Jim Pfaendtner

Nucleotide-dependent conformational states of actin

The influence of the state of the bound nucleotide (ATP, ADP-Pi, or ADP) on the conformational free-energy landscape of actin is investigated. Nucleotide-dependent folding of the DNase-I binding (DB) loop in monomeric actin and the actin trimer is carried out using all-atom molecular dynamics (MD) calculations accelerated with a multiscale implementation of the metadynamics algorithm. Additionally, an investigation of the opening and closing of the actin nucleotide binding cleft is performed. Nucleotide-dependent free-energy profiles for all of these conformational changes are calculated within the framework of metadynamics. We find that in ADP-bound monomer, the folded and unfolded states of the DB loop have similar relative free-energy. This result helps explain the experimental difficulty in obtaining an ordered crystal structure for this region of monomeric actin. However, we find that in the ADP-bound actin trimer, the folded DB loop is stable and in a free-energy minimum. It is also demonstrated that the nucleotide binding cleft favors a closed conformation for the bound nucleotide in the ATP and ADP-Pi states, whereas the ADP state favors an open confirmation, both in the monomer and trimer. These results suggest a mechanism of allosteric interactions between the nucleotide binding cleft and the DB loop. This behavior is confirmed by an additional simulation that shows the folding free-energy as a function of the nucleotide cleft width, which demonstrates that the barrier for folding changes significantly depending on the value of the cleft width.

Systematic Multiscale Parameterization of Heterogeneous Elastic Network Models of Proteins

We present a method to parameterize heterogeneous elastic network models (heteroENMs) of proteins to reproduce the fluctuations observed in atomistic simulations. Because it is based on atomistic simulation, our method allows the development of elastic coarse-grained models of proteins under different conditions or in different environments. The method is simple and applicable to models at any level of coarse-graining. We validated the method in three systems. First, we computed the persistence length of ADP-bound F-actin, using a heteroENM model. The value of 6.1 +/- 1.6 microm is consistent with the experimentally measured value of 9.0 +/- 0.5 microm. We then compared our method to a uniform elastic network model and a realistic extension algorithm via covariance Hessian (REACH) model of carboxy myoglobin, and found that the heteroENM method more accurately predicted mean-square fluctuations of alpha-carbon atoms. Finally, we showed that the method captures critical differences in effective harmonic interactions for coarse-grained models of the N-terminal Bin/amphiphysin/Rvs (N-BAR) domain of amphiphysin, by building models of N-BAR both bound to a membrane and free in solution.

A Systematic Methodology for Defining Coarse-Grained Sites in Large Biomolecules

Coarse-grained (CG) models of biomolecules have recently attracted considerable interest because they enable the simulation of complex biological systems on length-scales and timescales that are inaccessible for atomistic molecular dynamics simulation. A CG model is defined by a map that transforms an atomically detailed configuration into a CG configuration. For CG models of relatively small biomolecules or in cases that the CG and all-atom models have similar resolution, the construction of this map is relatively straightforward and can be guided by chemical intuition. However, it is more challenging to construct a CG map when large and complex domains of biomolecules have to be represented by relatively few CG sites. This work introduces a new and systematic methodology called essential dynamics coarse-graining (ED-CG). This approach constructs a CG map of the primary sequence at a chosen resolution for an arbitrarily complex biomolecule. In particular, the resulting ED-CG method variationally determines the CG sites that reflect the essential dynamics characterized by principal component analysis of an atomistic molecular dynamics trajectory. Numerical calculations illustrate this approach for the HIV-1 CA protein dimer and ATP-bound G-actin. Importantly, since the CG sites are constructed from the primary sequence of the biomolecule, the resulting ED-CG model may be better suited to appropriately explore protein conformational space than those from other CG methods at the same degree of resolution.

Structure and dynamics of the actin filament.

We used all-atom molecular dynamics simulations to investigate the structure and properties of the actin filament, starting with either the recent Oda model or the older Holmes model. Simulations of monomeric and polymerized actin show that polymerization changes the nucleotide-binding cleft, bringing together the Q137 side chain and bound ATP in a way that may enhance the ATP hydrolysis rate in the filament. Simulations with different bound nucleotides and conformations of the DNase I binding loop show that the persistence length of the filament depends only on loop conformation. Computational modeling reveals how bound phalloidin stiffens actin filaments and inhibits the release of gamma-phosphate from ADP-P(i) actin.

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.

Efficient Simulation of Explicitly Solvated Proteins in the Well-Tempered Ensemble

Herein, we report significant reduction in the cost of combined parallel tempering and metadynamics simulations (PTMetaD). The efficiency boost is achieved using the recently proposed well-tempered ensemble (WTE) algorithm. We studied the convergence of PTMetaD-WTE conformational sampling and free energy reconstruction of an explicitly solvated 20-residue tryptophan-cage protein (trp-cage). A set of PTMetaD-WTE simulations was compared to a corresponding standard PTMetaD simulation. The properties of PTMetaD-WTE and the convergence of the calculations were compared. The roles of the number of replicas, total simulation time, and adjustable WTE parameter γ were studied.

Actin filament remodeling by actin depolymerization factor/cofilin

We investigate, using molecular dynamics, how the severing protein, actin depolymerization factor (ADF)/cofilin, modulates the structure, conformational dynamics, and mechanical properties of actin filaments. The actin and cofilactin filament bending stiffness and corresponding persistence lengths obtained from all-atom simulations are comparable to values obtained from analysis of thermal fluctuations in filament shape. Filament flexibility is strongly affected by the nucleotide-linked conformation of the actin subdomain 2 DNase-I binding loop and the filament radial mass density distribution. ADF/cofilin binding between subdomains 1 and 3 of a filament subunit triggers reorganization of subdomain 2 of the neighboring subunit such that the DNase-I binding loop (DB-loop) moves radially away from the filament. Repositioning of the neighboring subunit DB-loop significantly weakens subunit interactions along the long-pitch helix and lowers the filament bending rigidity. Lateral filament contacts between the hydrophobic loop and neighboring short-pitch helix monomers in native filaments are also compromised with cofilin binding. These works provide a molecular interpretation of biochemical solution studies documenting the disruption of filament subunit interactions and also reveal the molecular basis of actin filament allostery and its linkage to ADF/cofilin binding.

Structure, dynamics, and activity of xylanase solvated in binary mixtures of ionic liquid and water.

We have discovered that a family 11 xylanase from Trichoderma longibrachiatum 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.

The General AMBER Force Field (GAFF) Can Accurately Predict Thermodynamic and Transport Properties of Many Ionic Liquids

We have applied molecular dynamics to calculate thermodynamic and transport properties of a set of 19 room-temperature ionic liquids. Since accurately simulating the thermophysical properties of solvents strongly depends upon the force field of choice, we tested the accuracy of the general AMBER force field, without refinement, for the case of ionic liquids. Electrostatic point charges were developed using ab initio calculations and a charge scaling factor of 0.8 to more accurately predict dynamic properties. The density, heat capacity, molar enthalpy of vaporization, self-diffusivity, and shear viscosity of the ionic liquids were computed and compared to experimentally available data, and good agreement across a wide range of cation and anion types was observed. Results show that, for a wide range of ionic liquids, the general AMBER force field, with no tuning of parameters, can reproduce a variety of thermodynamic and transport properties with similar accuracy to that of other published, often IL-specific, force fields.

Defining Coarse-Grained Representations of Large Biomolecules and Biomolecular Complexes from Elastic Network Models

Coarse-grained (CG) models of large biomolecular complexes enable simulations of these systems over long timescales that are not accessible for atomistic molecular dynamics (MD) simulations. A systematic methodology, called essential dynamics coarse-graining (ED-CG), has been developed for defining coarse-grained sites in a large biomolecule. The method variationally determines the CG sites so that key dynamic domains in the protein are preserved in the CG representation. The original ED-CG method relies on a principal component analysis (PCA) of a MD trajectory. However, for many large proteins and multi-protein complexes such an analysis may not converge or even be possible. This work develops a new ED-CG scheme using an elastic network model (ENM) of the protein structure. In this procedure, the low-frequency normal modes obtained by ENM are used to define dynamic domains and to define the CG representation accordingly. The method is then applied to several proteins, such as the HIV-1 CA protein dimer, ATP-bound G-actin, and the Arp2/3 complex. Numerical results show that ED-CG with ENM (ENM-ED-CG) is much faster than ED-CG with PCA because no MD is necessary. The ENM-ED-CG models also capture functional essential dynamics of the proteins almost as well as those using full MD with PCA. Therefore, the ENM-ED-CG method may be better suited to coarse-grain a very large biomolecule or biomolecular complex that is too computationally expensive to be simulated by conventional MD, or when a high resolution atomic structure is not even available.