Energy Landscapes of a Pair of Adsorbed Peptides.

The wide relevance of peptide adsorption in natural and synthetic contexts means it has attracted much attention. Molecular dynamics (MD) simulation has been widely used in these endeavors. Much of this has focused on single peptides due to the computational effort required to capture the rare events that characterize their adsorption. This focus is, however, of limited practical relevance as in reality, most systems of interest operate in the nondilute regime where peptides will interact with other adsorbed peptides. As an alternative to MD simulation, we have used energy landscape mapping (ELM) to investigate two met-enkephalin molecules adsorbed at a gas/graphite interface. Major conformations of the adsorbed peptides and the connecting transition states are elucidated along with the associated energy barriers and rates of exchange. The last of these makes clear that MD simulations are currently of limited use in probing the co-adsorption of two peptides, let alone more. The constant volume heat capacity as a function of temperature is also presented. Overall, this study represents a significant step toward characterizing peptide adsorption beyond the dilute limit.

Energy Landscape Mapping and Replica Exchange Molecular Dynamics of an Adsorbed Peptide.

Adsorption of peptides at the interface between a fluid and a solid occurs widely in both nature and applications. Knowing the dominant conformations of adsorbed peptides and the energy barriers between them is of interest for a variety of reasons. Molecular dynamics (MD) simulation is a widely used technique that can yield such understanding. However, the complexity of the energy landscapes of adsorbed peptides means that comprehensive exploration of the energy landscape by MD simulation is challenging. An alternative approach is energy landscape mapping (ELM), which involves the location of stationary points on the potential energy surface, and its analysis to determine, for example, the pathways and energy barriers between them. In the study reported here, a comparison is made between this technique and replica exchange molecular dynamics (REMD) for met-enkephalin adsorbed at the interface between graphite and the gas phase: the first ever direct comparison of these techniques for adsorbed peptides. Both methods yield the dominant adsorbed peptide conformations. Unlike REMD, however, ELM readily allows the identification of the connectivity and energy barriers between the favored conformations, transition paths, and structures between these conformations and the impact of entropy. It also permits the calculation of the constant volume heat capacity although the accuracy of this is limited by the sampling of high-energy minima. Overall, compared to REMD, ELM provides additional insights into the adsorbed peptide system provided sufficient care is taken to ensure that key parts of the landscape are adequately sampled.

Characterizing the Switching Transitions of an Adsorbed Peptide by Mapping the Potential Energy Surface.

Peptide adsorption occurs across technology, medicine, and nature. The functions of adsorbed peptides are related to their conformation. In the past, molecular simulation methods such as molecular dynamics have been used to determine key conformations of adsorbed peptides. However, the transitions between these conformations often occur too slowly to be modeled reliably by such methods. This means such transitions are less well understood. In the study reported here, discrete path sampling is used for the first time to study the potential energy surface of an adsorbed peptide (polyalanine) and the transition pathways between various stable adsorbed conformations that have been identified in prior work by two of the authors [ Mijajlovic , M. ; Biggs , M. J. J. Phys. Chem. C 2007 , 111 , 15839 - 15847 ]. Mechanisms for the switching of adsorbed polyalanine between the stable conformations are elucidated along with the energetics of these switches.

Molecular-level understanding of protein adsorption at the interface between water and a strongly interacting uncharged solid surface.

Although protein adsorption on solids is of immense relevance, experimental limitations mean there is still a remarkable lack of understanding of the adsorption mechanism, particularly at a molecular level. By subjecting 240+ molecular dynamics simulations of two peptide/water/solid surface systems to statistical analysis, a generalized molecular level mechanism for peptide adsorption has been identified for uncharged surfaces that interact strongly with the solution phase. This mechanism is composed of three phases: (1) biased diffusion of the peptide from the bulk phase toward the surface; (2) anchoring of the peptide to the water/solid interface via interaction of a hydrophilic group with the water adjacent to the surface or a strongly interacting hydrophobic group with the surface; and (3) lockdown of the peptide on the surface via a slow, stepwise and largely sequential adsorption of its residues, which we term 'statistical zippering'. The adsorption mechanism is dictated by the existence of water layers adjacent to the solid and orientational ordering therein. By extending the solid into the solution by ~8 Å and endowing it with a charged character, the water layers ensure the peptide feels the effect of the solid at a range well beyond the dispersion force that arises from it, thus inducing biased diffusion from afar. The charging of the interface also facilitates anchoring of the peptide near the surface via one of its hydrophilic groups, allowing it time it would otherwise not have to rearrange and lockdown. Finally, the slowness of the lockdown process is dictated by the need for the peptide groups to replace adjacent tightly bound interfacial water.

Free energy of adsorption for a peptide at a liquid/solid interface via nonequilibrium molecular dynamics.

Protein adsorption is of wide interest including in many technological applications such as tissue engineering, nanotechnology, biosensors, drug delivery, and vaccine production among others. Understanding the fundamentals of such technologies and their design would be greatly aided by an ability to efficiently predict the conformation of an adsorbed protein and its free energy of adsorption. In the study reported here, we show that this is possible when data obtained from nonequilibrium thermodynamic integration (NETI) combined with steered molecular dynamics (SMD) is subject to bootstrapping. For the met-enkephalin pentapeptide at a water-graphite interface, we were able to obtain accurate predictions for the location of the adsorbed peptide and its free energy of adsorption from around 50 and 80 SMD simulations, respectively. It was also shown that adsorption in this system is both energetically and entropically driven. The free energy of adsorption was also decomposed into that associated with formation of the cavity in the water near the graphite surface sufficient to accommodate the adsorbed peptide and that associated with insertion of the peptide into this cavity. This decomposition reveals that the former is modestly energetically and entropically unfavorable, whereas the latter is the opposite in both regards to a much greater extent.

On potential energy models for EA-based ab initio protein structure prediction.

Ab initio protein structure prediction involves determination of the three-dimensional (3D) conformation of proteins on the basis of their amino acid sequence, a potential energy (PE) model that captures the physics of the interatomic interactions, and a method to search for and identify the global minimum in the PE (or free energy) surface such as an evolutionary algorithm (EA). Many PE models have been proposed over the past three decades and more. There is currently no understanding of how the behavior of an EA is affected by the PE model used. The study reported here shows that the EA behavior can be profoundly affected: the EA performance obtained when using the ECEPP PE model is significantly worse than that obtained when using the Amber, OPLS, and CVFF PE models, and the optimal EA control parameter values for the ECEPP model also differ significantly from those associated with the other models.

Switching in of Ac-(Ala)10-NHMe at a solid surface.

Using molecular simulation, we show how Ac-(Ala)(10)-NHMe adsorbed on a solid surface switches between three conformations at distinct surface energies. The first switch is from an alpha-helix to a 3.1(10)-helix. The second involves further stretching to a 2(7)-helix. This switching has several potential applications including memory in molecular computers to motility elements in nanotechnology, and could be relevant to biological activity of proteins near solid surfaces (e.g., nano and aerosol particles) and disease processes induced by such interactions.

On use of the Amber potential with the Langevin dipole method.

Inclusion of solvent effects in biomolecular simulations is most ideally done using explicit methods, as they are able to capture the heterogeneous environment typical of biomolecules and systems involving them (e.g., proteins at solid interfaces). Common explicit methods based on molecular solvent models (e.g., TIP and SPC models) and molecular dynamic or Monte Carlo simulation are computationally expensive and are, therefore, not well-suited to situations where many simulations are required (e.g., in the ab initio structure prediction or design contexts). In such cases, more coarse-grained explicit approaches such as the Langevin dipole (LD) method of Warshel and co-workers are more appropriate. The recent incarnations of the LD method appear to produce good solvation free energy estimates. These incarnations use charges and solute structures obtained from high-level quantum mechanics simulations. As such an approach is clearly not possible for larger solutes or when many structures are to be considered, an alternative must be sought. One possibility is to use structures and charges derived from an existing analytical potential model-we report on such a coupling here with the Amber potential model. The accuracy and computational performance of this hybrid approach, which we term LD-Amber to distinguish it from previous incarnations of the LD method, was assessed by comparing results obtained from the approach with those from experiment and other theoretical methods for the solvation of 18 amino acid analogues and the alanine dipeptide. This comparison shows that the LD-Amber approach can yield results in line with experiment both qualitatively and quantitatively and is as accurate as other explicit methods while being computationally much cheaper.