An evolutionary strategy for all-atom folding of the 60-amino-acid bacterial ribosomal protein l20

We have investigated an evolutionary algorithm for de novo all-atom folding of the bacterial ribosomal protein L20. We report results of two simulations that converge to near-native conformations of this 60-amino-acid, four-helix protein. We observe a steady increase of "native content" in both simulated ensembles and a large number of near-native conformations in their final populations. We argue that these structures represent a significant fraction of the low-energy metastable conformations, which characterize the folding funnel of this protein. These data validate our all-atom free-energy force field PFF01 for tertiary structure prediction of a previously inaccessible structural family of proteins. We also compare folding simulations of the evolutionary algorithm with the basin-hopping technique for the Trp-cage protein. We find that the evolutionary algorithm generates a dynamic memory in the simulated population, which leads to faster overall convergence.

Basin hopping simulations for all-atom protein folding

We investigate different protocols of the basin hopping technique for de novo protein folding. Using the protein free-energy force field PFF01 we report the reproducible all-atom folding of the 20-amino-acid tryptophan-cage protein [Protein Data Bank (PDB) code: 112y] and of the recently discovered 26-amino-acid potassium channel blocker (PDB code: 1wqc), which exhibits an unusual fold. We find that simulations with increasing cycle length and random starting temperatures perform best in comparison with other parametrizations. The basin hopping technique emerges as a simple but very efficient and robust workhorse for all-atom protein folding.

All-atom folding of the three-helix HIV accessory protein with an adaptive parallel tempering method

All-atom protein structure prediction from the amino acid sequence alone remains an important goal of biophysical chemistry. Recent progress in force field development and validation suggests that the PFF01 free-energy force field correctly predicts the native conformation of various helical proteins as the global optimum of its free-energy surface. Reproducible protein structure prediction requires the availability of efficient optimization methods to locate the global minima of such complex potentials. Here we investigate an adapted version of the parallel tempering method as an efficient parallel stochastic optimization method for protein structure prediction. Using this approach we report the reproducible all-atom folding of the three-helix 40 amino acid HIV accessory protein from random conformations to within 2.4 A backbone RMS deviation from the experimental structure with modest computational resources.

Reproducible protein folding with the stochastic tunneling method

We report the reproducible folding of the 20 amino-acid protein trp cage using a novel version of the stochastic tunneling method and a recently developed all-atom protein free-energy force field. Six of 25 simulations reached an energy within 1 kcal/mol of the best energy, all of which correctly predicted the native experimental structure of the protein, in total eight simulations converged to the native structure. We find a strong correlation between energy and root-mean-square deviation to the native structure for all simulations.