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The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ.

Artificial molecular switches, rotors, and machines are set to establish design rules and applications beyond their biological counterparts. Herein we exemplify the role of noncovalent interactions and transient rearrangements in the complex behavior of supramolecular rotors caged in a 2D metal-organic coordination network. Combined scanning tunneling microscopy experiments and molecular dynamics modeling of a supramolecular rotor with respective rotation rates matching with 0.2 kcal mol(-1) (9 meV) precision, identify key steps in collective rotation events and reconfigurations. We notably reveal that stereoisomerization of the chiral trimeric units entails topological isomerization whereas rotation occurs in a topology conserving, two-step asynchronous process. In supramolecular constructs, distinct displacements of subunits occur inducing a markedly lower rotation barrier as compared to synchronous mechanisms of rigid rotors. Moreover, the chemical environment can be instructed to control the system dynamics. Our observations allow for a definition of mechanical cooperativity based on a significant reduction of free energy barriers in supramolecules compared to rigid molecules.

Proton transfer in macromolecular systems is a fascinating yet elusive process. In the last ten years, molecular simulations have shown to be a useful tool to unveil the atomistic mechanism. Notwithstanding, the large number of degrees of freedom involved make the accurate description of the process very hard even for the case of proton diffusion in bulk water. Here, multi-state empirical valence bond molecular dynamics simulations in conjunction with complex network analysis are applied to study proton transfer in liquid water. Making use of a transition network formalism, this approach takes into account the time evolution of several coordinates simultaneously. Our results provide evidence for a strong dependence of proton transfer on the length of the hydrogen bond solvating the Zundel complex, with proton transfer enhancement as shorter bonds are formed at the acceptor site. We identify six major states (nodes) on the network leading from the "special pair" to a more symmetric Zundel complex required for transferring the proton. Moreover, the second solvation shell specifically rearranges to promote the transfer, reiterating the idea that solvation beyond the first shell of the Zundel complex plays a crucial role in the process.

Recent advances in computational power and simulation programs finally delivered the first examples of reversible folding for small proteins with an all-atom description. But having at hand the atomistic details of the process did not lead to a straightforward interpretation of the mechanism. For the case of the Fip35 WW-domain where multiple long trajectories of 100 μs are available from D. E. Shaw Research, different interpretations emerged. Some of those are in clear contradiction with each other while others are in qualitative agreement. Here, we present a network-based analysis of the same data by looking at the local fluctuations of conventional order parameters for folding. We found that folding occurs through two major pathways, one almost four times more populated than the other. Each pathway involves the formation of an intermediate with one of the two hairpins in a native configuration. The quantitative agreement of our results with a state-of-the-art reaction coordinate optimization procedure as well as qualitative agreement with other Markov-state-models and different simulation schemes provides strong evidence for a multiple folding pathways scenario with the presence of intermediates.

We develop a three-dimensional lattice Boltzmann (LB) model accounting for directional interactions between water-like molecules, based on the so-called Ben-Naim (BN) potential [A. Ben-Naim, Molecular Theory of Water and Aqueous Solutions: Part I: Understanding Water (World Scientific Publishing Company, 2010); "Statistical mechanics of 'waterlike' particles in two dimensions. I. Physical model and application of the Percus-Yevick equation," J. Chem. Phys. 54, 3682 (1971)]. The water-like molecules are represented by rigid tetrahedra, with two donors and two acceptors at the corners and interacting with neighboring tetrahedra, sitting on the nodes of a regular lattice. The tetrahedra are free to rotate about their centers under the drive of the torque arising from the interparticle potential. The orientations of the water molecules are evolved in time via an overdamped Langevin dynamics for the torque, which is solved by means of a quaternion technique. The resulting advection-diffusion-reaction equation for the quaternion components is solved by a LB method, acting as a dynamic minimizer for the global energy of the fluid. By adding thermal fluctuations to the torque equation, the model is shown to reproduce some microscopic features of real water, such as an average number of hydrogen bonds per molecules (HBs) between 3 and 4, in a qualitative agreement with microscopic water models. Albeit slower than a standard LB solver for ordinary fluids, the present scheme opens up potentially far-reaching scenarios for multiscale applications based on a coarse-grained representation of the water solvent.

A large number of water models exist for molecular simulations. They differ in the ability to reproduce specific features of real water instead of others, like the correct temperature for the density maximum or the diffusion coefficient. Past analysis mostly concentrated on ensemble quantities, while few data were reported on the different microscopic behavior. Here, we compare seven widely used classical water models (SPC, SPC/E, TIP3P, TIP4P, TIP4P-Ew, TIP4P/2005, and TIP5P) in terms of their local structure-forming capabilities through hydrogen bonds for temperatures ranging from 210 to 350 K by the introduction of a set of order parameters taking into account the configuration of up to the second solvation shell. We found that all models share the same structural pattern up to a temperature shift. When this shift is applied, all models overlap onto a master curve. Interestingly, increased stabilization of fully coordinated structures extending to at least two solvation shells is found for models that are able to reproduce the correct position of the density maximum. Our results provide a self-consistent atomic-level structural comparison protocol, which can be of help in elucidating the influence of different water models on protein structure and dynamics.

Molecular dynamics (MD) simulations provide essential information about the thermodynamics and kinetics of proteins. Technological advances in both hardware and algorithms have seen this method accessing timescales that used to be unreachable only few years ago. The quest to simulate slow, biologically relevant macromolecular conformational changes, is still open. Here, we present an approximate approach to increase the speed of MD simulations by a factor of ∼4.5. This is achieved by using a large integration time step of 7 fs, in combination with frozen covalent bonds and look-up tables for nonbonded interactions of the solvent. Extensive atomistic MD simulations for a flexible peptide in water show that the approach reproduces the peptide's equilibrium conformational changes, preserving the essential properties of both thermodynamics and kinetics. Comparison of this approximate method with state-of-the-art implicit solvation simulations indicates that the former provides a better description of the underlying free-energy surface. Finally, simulations of a 33-residue peptide show that these fast MD settings are readily applicable to investigate biologically relevant systems., (Copyright © 2011 Wiley Periodicals, Inc.)

Network-based methods provide an accurate description of the free-energy landscape of peptides and proteins sampled by molecular dynamics simulations. To that end, it is necessary to group the individual snapshots in a meaningful way. The inherent structures (ISs) provide an appropriate discretization of the trajectory into microstates, avoiding problems that can arise in clustering algorithms that have been used previously. In this work, different minimization protocols to obtain the IS of a peptide are investigated on the basis of cut-based free-energy profiles. It is found that a computationally more efficient quasi-Newtonian algorithm provides quantitative agreement to the classical conjugate gradient method in terms of the population of the peptide substates and the energy barriers separating them. That is, despite the fact that the two algorithms can occasionally quench a given peptide snapshot in different potential energy minima, the overall properties of the system are not affected. As reported by others, atom permutations affect the calculation of the IS, requiring an improved implementation of current potential energy functions., (Copyright © 2010 Wiley Periodicals, Inc.)

Molecular dynamics (MD) simulations provide essential information about the thermodynamics and dynamics of proteins. To construct the free-energy surface from equilibrium trajectories, it is necessary to group the individual snapshots in a meaningful way. The inherent structures (IS) are shown to provide an appropriate discretization of the trajectory and to avoid problems that can arise in clustering algorithms that have been employed previously. The IS-based approach is illustrated with a 30-ns room temperature "native" state MD simulation of a 10-residue peptide in a beta-hairpin conformation. The transitions between the IS are used to construct a configuration space network from which a one-dimensional free-energy profile is obtained with the mincut method. The results demonstrate that the IS approach is useful and that even for this simple system, there exists a nontrivial organization of the native state into several valleys separated by barriers as high as 3 kcal/mol. Further, by introducing a coarse-grained network, it is demonstrated that there are multiple pathways connecting the valleys. This scenario is hidden when the snapshots of the trajectory are used directly with rmsd clustering to compute the free-energy profile. Application of the IS approach to the native state of the PDZ2 signaling domain indicates its utility for the study of biologically relevant systems.