Polarizable protein packing.
To incorporate protein polarization effects within a protein combinatorial optimization framework, we decompose the polarizable force field AMOEBA into low order terms. Including terms up to the third-order provides a fair approximation to the full energy while maintaining tractability. We represent the polarizable packing problem for protein G as a hypergraph and solve for optimal rotamers with the FASTER combinatorial optimization algorithm. These approximate energy models can be improved to high accuracy [root mean square deviation (rmsd) < 1 kJ mol(-1)] via ridge regression. The resulting trained approximations are used to efficiently identify new, low-energy solutions. The approach is general and should allow combinatorial optimization of other many-body problems.
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.
Albert H
AH
Ng
Christopher D
CD
Snow
D000465:Algorithms; D008956:Models, Chemical; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D011789:Quantum Theory
D011506:Proteins