Hydrogen Bonds, Hydrophobicity Forces and the Character of the Collapse Transition

We study the thermodynamic behavior of a model protein with 54 amino acids that is designed to form a three-helix bundle in its native state. The model contains three types of amino acids and five to six atoms per amino acid, and has the Ramachandran torsion angles as its only degrees of freedom. The force field is based on hydrogen bonds and effective hydrophobicity forces. We study how the character of the collapse transition depends on the strengths of these forces. For a suitable choice of these two parameters, it is found that the collapse transition is first-order-like and coincides with the folding transition. Also shown is that the corresponding one- and two-helix segments make less stable secondary structure than the three-helix sequence.Comment: 14 pages, 8 figure

Sequence-based study of two related proteins with different folding behaviors

ZSPA-1 is an engineered protein that binds to its parent, the three-helix-bundle Z domain of staphylococcal protein A. Uncomplexed ZSPA-1 shows a reduced helix content and a melting behavior that is less cooperative, compared with the wild-type Z domain. Here we show that the difference in folding behavior between these two sequences can be partly understood in terms of an off-lattice model with 5-6 atoms per amino acid and a minimalistic potential, in which folding is driven by backbone hydrogen bonding and effective hydrophobic attraction.Comment: 12 pages, 5 figure

Smooth Functional Transition along a Mutational Pathway with an Abrupt Protein Fold Switch

AbstractRecent protein design experiments have demonstrated that proteins can migrate between folds through the accumulation of substitution mutations without visiting disordered or nonfunctional points in sequence space. To explore the biophysical mechanism underlying such transitions we use a three-letter continuous protein model with seven atoms per amino acid to provide realistic sequence-structure and sequence-function mappings through explicit simulation of the folding and interaction of model sequences. We start from two 16-amino-acid sequences folding into an α-helix and a β-hairpin, respectively, each of which has a preferred binding partner with 35 amino acids. We identify a mutational pathway between the two folds, which features a sharp fold switch. By contrast, we find that the transition in function is smooth. Moreover, the switch in preferred binding partner does not coincide with the fold switch. Discovery of new folds in evolution might therefore be facilitated by following fitness slopes in sequence space underpinned by binding-induced conformational switching

Multisequence algorithm for coarse-grained biomolecular simulations: Exploring the sequence-structure relationship of proteins

Many biologically motivated problems naturally call for the investigation and comparison of molecular variants, such as determining the mechanisms of specificity in biomolecular interactions or the mechanisms of molecular evolution. We consider a generalized ensemble algorithm for coarse-grained simulations of biomolecules which allows the thermodynamic behavior of two or more sequences to be determined in a single multisequence run. By carrying out a random walk in sequence space, the method also enhances conformational sampling. Escape from local energy minima is accelerated by visiting sequences for which the minima are shallower or absent. We test the method on an intermediate-resolution coarse-grained model for protein folding with 3 amino acid types and explore the potential for large-scale coverage of sequence space by applying it to sets of more than 1,000 sequences each. The resulting thermodynamic data is used to analyze the structures and stability properties of sequences covering the space between folds with different secondary structures. Besides demonstrating that the method can be applied to large number of sequences, the results allow us to carry out a more systematic analysis of the biophysical properties of sequences along mutational pathways connecting pairs of different folds than has been previously possible. Please click Additional Files below to see the full abstract

Coupled Folding-Binding in a Hydrophobic/Polar Protein Model: Impact of Synergistic Folding and Disordered Flanks

Coupled folding-binding is central to the function of many intrinsically disordered proteins, yet not fully understood. With a continuous three-letter protein model, we explore the free-energy landscape of pairs of interacting sequences and how it is impacted by 1), variations in the binding mechanism; and 2), the addition of disordered flanks to the binding region. In particular, we focus on two sequences, one with 16 and one with 35 amino acids, which make a stable dimeric three-helix bundle at low temperatures. Three distinct binding mechanisms are realized by altering the stabilities of the individual monomers: docking, coupled folding-binding of a single α-helix, and synergistic folding and binding. Compared to docking, the free-energy barrier for binding is reduced when the single α-helix is allowed to fold upon binding, but only marginally. A greater reduction is found for synergistic folding, which in addition results in a binding transition state characterized by very few interchain contacts. Disordered flanking chain segments attached to the α-helix sequence can, despite a negligible impact on the dimer stability, lead to a downhill free-energy surface in which the barrier for binding is eliminated

Wind turbine wake simulation with explicit algebraic Reynolds stress modeling

Reynolds-averaged Navier–Stokes (RANS) simulations of wind turbine wakes are usually conducted with two-equation turbulence models based on the Boussinesq hypothesis; these are simple and robust but lack the capability of predicting various turbulence phenomena. Using the explicit algebraic Reynolds stress model (EARSM) of Wallin and Johansson (2000) can alleviate some of these deficiencies while still being numerically robust and only slightly more computationally expensive than the traditional two-equation models. The model implementation is verified with the homogeneous shear flow, half-channel flow, and square duct flow cases, and subsequently full three-dimensional wake simulations are run and analyzed. The results are compared with reference large-eddy simulation (LES) data, which show that the EARSM especially improves the prediction of turbulence anisotropy and turbulence intensity but that it also predicts less Gaussian wake profile shapes.</p