摘要
Point mutations on membrane proteins may lead to small structural variations. Prediction of such struc- tural variations can help to further understand the related bio-activities of membrane proteins. We constructed fifteen hybrid energy functions on the basis of Chemistry at Harvard Macromolecular Mechanics（CHARMM） force field, hydrogen bonding potential and distance-scaled, finite ideal-gas reference（DFIRE）-like statistical energies, and eva- luated their performance on a representative dataset of homologous membrane proteins via a newly developed all-atom replica exchange Monte Carlo algorithm. The energy function composed of CHARMM and hydrogen bonding potential has the best performance, and the original DFIRE potential shows much better performance than the DFIRE-Iike potentials constructed from membrane proteins. We can conclude that more membrane protein struc- tures with high resolution are necessary for the construction of robust prediction method of mutation induced mem- brane protein structure variations.
Point mutations on membrane proteins may lead to small structural variations. Prediction of such struc- tural variations can help to further understand the related bio-activities of membrane proteins. We constructed fifteen hybrid energy functions on the basis of Chemistry at Harvard Macromolecular Mechanics（CHARMM） force field, hydrogen bonding potential and distance-scaled, finite ideal-gas reference（DFIRE）-like statistical energies, and eva- luated their performance on a representative dataset of homologous membrane proteins via a newly developed all-atom replica exchange Monte Carlo algorithm. The energy function composed of CHARMM and hydrogen bonding potential has the best performance, and the original DFIRE potential shows much better performance than the DFIRE-Iike potentials constructed from membrane proteins. We can conclude that more membrane protein struc- tures with high resolution are necessary for the construction of robust prediction method of mutation induced mem- brane protein structure variations.
