We aim to apply principles of combinatorial topology and statistical mechanics to the prediction of protein stability. The goal is to enumerate the chain configurations in the globular states of protein molecules subject to known energetic or distance constraints. We plan to predict entropies of folding, the accessiblities of various chain conformations, and their approximate free energies principally through exhaustive simulation of the """"""""Hamiltonian paths"""""""" of chain molecules on lattices, weighted with appropriate interaction energies, and through use of Delaunay graphs, which are """"""""duals"""""""" of Voronoi lattices, and related methods. Previous approaches, including molecular mechanics, molecular dynamics, and lattice treatments, have only permitted sampling of relatively small fractions of conformational space, and thus cannot predict entropies and true free energies. It appears that exhaustive simulations have not been previously attempted due to the widely held misconception that the number of chain conformations available to globular proteins is virtually infinite. We have recently shown that the number of accessible conformations has been overestimated by many tens of orders of magnitude, and is small enough to be computer enumerable. If the proposed work is successful, it should have major impact on the protein folding problem inasmuch as it bears directly on the role of chain conformations and conformational entropy in the packing and stability of globular molecules.
| Perez, Alberto; MacCallum, Justin L; Brini, Emiliano et al. (2015) Grid-based backbone correction to the ff12SB protein force field for implicit-solvent simulations. J Chem Theory Comput 11:4770-9 |
| Pressé, Steve; Peterson, Jack; Lee, Julian et al. (2014) Single molecule conformational memory extraction: p5ab RNA hairpin. J Phys Chem B 118:6597-603 |
| Roy, Arijit; Perez, Alberto; Dill, Ken A et al. (2014) Computing the relative stabilities and the per-residue components in protein conformational changes. Structure 22:168-75 |
| Presse, Steve; Lee, Julian; Dill, Ken A (2013) Extracting conformational memory from single-molecule kinetic data. J Phys Chem B 117:495-502 |
| Peterson, G Jack; Pressé, Steve; Peterson, Kristin S et al. (2012) Simulated evolution of protein-protein interaction networks with realistic topology. PLoS One 7:e39052 |
| Schmit, Jeremy D; Dill, Ken (2012) Growth rates of protein crystals. J Am Chem Soc 134:3934-7 |
| Dill, Ken A; MacCallum, Justin L (2012) The protein-folding problem, 50 years on. Science 338:1042-6 |
| Perez, Alberto; Yang, Zheng; Bahar, Ivet et al. (2012) FlexE: Using elastic network models to compare models of protein structure. J Chem Theory Comput 8:3985-3991 |
| Ge, Hao; Presse, Steve; Ghosh, Kingshuk et al. (2012) Markov processes follow from the principle of maximum caliber. J Chem Phys 136:064108 |
| Prinz, Jan-Hendrik; Chodera, John D; Pande, Vijay S et al. (2011) Optimal use of data in parallel tempering simulations for the construction of discrete-state Markov models of biomolecular dynamics. J Chem Phys 134:244108 |
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