD, a Professor of Chemical Engineering at Princeton University, whose laboratory developed the in silico de novo protein
"At the heart of this innovative technology is a unique two-stage computer protein design method that not only selects and ranks sequenc
Contact: Greg Lester
University of Pennsylvania School of Medicine