Computational protein design with explicit consideration of surface hydrophobic patches
Ron Jacak
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599
Search for more papers by this authorAndrew Leaver-Fay
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599
Search for more papers by this authorCorresponding Author
Brian Kuhlman
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC 27599===Search for more papers by this authorRon Jacak
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599
Search for more papers by this authorAndrew Leaver-Fay
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599
Search for more papers by this authorCorresponding Author
Brian Kuhlman
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina 27599
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC 27599===Search for more papers by this authorAbstract
De novo protein design requires the identification of amino-acid sequences that favor the target-folded conformation and are soluble in water. One strategy for promoting solubility is to disallow hydrophobic residues on the protein surface during design. However, naturally occurring proteins often have hydrophobic amino acids on their surface that contribute to protein stability via the partial burial of hydrophobic surface area or play a key role in the formation of protein–protein interactions. A less restrictive approach for surface design that is used by the modeling program Rosetta is to parameterize the energy function so that the number of hydrophobic amino acids designed on the protein surface is similar to what is observed in naturally occurring monomeric proteins. Previous studies with Rosetta have shown that this limits surface hydrophobics to the naturally occurring frequency (∼ 28%), but that it does not prevent the formation of hydrophobic patches that are considerably larger than those observed in naturally occurring proteins. Here, we describe a new score term that explicitly detects and penalizes the formation of hydrophobic patches during computational protein design. With the new term, we are able to design protein surfaces that include hydrophobic amino acids at naturally occurring frequencies, but do not have large hydrophobic patches. By adjusting the strength of the new score term, the emphasis of surface redesigns can be switched between maintaining solubility and maximizing folding free energy. Proteins 2011. © 2012 Wiley Periodicals, Inc.
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