Protein design simulations suggest that side-chain conformational entropy is not a strong determinant of amino acid environmental preferences.
Loss of side-chain conformational entropy is an important force opposing protein folding and the relative preferences of the amino acids for being buried or solvent exposed may be partially determined by which amino acids lose more side-chain entropy when placed in the core of a protein. To investigate these preferences, we have incorporated explicit modeling of side-chain entropy into the protein design algorithm, RosettaDesign. In the standard version of the program, the energy of a particular sequence for a fixed backbone depends only on the lowest energy side-chain conformations that can be identified for that sequence. In the new model, the free energy of a single amino acid sequence is calculated by evaluating the average energy and entropy of an ensemble of structures generated by Monte Carlo sampling of amino acid side-chain conformations. To evaluate the impact of including explicit side-chain entropy, sequences were designed for 110 native protein backbones with and without the entropy model. In general, the differences between the two sets of sequences are modest, with the largest changes being observed for the longer amino acids: methionine and arginine. Overall, the identity between the designed sequences and the native sequences does not increase with the addition of entropy, unlike what is observed when other key terms are added to the model (hydrogen bonding, Lennard-Jones energies, and solvation energies). These results suggest that side-chain conformational entropy has a relatively small role in determining the preferred amino acid at each residue position in a protein.
Hu
Xiaozhen
X
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill 27599, USA.
Kuhlman
Brian
B
D000595:Amino Acid Sequence; D019943:Amino Acid Substitution; D000596:Amino Acids / Q000737:chemistry*; D003198:Computer Simulation; D019277:Entropy; D009010:Monte Carlo Method; D020641:Polymorphism, Single Nucleotide; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D011994:Recombinant Proteins / Q000737:chemistry / Q000378:metabolism
D000596:Amino Acids; D011506:Proteins; D011994:Recombinant Proteins