Simplified Models Of Protein Folding Research Articles

An exactly solvable model for aβ-hairpin with random interactions

I investigate a disordered version of a simplified model of proteinfolding, with binary degrees of freedom, applied to an idealβ-hairpin structure. Disorder is introduced by assuming that the contact energies areindependent and identically distributed random variables. The equilibrium free energy ofthe model is studied, by performing the exact calculation of its quenched value and provingthe self-averaging feature.

Kinetics of the Wako-Saitô-Muñoz-Eaton Model of Protein Folding

We consider a simplified model of protein folding, with binary degrees of freedom, whose equilibrium thermodynamics is exactly solvable. Based on this exact solution, the kinetics is studied in the framework of a local equilibrium approach, for which we prove that (i) the free energy decreases with time, (ii) the exact equilibrium is recovered in the infinite time limit, and (iii) the equilibration rate is an upper bound of the exact one. The kinetics is compared to the exact one for a small peptide and to Monte Carlo simulations for a longer protein; then rates are studied for a real protein and a model structure.

Funnel-like organization in sequence space determines the distributions of protein stability and folding rate preferred by evolution.

To understand the physical and evolutionary determinants of protein folding, we map out the complete organization of thermodynamic and kinetic properties for protein sequences that share the same fold. The exhaustive nature of our study necessitates using simplified models of protein folding. We obtain a stability map and a folding rate map in sequence space. Comparison of the two maps reveals a common organizational principle: optimality decreases more or less uniformly with distance from the optimal sequence in the sequence space. This gives a funnel-shaped optimality surface. Evolutionary dynamics of a sequence population on these two maps reveal how the simple organization of sequence space affects the distributions of stability and folding rate preferred by evolution.

Simplified models of protein folding exploiting the Lagrange radius of gyration of the hydrophobic component

Studies are performed using an early proposed, but relatively little investigated, model that efficiently emulates a hydrophobic funneling effect in protein folding. Its simple form, introduced as a further interaction term going as the square of the separation distance, is suitable for initial searches of conformational space by parallel computation and special processors which use polynomial representation of pair-wise interactions. Use of such a term implies calculation of the square of the Lagrange radius of gyration, but weighted by hydrophobicity rather than the masses of the constituent particles. The unusual choice is justified by the observation that experimental protein structures have forms consistent with this Lagrange formalism for hydrophobic residues, and so compact model structures have appropriate density. However, since the long-range and square-power form strains open structures and leads to rapid generation of compact structures, such that for most of the simulation chain the movements result in intra-chain clashes, a rapid rejection algorithm is employed that prunes out similar but high energy structures. The studies also explore the choice of the simplest possible models which might be used to explore folding. Hence pancreatic trypsin inhibitor is modeled as a ‘string-of-beads’, where the beads represent residues of differing hydrophobicity. This model has only limited success, and because there are no identifiable common centers of interaction between the ‘string-of-beads’ model and all-atom protein representations, it encounters the difficulties: (a) of comparing such highly simplified models with observed structures, and (b) of using such models as a starting point for conversion to all-atom models. The conclusion is that this solvent treatment is best applied to all-atom simulations from the outset. Nonetheless, low energy predictions obtained in this simple study can be considered as having promising features, and provide interesting insight into protein folding and the funneling contribution.

Robust proofs of NP-hardness for protein folding: general lattices and energy potentials.

This paper addresses the robustness of intractability arguments for simplified models of protein folding that use lattices to discretize the space of conformations that a protein can assume. We present two generalized NP-hardness results. The first concerns the intractability of protein folding independent of the lattice used to define the discrete protein-folding model. We consider a previously studied model and prove that for any reasonable lattice the protein-structure prediction problem is NP-hard. The second hardness result concerns the intractability of protein folding for a class of energy formulas that contains a broad range of mean force potentials whose form is similar to commonly used pair potentials (e.g., the Lennard-Jones potential). We prove that protein-structure prediction is NP-hard for any energy formula in this class. These are the first robust intractability results that identify sources of computational complexity of protein-structure prediction that transcend particular problem formulations.