Efficient Sampling of High-Dimensional Free-Energy Landscapes with Parallel Bias Metadynamics

Metadynamics accelerates sampling of molecular dynamics while reconstructing thermodynamic properties of selected descriptors of the system. Its main practical difficulty originates from the compromise between keeping the number of descriptors small for efficiently exploring their multidimensional free-energy landscape and biasing all of the slow motions of a process. Here we illustrate on a model system and on the tryptophan-cage miniprotein parallel bias metadynamics, a method that overcomes this issue by simultaneously applying multiple low-dimensional bias potentials

Exhaustively Sampling Peptide Adsorption with Metadynamics

Simulating the adsorption of a peptide or protein and obtaining quantitative estimates of thermodynamic observables remains challenging for many reasons. One reason is the dearth of molecular scale experimental data available for validating such computational models. We also lack simulation methodologies that effectively address the dual challenges of simulating protein adsorption: overcoming strong surface binding and sampling conformational changes. Unbiased classical simulations do not address either of these challenges. Previous attempts that apply enhanced sampling generally focus on only one of the two issues, leaving the other to chance or brute force computing. To improve our ability to accurately resolve adsorbed protein orientation and conformational states, we have applied the Parallel Tempering Metadynamics in the Well-Tempered Ensemble (PTMetaD-WTE) method to several explicitly solvated protein/surface systems. We simulated the adsorption behavior of two peptides, LKα14 and LKβ15, onto two self-assembled monolayer (SAM) surfaces with carboxyl and methyl terminal functionalities. PTMetaD-WTE proved effective at achieving rapid convergence of the simulations, whose results elucidated different aspects of peptide adsorption including: binding free energies, side chain orientations, and preferred conformations. We investigated how specific molecular features of the surface/protein interface change the shape of the multidimensional peptide binding free energy landscape. Additionally, we compared our enhanced sampling technique with umbrella sampling and also evaluated three commonly used molecular dynamics force fields

Car–Parrinello Molecular Dynamics + Metadynamics Study of High-Temperature Methanol Oxidation Reactions Using Generic Collective Variables

We used Car–Parrinello molecular dynamics (CPMD) and metadynamics in conjunction with the recently introduced social permutation invariant collective coordinates to study the mechanism of high-temperature methanol oxidation. Using a set of biased MD trajectories, we collected specific elementary reactions that arise during the simulations and assembled their connectivity in a small reaction network. A subset of the reaction network generated with metadynamics is compared to a consensus reaction network generated from many literature sources, and the many similarities indicate that this approach may be a useful way to enumerate bimolecular radical reactions in complex systems. We also demonstrated some intrinsic similarities to atomic contact maps used in our metadynamics approach and the reaction matrix/operators that are found in common mechanism generation algorithms. Extending the capabilities of these new generic collective variables for the study of complex reaction networks can help overcome limitations of enhanced sampling methods in the study of chemical reactions

Destabilization of Human Serum Albumin by Ionic Liquids Studied Using Enhanced Molecular Dynamics Simulations

Ionic liquid (IL) containing solvents can change the structure, dynamics, function, and stability of proteins. In order to investigate the mechanisms by which ILs induce structural changes in a large multidomain protein, we study the interactions of human serum albumin (HSA) with two different ILs, 1-butyl-3-methylimidazolium tetrafluoroborate and choline dihydrogen phosphate. Root mean square deviation and fluctuation calculations indicate that high concentrations of ILs in mixtures with water lead to protein structures that remain close to their crystallographic structures on time scales of hundreds of nanoseconds. To overcome potential time scale limitations due to the high viscosity of the solvent, we employed enhanced sampling techniques to estimate the free energy of an experimentally determined important transition within the protein structure. Metadynamics simulations show that the free energy landscape of the unfolding of loop 1 of domain I is different in the presence of ILs than it is in water, consistent with previously published experimental evidence. We then apply essential dynamics coarse graining to systematically predict differences in the dynamics of proteins solvated in IL–water mixtures versus pure water systems. We also demonstrate that the presence of ionic liquids changes the distribution of intermolecular distances among several ligands, indicating that the protein structure swells in the presence of certain ILs, consistent with experimental evidence

Ionic Liquids Can Selectively Change the Conformational Free-Energy Landscape of Sugar Rings

We investigated the conformational free energy landscape of glucose solvated in water and in the ionic liquids (ILs) 1-butyl-3-methylimidazolium chloride ([Bmim]­[Cl]) and 1-butyl-3-methylimidazoulim boron tetrafluoride ([Bmim]­[BF₄]). To quantify equilibrium thermodynamic solvent effects, molecular dynamics simulations in conjunction with enhanced sampling based on the metadynamics framework were used. The results show that the solvent choice induces significant differences in the equilibrium ring structures, which may help further resolve the molecular mechanism governing IL-mediated cellulose dissolution

Lifting the Curse of Dimensionality on Enhanced Sampling of Reaction Networks with Parallel Bias Metadynamics

A common challenge to applying metadynamics to the study of complex systems is selecting the proper collective variables to bias. The advent of generic collective variables, specifically social permutation invariant (SPRINT) coordinates, has helped to address this challenge by reducing the level of a priori knowledge required to just basic chemical fundamentals. However, the efficiency of biasing SPRINT coordinates can be severely handicapped by the high dimensionality of the bias potential. Here, we circumvent this deficiency by biasing SPRINT coordinates using the parallel bias metadynamics framework. We demonstrate the efficacy of this method to efficiently explore a complex system, without any prior knowledge about transition pathways, by applying it to study the decomposition of γ-ketohydroperoxide and generating a comprehensive reaction network of relevant pathways. The reduction in both computational cost and chemical intuition makes this method a promising option for studying complex reacting systems

Strong Electrostatic Interactions Lead to Entropically Favorable Binding of Peptides to Charged Surfaces

Thermodynamic analyses can provide key insights into the origins of protein self-assembly on surfaces, protein function, and protein stability. However, obtaining quantitative measurements of thermodynamic observables from unbiased classical simulations of peptide or protein adsorption is challenging because of sampling limitations brought on by strong biomolecule/surface binding forces as well as time scale limitations. We used the parallel tempering metadynamics in the well-tempered ensemble (PTMetaD-WTE) enhanced sampling method to study the adsorption behavior and thermodynamics of several explicitly solvated model peptide adsorption systems, providing new molecular-level insight into the biomolecule adsorption process. Specifically studied were peptides LKα14 and LKβ15 and trpcage miniprotein adsorbing onto a charged, hydrophilic self-assembled monolayer surface functionalized with a carboxylic acid/carboxylate headgroup and a neutral, hydrophobic methyl-terminated self-assembled monolayer surface. Binding free energies were calculated as a function of temperature for each system and decomposed into their respective energetic and entropic contributions. We investigated how specific interfacial features such as peptide/surface electrostatic interactions and surface-bound ion content affect the thermodynamic landscape of adsorption and lead to differences in surface-bound conformations of the peptides. Results show that upon adsorption to the charged surface, configurational entropy gains of the released solvent molecules dominate the configurational entropy losses of the bound peptide. This behavior leads to an apparent increase in overall system entropy upon binding and therefore to the surprising and seemingly nonphysical result of an apparent increased binding free energy at elevated temperatures. Opposite effects and conclusions are found for the neutral surface. Additional simulations demonstrate that by adjusting the ionic strength of the solution, results that show the expected physical behavior, i.e., peptide binding strength that decreases with increasing temperature or is independent of temperature altogether, can be recovered on the charged surface. On the basis of this analysis, an overall free energy for the entire thermodynamic cycle for peptide adsorption on charged surfaces is constructed and validated with independent simulations

Structural and Dynamic Features of Candida rugosa Lipase 1 in Water, Octane, Toluene, and Ionic Liquids BMIM-PF6 and BMIM-NO3

Ionic liquids (ILs) and organic chemicals can be used as solvents in biochemical reactions to influence the structural and dynamic features of the enzyme, sometimes detrimentally. In this work we report the results for molecular dynamics simulations of Candida rugosa lipase (CRL) in ILs BMIM-PF₆ and BMIM-NO₃, as well as organic solvents toluene and octane in an effort to explore the role of solvent on the structure and dynamics of an enzyme known to be active in many nonaqueous media. Simulations of CRL in water were also included for comparison, bringing the aggregate simulation time to over 2.8 μs. At both 310 and 375 K the ILs significantly dampen protein dynamics and trap the system near its starting structure. Structural changes in the enzyme follow the viscosity of the solvent, with the enzyme deviating from its initial structure the most in water and the least in BMIM-PF₆. Interactions between the enzyme surface and the solvent in the IL simulations show that contacts are dominated by the IL anion, which is ascribed to a broader spatial distribution of positively charged protein residues and reduced mobility of the cation due to the size of the imadazolium ring

Lifting the Curse of Dimensionality on Enhanced Sampling of Reaction Networks with Parallel Bias Metadynamics

A common challenge to applying metadynamics to the study of complex systems is selecting the proper collective variables to bias. The advent of generic collective variables, specifically social permutation invariant (SPRINT) coordinates, has helped to address this challenge by reducing the level of a priori knowledge required to just basic chemical fundamentals. However, the efficiency of biasing SPRINT coordinates can be severely handicapped by the high dimensionality of the bias potential. Here, we circumvent this deficiency by biasing SPRINT coordinates using the parallel bias metadynamics framework. We demonstrate the efficacy of this method to efficiently explore a complex system, without any prior knowledge about transition pathways, by applying it to study the decomposition of γ-ketohydroperoxide and generating a comprehensive reaction network of relevant pathways. The reduction in both computational cost and chemical intuition makes this method a promising option for studying complex reacting systems

Structure, Dynamics, and Activity of Xylanase Solvated in Binary Mixtures of Ionic Liquid and Water

We have discovered that a family 11 xylanase from <i>Trichoderma longibrachiatum</i> maintains significant activity in low concentrations of the ionic liquids (IL) 1-ethyl-3-methyl-imidazolium acetate ([EMIM]­[OAc]) or 1-ethyl-3-methyl-imidazolium ethyl sulfate ([EMIM]­[EtSO₄]) in water. In order to understand the mechanisms by which the ionic liquids affect the activity of xylanase, we conducted molecular dynamics simulations of the enzyme in various concentrations of the cosolvent. The simulations show that higher concentrations of ionic liquid correlate with less deviation from the starting crystallographic structure. Dynamic motion of the protein is severely dampened by even the lowest tested concentrations of ionic liquid as measured by root-mean-square fluctuation. Principal component analysis shows that the characteristics of the main modes of enzyme motion are greatly affected by the choice of solvent. Cations become kinetically trapped in the binding pocket, allowing them to act as a competitive inhibitor to the natural substrate. Dynamic light scattering and kinetic studies evaluated the stability of the enzyme in the new solvents. These studies indicate that likely factors in the loss of enzyme activity for this xylanase are the dampening of dynamic motion and kinetic trapping of cations in the binding pocket as opposed to the denaturing of the protein