Exploring multiple timescale motions in protein GB3 using accelerated molecular dynamics and NMR spectroscopy

Biological function relies on the complex spectrum of conformational dynamics occurring in biomolecules. We have combined Accelerated Molecular Dynamics (AMD) with experimental results derived from NMR to probe multiple time-scale motions in the third IgG-binding domain of Protein G (GB3). AMD is shown to accurately reproduce the amplitude and distribution of slow motional modes characterized using residual dipolar couplings, reporting on dynamics up to the millisecond timescale. In agreement with experiment, larger amplitude slower motions are localized in the beta-strand/loop motif spanning residues 14-24 and in loop 42-44. Principal component analysis shows these fluctuations participating in the primary mode, substantiating the existence of a correlated motion traversing the beta-sheet that culminates in maximum excursions at the active site of the molecule. Fast dynamics were simulated using extensive standard MD simulations and compared to order parameters extracted from 15N relaxation. Notably 60 2-ns fully solvated MD simulations exploring the different conformational substates sampled from AMD resulted in better reproduction of order parameters compared to the same number of simulations starting from the relaxed crystal structure. This illustrates the inherent dependence of protein dynamics on local conformational topology. The results provide rare insight into the complex hierarchy of dynamics present in GB3 and allow us to develop a model of the conformational landscape native to the protein, appearing as a steep sided potential well whose flat bottom comprises multiple similar but discrete conformational substates.     

Estimating kinetic rates from accelerated molecular dynamics simulations: alanine dipeptide in explicit solvent as a case study

Molecular dynamics (MD) simulation is the standard computational technique used to obtain information on the time evolution of the conformations of proteins and many other molecular systems. However, for most biological systems of interest, the time scale for slow conformational transitions is still inaccessible to standard MD simulations. Several sampling methods have been proposed to address this issue, including the accelerated molecular dynamics method. In this work, we study the extent of sampling of the phi/psi space of alanine dipeptide in explicit water using accelerated molecular dynamics and present a framework to recover the correct kinetic rate constant for the helix to beta-strand transition. We show that the accelerated MD can drastically enhance the sampling of the phi/psi conformational phase space when compared to normal MD. In addition, the free energy density plots of the phi/psi space show that all minima regions are accurately sampled and the canonical distribution is recovered. Moreover, the kinetic rate constant for the helix to beta-strand transition is accurately estimated from these simulations by relating the diffusion coefficient to the local energetic roughness of the energy landscape. Surprisingly, even for such a low barrier transition, it is difficult to obtain enough transitions to accurately estimate the rate constant when one uses normal MD.     

Coarse-grained protein molecular dynamics simulations

A limiting factor in biological science is the time-scale gap between experimental and computational trajectories. At this point, all-atom explicit solvent molecular dynamics (MD) are clearly too expensive to explore long-range protein motions and extract accurate thermodynamics of proteins in isolated or multimeric forms. To reach the appropriate time scale, we must then resort to coarse graining. Here we couple the coarse-grained OPEP model, which has already been used with activated methods, to MD simulations. Two test cases are studied: the stability of three proteins around their experimental structures and the aggregation mechanisms of the Alzheimer's Abeta16-22 peptides. We find that coarse-grained isolated proteins are stable at room temperature within 50 ns time scale. Based on two 220 ns trajectories starting from disordered chains, we find that four Abeta16-22 peptides can form a three-stranded beta sheet. We also demonstrate that the reptation move of one chain over the others, first observed using the activation-relaxation technique, is a kinetically important mechanism during aggregation. These results show that MD-OPEP is a particularly appropriate tool to study qualitatively the dynamics of long biological processes and the thermodynamics of molecular assemblies.     

Essential dynamics for the study of microstructures in liquids

Essential Dynamics (ED) is a powerful tool for analyzing molecular dynamics (MD) simulations and it is widely adopted for conformational analysis of large molecular systems such as, for example, proteins and nucleic acids. In this study, we extend the use of ED to the study of clusters of arbitrary size constituted by weakly interacting particles, for example, atomic clusters and supramolecular systems. The key feature of the method we present is the identification of the relevant atomic‐molecular clusters to be analyzed by ED for extracting the information of interest. The application of this computational approach allows a straightforward and unbiased conformational study of the local microstructures in liquids, as emerged from semiclassical MD simulations. The good performance of the method is demonstrated by calculating typical observables of liquid water, that is, NMR, NEXAFS O1s, and IR spectra, known to be rather sensitive both to the presence and to the conformational features of hydrogen‐bonded clusters. © 2014 Wiley Periodicals, Inc.     

A generalized Langevin dynamics approach to model solvent dynamics effects on proteins via a solvent-accessible surface. The carboxypeptidase A inhibitor protein as a model

A generalized Langevin dynamics (GLD) scheme is derived for (bio)macromolecules having internal structure, arbitrary shapes and a size larger than solvent molecules (i.e. proteins). The concept of solvent-accessible surface area (SASA) is used to incorporate solvent effects via external forces thereby avoiding its explicit molecular representation. A simulation algorithm is implemented in the GROMOS molecular dynamics (MD) program including random forces and memory effects, while solvation effects enter via derivatives of the surface area. The potato carboxypeptidase inhibitor (PCI), a small protein, is used to numerically test the approach. This molecule has N- and C-terminal tails whose structure and fluctuations are solvent dependent. A 1-ns MD trajectory was analyzed in depth. X-ray and NMR structures are used in conjunction with MD simulations with and without explicit solvent to gauge the quality of the results. All the analyses showed that the GLD simulation approached the results obtained for the MD simulation with explicit simple-point-charge-model water molecules. The SASAs of the polar atoms show a natural exposure towards the solvent direction. A FLS solvent simulation was completed in order to sense memory effects. The approach and results presented here could be of great value for developing alternatives to the use of explicit solvent molecules in the MD simulation of proteins, expanding its use and the time-scale explored. Received: 2 February 2000 / Revised: 12 March 2000 / Accepted: 26 May 2000 / Published online: 2 November 2000     

Interpreting protein structural dynamics from NMR chemical shifts

In this investigation, semiempirical NMR chemical shift prediction methods are used to evaluate the dynamically averaged values of backbone chemical shifts obtained from unbiased molecular dynamics (MD) simulations of proteins. MD-averaged chemical shift predictions generally improve agreement with experimental values when compared to predictions made from static X-ray structures. Improved chemical shift predictions result from population-weighted sampling of multiple conformational states and from sampling smaller fluctuations within conformational basins. Improved chemical shift predictions also result from discrete changes to conformations observed in X-ray structures, which may result from crystal contacts, and are not always reflective of conformational dynamics in solution. Chemical shifts are sensitive reporters of fluctuations in backbone and side chain torsional angles, and averaged (1)H chemical shifts are particularly sensitive reporters of fluctuations in aromatic ring positions and geometries of hydrogen bonds. In addition, poor predictions of MD-averaged chemical shifts can identify spurious conformations and motions observed in MD simulations that may result from force field deficiencies or insufficient sampling and can also suggest subsets of conformational space that are more consistent with experimental data. These results suggest that the analysis of dynamically averaged NMR chemical shifts from MD simulations can serve as a powerful approach for characterizing protein motions in atomistic detail.     

Application of torsion angle molecular dynamics for efficient sampling of protein conformations

We investigate the application of torsion angle molecular dynamics (TAMD) to augment conformational sampling of peptides and proteins. Interesting conformational changes in proteins mainly involve torsional degrees of freedom. Carrying out molecular dynamics in torsion space does not only explicitly sample the most relevant degrees of freedom, but also allows larger integration time steps with elimination of the bond and angle degrees of freedom. However, the covalent geometry needs to be fixed during internal coordinate dynamics, which can introduce severe distortions to the underlying potential surface in the extensively parameterized modern Cartesian-based protein force fields. A "projection" approach (Katritch et al. J Comput Chem 2003, 24, 254-265) is extended to construct an accurate internal coordinate force field (ICFF) from a source Cartesian force field. Torsion crossterm corrections constructed from local molecular fragments, together with softened van der Waals and electrostatic interactions, are used to recover the potential surface and incorporate implicit bond and angle flexibility. MD simulations of dipeptide models demonstrate that full flexibility in both the backbone phi/psi and side chain chi1 angles are virtually restored. The efficacy of TAMD in enhancing conformational sampling is then further examined by folding simulations of small peptides and refinement experiments of protein NMR structures. The results show that an increase of several fold in conformational sampling efficiency can be reliably achieved. The current study also reveals some complicated intrinsic properties of internal coordinate dynamics, beyond energy conservation, that can limit the maximum size of the integration time step and thus the achievable gain in sampling efficiency.     

Rotamer decomposition and protein dynamics: Efficiently analyzing dihedral populations from molecular dynamics

Molecular mechanics methods have matured into powerful methods to understand the dynamics and flexibility of macromolecules and especially proteins. As multinanosecond to microsecond length molecular dynamics (MD) simulations become commonplace, advanced analysis tools are required to generate scientifically useful information from large amounts of data. Some of the key degrees of freedom to understand protein flexibility and dynamics are the amino acid residue side chain dihedral angles. In this work, we present an easily automated way to summarize and understand the relevant dihedral populations. A tremendous reduction in complexity is achieved by describing dihedral timeseries in terms of histograms decomposed into Gaussians. Using the familiar and widely studied protein lysozyme, it is demonstrated that our approach captures essential properties of protein structure and dynamics. A simple classification scheme is proposed that indicates the rotational state population for each dihedral angle of interest and allows a decision if a given side chain or peptide backbone fragment remains rigid during the course of an MD simulation, adopts a converged distribution between conformational substates or has not reached convergence yet. © 2012 Wiley Periodicals, Inc.     

Adaptive Accelerated Molecular Dynamics (Ad-AMD) Revealing the Molecular Plasticity of P450cam

An extended accelerated molecular dynamics (AMD) methodology called adaptive AMD is presented. Adaptive AMD (Ad-AMD) is an efficient and robust conformational space sampling algorithm that is particularly-well suited to proteins with highly structured potential energy surfaces exhibiting complex, large-scale collective conformational transitions. Ad-AMD simulations of substrate-free P450cam reveal that this system exists in equilibrium between a fully and partially open conformational state. The mechanism for substrate binding depends on the size of the ligand. Larger ligands enter the P450cam binding pocket, and the resulting substrate-bound system is trapped in an open conformation via a population shift mechanism. Small ligands, which fully enter the binding pocket, cause an induced-fit mechanism, resulting in the formation of an energetically stable closed conformational state. These results are corroborated by recent experimental studies and potentially provide detailed insight into the functional dynamics and conformational behavior of the entire cytochrome-P450 superfamily.     

Efficient evaluation of sampling quality of molecular dynamics simulations by clustering of dihedral torsion angles and Sammon mapping

A direct conformational clustering and mapping approach for peptide conformations based on backbone dihedral angles has been developed and applied to compare conformational sampling of Met-enkephalin using two molecular dynamics (MD) methods. Efficient clustering in dihedrals has been achieved by evaluating all combinations resulting from independent clustering of each dihedral angle distribution, thus resolving all conformational substates. In contrast, Cartesian clustering was unable to accurately distinguish between all substates. Projection of clusters on dihedral principal component (PCA) subspaces did not result in efficient separation of highly populated clusters. However, representation in a nonlinear metric by Sammon mapping was able to separate well the 48 highest populated clusters in just two dimensions. In addition, this approach also allowed us to visualize the transition frequencies between clusters efficiently. Significantly, higher transition frequencies between more distinct conformational substates were found for a recently developed biasing-potential replica exchange MD simulation method allowing faster sampling of possible substates compared to conventional MD simulations. Although the number of theoretically possible clusters grows exponentially with peptide length, in practice, the number of clusters is only limited by the sampling size (typically much smaller), and therefore the method is well suited also for large systems. The approach could be useful to rapidly and accurately evaluate conformational sampling during MD simulations, to compare different sampling strategies and eventually to detect kinetic bottlenecks in folding pathways.     

Thermodynamic features and environmental effects in a two-states molecular device under strict electrochemical control

The thermodynamic features of a synthetic molecular thread, recently proposed acting as an electrochemically-driven two-states molecular device, have been systematically investigated by means of nanoseconds time-scale classical molecular dynamics (MD) simulations and basic statistical mechanics relations. Results clearly suggest that the accessible conformational space of such a potential molecular switch shows a strong environmental dependence: the reversible molecular switching mechanism observed in liquid solution is effectively suppressed when the synthetic thread is hypothesized working in vacuo. Such a result has been related to a subtle energetic/entropic balance experienced by the whole system (solute and solvent) during the intramolecular conformational transition of the molecular thread, in presence and in absence of the solvent.     

Simulation of conformational transitions by the restricted perturbation-targeted molecular dynamics method

A method for the simulation of conformational transitions is presented. The method, based on targeted molecular dynamics (TMD), limits the conformational change at each molecular dynamics step to a fixed size, that minimizes the root mean square deviation from the target. The method is more efficient than standard TMD and yields lower energy pathways, but, like the TMD method, requires only a single molecular dynamics simulation. Test calculations and comparisons with standard TMD calculations for the alanine dipeptide with the analytic continuum electrostatics implicit solvent model are presented.     

An application of coupled reference interaction site model/molecular dynamics to the conformational analysis of the alanine dipeptide

We present an application of our recently proposed coupled reference interaction site model (RISM) molecular dynamics (MD) solvation free energy methodology [Freedman and Truong, Chem. Phys. Lett. 381, 362 (2003); J. Chem. Phys. 121, 2187 (2004)] to study the conformational stability of alanine dipeptide in aqueous solution. In this methodology, radial distribution functions obtained from a single MD simulation are substituted into a RISM expression for solvation free energy. Consequently, iterative solution of the RISM equation is not needed. The relative solvation free energies of seven different conformations of the alanine dipeptide in aqueous solution are calculated. Results from the coupled RISM/MD methodology are in good agreement with those from earlier simulations using the accurate free energy perturbation approach, showing that the alphaR conformation is most stabilized by solution. This study establishes a framework for applying this coupled RISM/MD method to larger biological systems.     

Parametrization, molecular dynamics simulation, and calculation of electron spin resonance spectra of a nitroxide spin label on a polyalanine alpha-helix

The nitroxide spin label 1-oxyl-2,2,5,5-tetramethylpyrroline-3-methyl-methanethiosulfonate (MTSSL), commonly used in site-directed spin labeling of proteins, is studied with molecular dynamics (MD) simulations. After developing force field parameters for the nitroxide moiety and the spin label linker, we simulate MTSSL attached to a polyalanine alpha-helix in explicit solvent to elucidate the factors affecting its conformational dynamics. Electron spin resonance spectra at 9 and 250 GHz are simulated in the time domain using the MD trajectories and including global rotational diffusion appropriate for the tumbling of T4 Lysozyme in solution. Analysis of the MD simulations reveals the presence of significant hydrophobic interactions of the spin label with the alanine side chains.     

Accelerating chemical reactions: exploring reactive free-energy surfaces using accelerated ab initio molecular dynamics

A biased potential molecular dynamics simulation approach, accelerated molecular dynamics (AMD), has been implemented in the framework of ab initio molecular dynamics for the study of chemical reactions. Using two examples, the double proton transfer reaction in formic acid dimer and the hypothetical adiabatic ring opening and subsequent rearrangement reactions in methylenecyclopropane, it is demonstrated that ab initio AMD can be readily employed to efficiently explore the reactive potential energy surface, allowing the prediction of chemical reactions and the identification of metastable states. An adaptive variant of the AMD method is developed, which additionally affords an accurate representation of both the free-energy surface and the mechanism associated with the chemical reaction of interest and can also provide an estimate of the reaction rate.