BBA - General Subjects (v.1850, #5)

Editorial preface by Lennart Nilsson; Johan Åqvist (859-860).

Molecular Mechanics (MM) is the method of choice for computational studies of biomolecular systems owing to its modest computational cost, which makes it possible to routinely perform molecular dynamics (MD) simulations on chemical systems of biophysical and biomedical relevance.As one of the main factors limiting the accuracy of MD results is the empirical force field used, the present paper offers a review of recent developments in the CHARMM additive force field, one of the most popular biomolecular force fields. Additionally, we present a detailed discussion of the CHARMM Drude polarizable force field, anticipating a growth in the importance and utilization of polarizable force fields in the near future. Throughout the discussion emphasis is placed on the force fields' parametrization philosophy and methodology.Recent improvements in the CHARMM additive force field are mostly related to newly found weaknesses in the previous generation of additive force fields. Beyond the additive approximation is the newly available CHARMM Drude polarizable force field, which allows for MD simulations of up to 1 μs on proteins, DNA, lipids and carbohydrates.Addressing the limitations ensures the reliability of the new CHARMM36 additive force field for the types of calculations that are presently coming into routine computational reach while the availability of the Drude polarizable force fields offers an inherently more accurate model of the underlying physical forces driving macromolecular structures and dynamics. This article is part of a Special Issue entitled “Recent developments of molecular dynamics”.
Keywords: Molecular dynamics; Empirical force field; Potential energy function; Molecular Mechanics; Computer-aided drug design; Biophysics;

Enhanced sampling techniques in molecular dynamics simulations of biological systems by Rafael C. Bernardi; Marcelo C.R. Melo; Klaus Schulten (872-877).
Molecular dynamics has emerged as an important research methodology covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local minima separated by high-energy barriers, which govern the biomolecular motion.In the past few decades methods have been developed that address the sampling problem, such as replica-exchange molecular dynamics, metadynamics and simulated annealing. Here we present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied.Enhanced sampling methods have been employed for a broad range of biological systems and the choice of a suitable method is connected to biological and physical characteristics of the system, in particular system size. While metadynamics and replica-exchange molecular dynamics are the most adopted sampling methods to study biomolecular dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromolecular complexes.Molecular dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biological function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: Enhanced sampling; Molecular dynamics; Replica-exchange molecular dynamics; Metadynamics; Generalized simulated annealing; Cellulosome;

Accelerated molecular dynamics (aMD) has been proven to be a powerful biasing method for enhanced sampling of biomolecular conformations on general-purpose computational platforms. Biologically important long timescale events that are beyond the reach of standard molecular dynamics can be accessed without losing the detailed atomistic description of the system in aMD. Over other biasing methods, aMD offers the advantages of tuning the level of acceleration to access the desired timescale without any advance knowledge of the reaction coordinate.Recent advances in the implementation of aMD and its applications to small peptides and biological macromolecules are reviewed here along with a brief account of all the aMD variants introduced in the last decade.In comparison to the original implementation of aMD, the recent variant in which all the rotatable dihedral angles are accelerated (RaMD) exhibits faster convergence rates and significant improvement in statistical accuracy of retrieved thermodynamic properties. RaMD in conjunction with accelerating diffusive degrees of freedom, i.e. dual boosting, has been rigorously tested for the most difficult conformational sampling problem, protein folding. It has been shown that RaMD with dual boosting is capable of efficiently sampling multiple folding and unfolding events in small fast folding proteins.RaMD with the dual boost approach opens exciting possibilities for sampling multiple timescales in biomolecules. While equilibrium properties can be recovered satisfactorily from aMD-based methods, directly obtaining dynamics and kinetic rates for larger systems presents a future challenge. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: Accelerated molecular dynamics; Enhanced sampling; Protein folding; Trp-cage; Villin headpiece; Chignolin;

A molecular simulation protocol to avoid sampling redundancy and discover new states by Marco Bacci; Andreas Vitalis; Amedeo Caflisch (889-902).
For biomacromolecules or their assemblies, experimental knowledge is often restricted to specific states. Ambiguity pervades simulations of these complex systems because there is no prior knowledge of relevant phase space domains, and sampling recurrence is difficult to achieve. In molecular dynamics methods, ruggedness of the free energy surface exacerbates this problem by slowing down the unbiased exploration of phase space. Sampling is inefficient if dwell times in metastable states are large.We suggest a heuristic algorithm to terminate and reseed trajectories run in multiple copies in parallel. It uses a recent method to order snapshots, which provides notions of “interesting” and “unique” for individual simulations. We define criteria to guide the reseeding of runs from more “interesting” points if they sample overlapping regions of phase space.Using a pedagogical example and an α-helical peptide, the approach is demonstrated to amplify the rate of exploration of phase space and to discover metastable states not found by conventional sampling schemes. Evidence is provided that accurate kinetics and pathways can be extracted from the simulations.The method, termed PIGS for Progress Index Guided Sampling, proceeds in unsupervised fashion, is scalable, and benefits synergistically from larger numbers of replicas. Results confirm that the underlying ideas are appropriate and sufficient to enhance sampling.In molecular simulations, errors caused by not exploring relevant domains in phase space are always unquantifiable and can be arbitrarily large. Our protocol adds to the toolkit available to researchers in reducing these types of errors. This article is part of a Special Issue entitled “Recent Developments of Molecular Dynamics.”
Keywords: Enhanced sampling; Molecular dynamics; Biomolecules; Simulation convergence; Transition path; Scalable algorithm;

Effect of external pulling forces on the length distribution of peptides by Matthew Batchelor; James Gowdy; Emanuele Paci (903-910).
The distribution of the length of a polypeptide, or that of the distance between any two of its atoms, is an important property as it can be analytically or numerically estimated for a number of polymer models. Importantly, it is directly measurable through a number of different experimental techniques. Length distributions can be straightforwardly assessed from molecular dynamics simulation; however, true convergence through full accurate coverage of the length range is difficult to achieve.The application of external constant force combined with the weighted-histogram analysis method (WHAM) is used to enhance sampling of unlikely ‘long’ or ‘short’ conformations and obtain the potential of mean force, while also collecting dynamic properties of the chain under variable tension.We demonstrate the utility of constant force to enhance the sampling efficiency and obtain experimentally measurable quantities on a series of short peptides, including charge-rich sequences that are known to be highly helical but whose properties are distinct from those of helical peptides undergoing helix–coil transitions.Force-enhanced sampling enhances the range and accuracy of the length-based potential of mean force of the peptide, in particular those sequences that contain increased numbers of charged residues.This approach allows users to simultaneously probe the force-dependent behaviour of peptides directly, enhance the range and accuracy of the length-based PMF of the peptide and also test the convergence of simulations by comparing the overlap of PMF profiles from different constant forces. This article is part of a special issue entitled Recent developments of molecular dynamics.
Keywords: Peptides; Length distribution; Force; Freely jointed chain; Alpha helix; Random coil;

Comparing the intrinsic dynamics of multiple protein structures using elastic network models by Edvin Fuglebakk; Sandhya P. Tiwari; Nathalie Reuter (911-922).
Elastic network models (ENMs) are based on the simple idea that a protein can be described as a set of particles connected by springs, which can then be used to describe its intrinsic flexibility using, for example, normal mode analysis. Since the introduction of the first ENM by Monique Tirion in 1996, several variants using coarser protein models have been proposed and their reliability for the description of protein intrinsic dynamics has been widely demonstrated. Lately an increasing number of studies have focused on the meaning of slow dynamics for protein function and its potential conservation through evolution. This leads naturally to comparisons of the intrinsic dynamics of multiple protein structures with varying levels of similarity.We describe computational strategies for calculating and comparing intrinsic dynamics of multiple proteins using elastic network models, as well as a selection of examples from the recent literature.The increasing interest for comparing dynamics across protein structures with various levels of similarity, has led to the establishment and validation of reliable computational strategies using ENMs. Comparing dynamics has been shown to be a viable way for gaining greater understanding for the mechanisms employed by proteins for their function. Choices of ENM parameters, structure alignment or similarity measures will likely influence the interpretation of the comparative analysis of protein motion.Understanding the relation between protein function and dynamics is relevant to the fundamental understanding of protein structure–dynamics–function relationship. This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: Elastic network models; Protein dynamics; Intrinsic dynamics; Normal mode analysis;

Solvation and cavity occupation in biomolecules by Gillian C. Lynch; John S. Perkyns; Bao Linh Nguyen; B. Montgomery Pettitt (923-931).
Solvation density locations are important for protein dynamics and structure. Knowledge of the preferred hydration sites at biomolecular interfaces and those in the interior of cavities can enhance understanding of structure and function. While advanced X-ray diffraction methods can provide accurate atomic structures for proteins, that technique is challenged when it comes to providing accurate hydration structures, especially for interfacial and cavity bound solvent molecules.Advances in integral equation theories which include more accurate methods for calculating the long-ranged Coulomb interaction contributions to the three-dimensional distribution functions make it possible to calculate angle dependent average solvent structure, accurately, around and inside irregular molecular conformations. The proximal radial distribution method provides another approximate method to determine average solvent structures for biomolecular systems based on a proximal or near neighbor solvent distribution that can be constructed from previously collected solvent distributions. These two approximate methods, along with all-atom molecular dynamics simulations are used to determine the solvent density inside the myoglobin heme cavity.Myoglobin is a good test system for these methods because the cavities are many and one is large, tens of Å3, but is shown to have only four hydration sites. These sites are not near neighbors which implies that the large cavity must have more than one way in and out.Our results show that main solvation sites are well reproduced by all three methods. The techniques also produce a clearly identifiable solvent pathway into the interior of the protein.The agreement between molecular dynamics and less computationally demanding approximate methods is encouraging.This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: Integral equations; Proximal radial distribution functions; Molecular dynamics; Solvation;

Free energy simulations are an important tool in the arsenal of computational biophysics, allowing the calculation of thermodynamic properties of binding or enzymatic reactions. This paper introduces methods to increase the accuracy and precision of free energy calculations by calculating the free energy costs of constraints during post-processing. The primary purpose of employing constraints for these free energy methods is to increase the phase space overlap between ensembles, which is required for accuracy and convergence.The free energy costs of applying or removing constraints are calculated as additional explicit steps in the free energy cycle. The new techniques focus on hard degrees of freedom and use both gradients and Hessian estimation. Enthalpy, vibrational entropy, and Jacobian free energy terms are considered.We demonstrate the utility of this method with simple classical systems involving harmonic and anharmonic oscillators, four-atomic benchmark systems, an alchemical mutation of ethane to methanol, and free energy simulations between alanine and serine. The errors for the analytical test cases are all below 0.0007 kcal/mol, and the accuracy of the free energy results of ethane to methanol is improved from 0.15 to 0.04 kcal/mol. For the alanine to serine case, the phase space overlaps of the unconstrained simulations range between 0.15 and 0.9%. The introduction of constraints increases the overlap up to 2.05%. On average, the overlap increases by 94% relative to the unconstrained value and precision is doubled.The approach reduces errors arising from constraints by about an order of magnitude. Free energy simulations benefit from the use of constraints through enhanced convergence and higher precision.The primary utility of this approach is to calculate free energies for systems with disparate energy surfaces and bonded terms, especially in multi-scale molecular mechanics/quantum mechanics simulations. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: Free energy calculation; Constraint correction; Molecular dynamics simulation; Normal mode analysis; Bennett's acceptance ratio;

Efficiently computing pathway free energies: New approaches based on chain-of-replica and Non-Boltzmann Bennett reweighting schemes by Phillip S. Hudson; Justin K. White; Fiona L. Kearns; Milan Hodoscek; Stefan Boresch; H. Lee Woodcock (944-953).
Accurately modeling condensed phase processes is one of computation's most difficult challenges. Include the possibility that conformational dynamics may be coupled to chemical reactions, where multiscale (i.e., QM/MM) methods are needed, and this task becomes even more daunting.Free energy simulations (i.e., molecular dynamics), multiscale modeling, and reweighting schemes.Herein, we present two new approaches for mitigating the aforementioned challenges. The first is a new chain-of-replica method (off-path simulations, OPS) for computing potentials of mean force (PMFs) along an easily defined reaction coordinate. This development is coupled with a new distributed, highly-parallel replica framework (REPDstr) within the CHARMM package. Validation of these new schemes is carried out on two processes that undergo conformational changes. First is the simple torsional rotation of butane, while a much more challenging glycosidic rotation (in vacuo and solvated) is the second. Additionally, a new approach that greatly improves (i.e., possibly an order of magnitude) the efficiency of computing QM/MM PMFs is introduced and compared to standard schemes. Our efforts are grounded in the recently developed method for efficiently computing QM-based free energies (i.e., QM-Non-Boltzmann Bennett, QM-NBB). Again, we validate this new technique by computing the QM/MM PMF of butane's torsional rotation.The OPS–REPDstr method is a promising new approach that overcomes many limitations of standard pathway simulations in CHARMM. The combination of QM-NBB with pathway techniques is very promising as it offers significant advantages over current procedures.Efficiently computing potentials of mean force is a major, unresolved, area of interest.This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: Reaction path; Free energy; QM/MM; Potential of mean force; Bennett's acceptance ratio; BAR; Reweighting; QM-Non-Boltzmann Bennett; QM-NBB;

Recent advances in QM/MM free energy calculations using reference potentials by Fernanda Duarte; Beat A. Amrein; David Blaha-Nelson; Shina C.L. Kamerlin (954-965).
Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way.Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field.The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed.As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: Multiscale modeling; QM/MM free energy calculation; Averaging potential; Reference potential; Mean field approximation;

Molecular dynamics and Monte Carlo simulations for protein–ligand binding and inhibitor design by Daniel J. Cole; Julian Tirado-Rives; William L. Jorgensen (966-971).
Non-nucleoside inhibitors of HIV reverse transcriptase are an important component of treatment against HIV infection. Novel inhibitors are sought that increase potency against variants that contain the Tyr181Cys mutation.Molecular dynamics based free energy perturbation simulations have been run to study factors that contribute to protein–ligand binding, and the results are compared with those from previous Monte Carlo based simulations and activity data.Predictions of protein–ligand binding modes are very consistent for the two simulation methods; the accord is attributed to the use of an enhanced sampling protocol. The Tyr181Cys binding pocket supports large, hydrophobic substituents, which is in good agreement with experiment.Although some discrepancies exist between the results of the two simulation methods and experiment, free energy perturbation simulations can be used to rapidly test small molecules for gains in binding affinity.Free energy perturbation methods show promise in providing fast, reliable and accurate data that can be used to complement experiment in lead optimization projects. This article is part of a Special Issue entitled “Recent developments of molecular dynamics”.Display Omitted
Keywords: Non-nucleoside inhibitors of HIV-1 reverse transcriptase; Replica exchange with solute tempering; Free energy perturbation; Enhanced sampling;

The number of high-resolution structures of pharmacologically relevant membrane proteins has been strongly increasing. This makes computing relative affinities of chemically similar compounds binding to a membrane protein possible in order to guide decision making in drug design. However, the preparation step of such calculations is time-consuming and complex.We extended the free energy workflow tool FEW, available in AMBER, towards facilitating the setup of molecular dynamics simulations with explicit membrane, and the setup and execution of effective binding energy calculations according to a 1-trajectory implicit solvent/implicit membrane MM-PBSA approach for multiple ligands binding to the same membrane protein.We validated the implemented protocol initially on two model systems, a sodium ion in the presence of an implicit membrane slab and a proton traversing the M2 proton-channel of the influenza A virus. For the latter, we found a good agreement for several important events along the proton pathway with those obtained in a recent computational study. Finally, we performed a case study on effective binding energy calculations for a set of inhibitors binding to the M2 proton-channel.From the case study, we estimate a considerable speed up in the setup and analysis times for implicit solvent/implicit membrane MM-PBSA calculations by the extended version of FEW compared to a manual preparation.Together with the overall runtime and the analysis results, this suggests that such type of calculations can be valuable in later stages of drug design projects on membrane proteins. This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: AMBER; Molecular dynamics simulations; Ion channel; Membrane protein; Drug design;

The key to predicting the stability of protein mutants lies in an accurate description and proper configurational sampling of the folded and denatured states by Andreas P. Eichenberger; Wilfred F. van Gunsteren; Sereina Riniker; Lukas von Ziegler; Niels Hansen (983-995).
The contribution of particular hydrogen bonds to the stability of a protein fold can be investigated experimentally as well as computationally by the construction of protein mutants which lack particular hydrogen-bond donors or acceptors with a subsequent determination of their structural stability. However, the comparison of experimental data with computational results is not straightforward. One of the difficulties is related to the representation of the unfolded state conformation.A series of molecular dynamics simulations of the 34-residue WW domain of protein Pin1 and 20 amide-to-ester mutants started from the X-ray crystal structure and the NMR solution structure are analysed in terms of backbone–backbone hydrogen bonding and differences in free enthalpies of folding in order to provide a structural interpretation of the experimental data available.The contribution of the different β-sheet hydrogen bonds to the relative stability of the mutants with respect to wild type cannot be directly inferred from experimental thermal denaturation temperatures or free enthalpies of chaotrope denaturation for the different mutants, because some β-sheet hydrogen bonds show sizeable variation in occurrence between the different mutants.A proper representation of unfolded state conformations appears to be essential for an adequate description of relative stabilities of protein mutants.The simulations may be used to link the structural Boltzmann ensembles to relative free enthalpies of folding between mutants and wild-type protein and show that unfolded conformations have to be treated with a sufficient level of detail in free energy calculations of protein stability. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: Protein stability; Molecular dynamics; Free energy; Hydrogen bonds;

The nature of ligand motion in proteins is difficult to characterize directly usingexperiment. Specifically, it is unclear to what degree these motions are coupled.All-atom simulations are used to sample ligand motion in truncated Hemoglobin N. A transition network analysis including ligand- and protein-degrees of freedom is used to analyze the microscopic dynamics.Clustering of two different subsets of MD trajectories highlights the importance of a diverse and exhaustive description to define the macrostates for a ligand-migration network. Monte Carlo simulations on the transition matrices from one particular clustering are able to faithfully capture the atomistic simulations. Contrary to clustering by ligand positions only, including a protein degree of freedom yields considerably improved coarse grained dynamics. Analysis with and without imposing detailed balance agree closely which suggests that the underlying atomistic simulations are converged with respect to sampling transitions between neighboring sites.Protein and ligand dynamics are not independent from each other and ligand migration through globular proteins is not passive diffusion.Transition network analysis is a powerful tool to analyze and characterize the microscopic dynamics in complex systems. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: Truncated hemoglobin; Network; Ligand dynamics;

Electrostatic free energies in translational GTPases: Classic allostery and the rest by Thomas Simonson; Alexey Aleksandrov; Priyadarshi Satpati (1006-1016).
GTPases typically switch between an inactive, OFF conformation and an active, ON conformation when a GDP ligand is replaced by GTP. Their ON/OFF populations and activity thus depend on the stabilities of four protein complexes, two apo-protein forms, and GTP/GDP in solution. A complete characterization is usually not possible experimentally and poses major challenges for simulations. We review the most important methodological challenges and we review thermodynamic data for two GTPases involved in translation of the genetic code: archaeal Initiation Factors 2 and 5B (aIF2, aIF5B). One main challenge is the multiplicity of states and conformations, including those of GTP/GDP in solution. Another is force field accuracy, especially for interactions of GTP/GDP with co-bound divalent Mg2 + ions. The calculation of electrostatic free energies also poses specific challenges, and requires careful protocols. For aIF2, experiments and earlier simulations showed that it is a “classic” GTPase, with distinct ON/OFF conformations that prefer to bind GTP and GDP, respectively. For aIF5B, we recently proposed a non-classic mechanism, where the ON/OFF states differ only in the protonation state of Glu81 in the nucleotide binding pocket. This model is characterized here using free energy simulations. The methodological analysis should help future studies, while the aIF2, aIF5B examples illustrate the diversity of ATPase/GTPase mechanisms. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: Molecular recognition; induced fit; molecular dynamics; continuum electrostatics; computational chemistry;

The epidermal growth factor receptor (EGFR) is the best characterised member of the receptor tyrosine kinases, which play an important role in signalling across mammalian cell membranes. The EGFR juxtamembrane (JM) domain is involved in the mechanism of activation of the receptor, interacting with the anionic lipid phosphatidylinositol 4,5-bisphosphate (PIP2) in the intracellular leaflet of the cell membrane.Multiscale MD simulations were used to characterize PIP2–JM interactions. Simulations of the transmembrane helix plus JM region (TM–JM) dimer (PDB:2M20) in both PIP2-containing and PIP2-depleted lipid bilayer membranes revealed the interactions of the JM with PIP2 and other lipids.PIP2 forms strong interactions with the basic residues in the R645–R647 motif of the JM domain resulting in clustering of PIP2 around the protein. This association of PIP2 and the JM domain aids stabilization of JM-A dimer away from the membrane. Mutation (R645N/R646N/R647N) or PIP2-depletion results in deformation of the JM-A dimer and changes in JM–membrane interactions.These simulations support the proposal that the positively charged residues at the start of the JM-A domain stabilize the JM-A helices in an orientation away from the membrane surface through binding to PIP2, thus promoting a conformation corresponding to an asymmetric (i.e. activated) kinase.This study indicates that MD simulations may be used to characterise JM/lipid interactions, thus helping to define their role in the mechanisms of receptor tyrosine kinases. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: EGFR; Juxtamembrane domain; PIP2; Molecular dynamics; Lipid bilayer;

Molecular dynamics for computational proteomics of methylated histone H3 by Cédric Grauffel; Roland H. Stote; Annick Dejaegere (1026-1040).
Post-translational modifications of histones, and in particular of their disordered N-terminal tails, play a major role in epigenetic regulation. The identification of proteins and proteic domains that specifically bind modified histones is therefore of paramount importance to understand the molecular mechanisms of epigenetics.We performed an energetic analysis using the MM/PBSA method in order to study known complexes between methylated histone H3 and effector domains of the PHD family. We then developed a simple molecular dynamics based predictive model based on our analysis.We present a thorough validation of our procedure, followed by the computational predictions of new PHD domains specific for binding histone H3 methylated on lysine 4 (K4).PHD domains recognize methylated K4 on histone H3 in the context of a linear interaction motif (LIM) formed by the first four amino acids of histone H3 as opposed to recognition of a single methylated site.PHD domains with different sequences find chemically equivalent solutions for stabilizing the histone LIM and these can be identified from energetic analysis. This analysis, in turn, allows for the identification of new PHD domains that bind methylated H3K4 using information that cannot be retrieved from sequence comparison alone.Molecular dynamics simulations can be used to devise computational proteomics protocols that are both easy to implement and interpret, and that yield reliable predictions that compare favorably to and complement experimental proteomics methods. This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: Molecular dynamics; Protein interaction; Histone; Proteomics; Epigenetics;

Convergence and reproducibility in molecular dynamics simulations of the DNA duplex d(GCACGAACGAACGAACGC) by Rodrigo Galindo-Murillo; Daniel R. Roe; Thomas E. Cheatham (1041-1058).
The structure and dynamics of DNA are critically related to its function. Molecular dynamics simulations augment experiment by providing detailed information about the atomic motions. However, to date the simulations have not been long enough for convergence of the dynamics and structural properties of DNA.Molecular dynamics simulations performed with AMBER using the ff99SB force field with the parmbsc0 modifications, including ensembles of independent simulations, were compared to long timescale molecular dynamics performed with the specialized Anton MD engine on the B-DNA structure d(GCACGAACGAACGAACGC). To assess convergence, the decay of the average RMSD values over longer and longer time intervals was evaluated in addition to assessing convergence of the dynamics via the Kullback–Leibler divergence of principal component projection histograms.These molecular dynamics simulations—including one of the longest simulations of DNA published to date at ~ 44 μs—surprisingly suggest that the structure and dynamics of the DNA helix, neglecting the terminal base pairs, are essentially fully converged on the ~ 1–5 μs timescale.We can now reproducibly converge the structure and dynamics of B-DNA helices, omitting the terminal base pairs, on the μs time scale with both the AMBER and CHARMM C36 nucleic acid force fields. Results from independent ensembles of simulations starting from different initial conditions, when aggregated, match the results from long timescale simulations on the specialized Anton MD engine.With access to large-scale GPU resources or the specialized MD engine “Anton” it is possible for a variety of molecular systems to reproducibly and reliably converge the conformational ensemble of sampled structures. This article is part of a Special Issue entitled: Recent developments of molecular dynamics.Display Omitted
Keywords: DNA dynamics; Nucleic acid; Base pair fraying; Convergence; Reproducibility; Molecular dynamics;

All-atom crystal simulations of DNA and RNA duplexes by Chunmei Liu; Pawel A. Janowski; David A. Case (1059-1071).
Molecular dynamics simulations can complement experimental measures of structure and dynamics of biomolecules. The quality of such simulations can be tested by comparisons to models refined against experimental crystallographic data.The duplex structures conform much more closely to the average structure seen in the crystal than do structures extracted from a solution simulation with the same force field. Sequence-dependent variations in helical parameters, and in groove widths, are largely maintained in the crystal structure, but are smoothed out in solution. However, the integrity of the crystal lattice is slowly degraded in both simulations, with the result that the interfaces between chains become heterogeneous. This problem is more severe for the DNA crystal, which has fewer inter-chain hydrogen bond contacts than does the RNA crystal.Crystal simulations using current force fields reproduce many features of observed crystal structures, but suffer from a gradual degradation of the integrity of the crystal lattice.The results offer insights into force-field simulations that test their ability to preserve weak interactions between chains, which will be of importance also in non-crystalline applications that involve binding and recognition.This article is part of a Special Issue entitled Recent developments of molecular dynamics.
Keywords: Molecular dynamics; Nucleic acids; Crystal;

Molecular dynamic simulations of protein/RNA complexes: CRISPR/Csy4 endoribonuclease by Carolina Estarellas; Michal Otyepka; Jaroslav Koča; Pavel Banáš; Miroslav Krepl; Jiří Šponer (1072-1090).
Many prokaryotic genomes comprise Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) offering defense against foreign nucleic acids. These immune systems are conditioned by the production of small CRISPR-derived RNAs matured from long RNA precursors. This often requires a Csy4 endoribonuclease cleaving the RNA 3′-end.We report extended explicit solvent molecular dynamic (MD) simulations of Csy4/RNA complex in precursor and product states, based on X-ray structures of product and inactivated precursor (55 simulations; ~ 3.7 μs in total).The simulations identify double-protonated His29 and deprotonated terminal phosphate as the likely dominant protonation states consistent with the product structure. We revealed potential substates consistent with Ser148 and His29 acting as the general base and acid, respectively. The Ser148 could be straightforwardly deprotonated through solvent and could without further structural rearrangements deprotonate the nucleophile, contrasting similar studies investigating the general base role of nucleobases in ribozymes. We could not locate geometries consistent with His29 acting as general base. However, we caution that the X-ray structures do not always capture the catalytically active geometries and then the reactive structures may be unreachable by the simulation technique.We identified potential catalytic arrangement of the Csy4/RNA complex but we also report limitations of the simulation technique. Even for the dominant protonation state we could not achieve full agreement between the simulations and the structural data.Potential catalytic arrangement of the Csy4/RNA complex is found. Further, we provide unique insights into limitations of simulations of protein/RNA complexes, namely, the influence of the starting experimental structures and force field limitations. This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: Cas6 superfamily; Endoribonuclease; RNA cleavage; Protein/RNA complex; Molecular dynamic simulation; Force field;

Protein-DNA binding often involves dramatic conformational changes such as protein folding and DNA bending. While thermodynamic aspects of this behavior are understood, and its biological function is often known, the mechanism by which the conformational changes occur is generally unclear. By providing detailed structural and energetic data, molecular dynamics simulations have been helpful in elucidating and rationalizing protein-DNA binding.This review will summarize recent atomistic molecular dynamics simulations of the conformational dynamics of DNA and protein-DNA binding. A brief overview of recent developments in DNA force fields is given as well.Simulations have been crucial in rationalizing the intrinsic flexibility of DNA, and have been instrumental in identifying the sequence of binding events, the triggers for the conformational motion, and the mechanism of binding for a number of important DNA-binding proteins.Molecular dynamics simulations are an important tool for understanding the complex binding behavior of DNA-binding proteins. With recent advances in force fields and rapid increases in simulation time scales, simulations will become even more important for future studies. This article is part of a Special Issue entitled Recent developments of molecular dynamics.Display Omitted
Keywords: Molecular dynamics; Protein-DNA; DNA bending; Protein folding; Simulation;