Molecular dynamics simulations reveal the parallel stranded d(GGGA)3GGG DNA quadruplex folds via multiple paths from a coil-like ensemble

G-quadruplexes (G4s) are non-canonical nucleic acid structures that fold through complex processes. Characterization of the G4 folding landscape may help to elucidate biological roles of G4s but is challenging both experimentally and computationally. Here, we achieved complete folding of a three-quartet parallel DNA G4 with (GGGA)3GGG sequence using all-atom explicit-solvent enhanced-sampling molecular dynamics (MD) simulations. The simulations suggested early formation of guanine stacks in the G-tracts, which behave as semi-rigid blocks in the folding process. The folding continues via the formation of a collapsed compact coil-like ensemble. Structuring of the G4 from the coil then proceeds via various cross-like, hairpin, slip-stranded and two-quartet ensembles and can bypass the G-triplex structure. Folding of the parallel G4 does not appear to involve any salient intermediates and is a multi-pathway process. We also carried out an extended set of simulations of parallel G-hairpins. While parallel G-hairpins are extremely unstable when isolated, they are more stable inside the coil structure. On the methodology side, we show that the AMBER DNA force field predicts the folded G4 to be less stable than the unfolded ensemble, uncovering substantial force-field issues. Overall, we provide unique atomistic insights into the folding landscape of parallel-stranded G4 but also reveal limitations of current state-of-the-art MD techniques.

Simple Adjustment of Intranucleotide Base-Phosphate Interaction in the OL3 AMBER Force Field Improves RNA Simulations

Molecular dynamics (MD) simulations represent an established tool to study RNA molecules. The outcome of MD studies depends, however, on the quality of the force field (ff). Here we suggest a correction for the widely used AMBER OL3 ff by adding a simple adjustment of the nonbonded parameters. The reparameterization of the Lennard-Jones potential for the -H8···O5'- and -H6···O5'- atom pairs addresses an intranucleotide steric clash occurring in the type 0 base-phosphate interaction (0BPh). The nonbonded fix (NBfix) modification of 0BPh interactions (NBfix0BPh modification) was tuned via a reweighting approach and subsequently tested using an extensive set of standard and enhanced sampling simulations of both unstructured and folded RNA motifs. The modification corrects minor but visible intranucleotide clash for the anti nucleobase conformation. We observed that structural ensembles of small RNA benchmark motifs simulated with the NBfix0BPh modification provide better agreement with experiments. No side effects of the modification were observed in standard simulations of larger structured RNA motifs. We suggest that the combination of OL3 RNA ff and NBfix0BPh modification is a viable option to improve RNA MD simulations.

Accelerating Solvent Dynamics with Replica Exchange for Improved Free Energy Sampling

Molecular reactions in solution typically involve solvent exchange; for example, a surface must partly desolvate for a molecule to adsorb onto it. When these reactions are simulated, slow solvent dynamics can limit the sampling of configurations and reduce the accuracy of free energy estimates. Here, we combine Hamiltonian replica exchange (HREX) with well-tempered metadynamics (WTMD) to accelerate the sampling of solvent configurations orthogonal to the collective variable space. We compute the formation free energy of a carbonate vacancy in the calcite-water interface and find that the combination of WTMD with HREX significantly improves the sampling relative to WTMD without HREX.

An interoperable implementation of collective-variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. In this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

Reaction Coordinates for Conformational Transitions Using Linear Discriminant Analysis on Positions

In this work, we demonstrate that Linear Discriminant Analysis (LDA) applied to atomic positions in two different states of a biomolecule produces a good reaction coordinate between those two states. Atomic coordinates of a macromolecule are a direct representation of a macromolecular configuration, and yet, they are not used in enhanced sampling studies due to a lack of rotational and translational invariance. We resolve this issue using the technique of our prior work, whereby a molecular configuration is considered a member of an equivalence class in size-and-shape space, which is the set of all configurations that can be translated and rotated to a single point within a reference multivariate Gaussian distribution characterizing a single molecular state. The reaction coordinates produced by LDA applied to positions are shown to be good reaction coordinates both in terms of characterizing the transition between two states of a system within a long molecular dynamics (MD) simulation and also ones that allow us to readily produce free energy estimates along that reaction coordinate using enhanced sampling MD techniques.

Ingenuity in performing replica permutation: How to order the state labels for improving sampling efficiency

In the replica-permutation method, an advanced version of the replica-exchange method, all combinations of replicas and parameters are considered for parameter permutation, and a list of all the combinations is prepared. Here, we report that the temperature transition probability depends on how the list is created, especially in replica permutation with solute tempering (RPST). We found that the transition probabilities decrease at large replica indices when the combinations are sequentially assigned to the state labels as in the originally proposed list. To solve this problem, we propose to modify the list by randomly assigning the combinations to the state labels. We performed molecular dynamics simulations of amyloid-β(16-22) peptides using RPST with the "randomly assigned" list (RPST-RA) and RPST with the "sequentially assigned" list (RPST-SA). The results show the decreases in the transition probabilities in RPST-SA are eliminated, and the sampling efficiency is improved in RPST-RA.

Automatic Learning of Hydrogen-Bond Fixes in the AMBER RNA Force Field

The capability of current force fields to reproduce RNA structural dynamics is limited. Several methods have been developed to take advantage of experimental data in order to enforce agreement with experiments. Here, we extend an existing framework which allows arbitrarily chosen force-field correction terms to be fitted by quantification of the discrepancy between observables back-calculated from simulation and corresponding experiments. We apply a robust regularization protocol to avoid overfitting and additionally introduce and compare a number of different regularization strategies, namely, L1, L2, Kish size, relative Kish size, and relative entropy penalties. The training set includes a GACC tetramer as well as more challenging systems, namely, gcGAGAgc and gcUUCGgc RNA tetraloops. Specific intramolecular hydrogen bonds in the AMBER RNA force field are corrected with automatically determined parameters that we call gHBfix_opt. A validation involving a separate simulation of a system present in the training set (gcUUCGgc) and new systems not seen during training (CAAU and UUUU tetramers) displays improvements regarding the native population of the tetraloop as well as good agreement with NMR experiments for tetramers when using the new parameters. Then, we simulate folded RNAs (a kink–turn and L1 stalk rRNA) including hydrogen bond types not sufficiently present in the training set. This allows a final modification of the parameter set which is named gHBfix21 and is suggested to be applicable to a wider range of RNA systems.

Toward Convergence in Folding Simulations of RNA Tetraloops: Comparison of Enhanced Sampling Techniques and Effects of Force Field Modifications

Atomistic molecular dynamics simulations represent an established technique for investigation of RNA structural dynamics. Despite continuous development, contemporary RNA simulations still suffer from suboptimal accuracy of empirical potentials (force fields, ffs) and sampling limitations. Development of efficient enhanced sampling techniques is important for two reasons. First, they allow us to overcome the sampling limitations, and second, they can be used to quantify ff imbalances provided they reach a sufficient convergence. Here, we study two RNA tetraloops (TLs), namely the GAGA and UUCG motifs. We perform extensive folding simulations and calculate folding free energies (ΔG_fold^°) with the aim to compare different enhanced sampling techniques and to test several modifications of the nonbonded terms extending the AMBER OL3 RNA ff. We demonstrate that replica-exchange solute tempering (REST2) simulations with 12-16 replicas do not show any sign of convergence even when extended to a timescale of 120 μs per replica. However, the combination of REST2 with well-tempered metadynamics (ST-MetaD) achieves good convergence on a timescale of 5-10 μs per replica, improving the sampling efficiency by at least 2 orders of magnitude. Effects of ff modifications on ΔG_fold^° energies were initially explored by the reweighting approach and then validated by new simulations. We tested several manually prepared variants of the gHBfix potential which improve stability of the native state of both TLs by ∼2 kcal/mol. This is sufficient to conveniently stabilize the folded GAGA TL while the UUCG TL still remains under-stabilized. Appropriate adjustment of van der Waals parameters for C-H···O5' base-phosphate interaction may further stabilize the native states of both TLs by ∼0.6 kcal/mol.

Replica permutation with solute tempering for molecular dynamics simulation and its application to the dimerization of amyloid-β fragments

We propose the replica permutation with solute tempering (RPST) by combining the replica-permutation method (RPM) and the replica exchange with solute tempering (REST). Temperature permutations are performed among more than two replicas in RPM, whereas temperature exchanges are performed between two replicas in the replica-exchange method (REM). The temperature transition in RPM occurs more efficiently than in REM. In REST, only the temperatures of the solute region, the solute temperatures, are exchanged to reduce the number of replicas compared to REM. Therefore, RPST is expected to be an improved method taking advantage of these methods. For comparison, we applied RPST, REST, RPM, and REM to two amyloid-β(16–22) peptides in explicit water. We calculated the transition ratio and the number of tunneling events in the temperature space and the number of dimerization events of amyloid-β(16–22) peptides. The results indicate that, in RPST, the number of replicas necessary for frequent random walks in the temperature and conformational spaces is reduced compared to the other three methods. In addition, we focused on the dimerization process of amyloid-β(16–22) peptides. The RPST simulation with a relatively small number of replicas shows that the two amyloid-β(16–22) peptides form the intermolecular antiparallel β-bridges due to the hydrophilic side-chain contact between Lys and Glu and hydrophobic side-chain contact between Leu, Val, and Phe, which stabilizes the dimer of the peptides.

Reweighting of molecular simulations with explicit-solvent SAXS restraints elucidates ion-dependent RNA ensembles

Small-angle X-ray scattering (SAXS) experiments are increasingly used to probe RNA structure. A number of forward models that relate measured SAXS intensities and structural features, and that are suitable to model either explicit-solvent effects or solute dynamics, have been proposed in the past years. Here, we introduce an approach that integrates atomistic molecular dynamics simulations and SAXS experiments to reconstruct RNA structural ensembles while simultaneously accounting for both RNA conformational dynamics and explicit-solvent effects. Our protocol exploits SAXS pure-solute forward models and enhanced sampling methods to sample an heterogenous ensemble of structures, with no information towards the experiments provided on-the-fly. The generated structural ensemble is then reweighted through the maximum entropy principle so as to match reference SAXS experimental data at multiple ionic conditions. Importantly, accurate explicit-solvent forward models are used at this reweighting stage. We apply this framework to the GTPase-associated center, a relevant RNA molecule involved in protein translation, in order to elucidate its ion-dependent conformational ensembles. We show that (a) both solvent and dynamics are crucial to reproduce experimental SAXS data and (b) the resulting dynamical ensembles contain an ion-dependent fraction of extended structures.

Computational methods for exploring protein conformations

Proteins are dynamic molecules that can transition between a potentially wide range of structures comprising their conformational ensemble. The nature of these conformations and their relative probabilities are described by a high-dimensional free energy landscape. While computer simulation techniques such as molecular dynamics simulations allow characterisation of the metastable conformational states and the transitions between them, and thus free energy landscapes, to be characterised, the barriers between states can be high, precluding efficient sampling without substantial computational resources. Over the past decades, a dizzying array of methods have emerged for enhancing conformational sampling, and for projecting the free energy landscape onto a reduced set of dimensions that allow conformational states to be distinguished, known as collective variables (CVs), along which sampling may be directed. Here, a brief description of what biomolecular simulation entails is followed by a more detailed exposition of the nature of CVs and methods for determining these, and, lastly, an overview of the myriad different approaches for enhancing conformational sampling, most of which rely upon CVs, including new advances in both CV determination and conformational sampling due to machine learning.

Exploring Large Domain Motions in Proteins Using Atomistic Molecular Dynamics with Enhanced Conformational Sampling

Conformational transitions in multidomain proteins are essential for biological functions. The Apo conformations are typically open and flexible, while the Holo states form more compact conformations stabilized by protein-ligand interactions. Unfortunately, the atomically detailed mechanisms for such open-closed conformational changes are difficult to be accessed experimentally as well as computationally. To simulate the transitions using atomistic molecular dynamics (MD) simulations, efficient conformational sampling algorithms are required. In this work, we propose a new approach based on generalized replica-exchange with solute tempering (gREST) for exploring the open-closed conformational changes in multidomain proteins. Wherein, selected surface charged residues in a target protein are defined as the solute region in gREST simulation and the solute temperatures are different in replicas and exchanged between them to enhance the domain motions. This approach is called gREST selected surface charged residues (gREST_SSCR) and is applied to the Apo and Holo states of ribose binding protein (RBP) in solution. The conformational spaces sampled with gREST_SSCR are much wider than those with the conventional MD, sampling open-closed conformational changes while maintaining RBP domains’ stability. The free-energy landscapes of RBP in the Apo and Holo states are drawn along with twist and hinge angles of the two moving domains. The inter-domain salt-bridges that are not observed in the experimental structures are also important in the intermediate states during the conformational changes.

Role of the N-Terminal Transmembrane Helix Contacts in the Activation of FGFR3

Fibroblast growth factor receptor 3 (FGFR3) is a member of receptor tyrosine kinases, which is involved in skeletal cell growth, differentiation, and migration. FGFR3 transduces biochemical signals from the extracellular ligand-binding domain to the intracellular kinase domain through the conformational changes of the transmembrane (TM) helix dimer. Here, we apply generalized replica exchange with solute tempering method to wild type (WT) and G380R mutant (G380R) of FGFR3. The dimer interface in G380R is different from WT and the simulation results are in good agreement with the solid-state nuclear magnetic resonance (NMR) spectroscopy. TM helices in G380R are extended more than WT, and thereby, G375 in G380R contacts near the N-termini of the TM helix dimer. Considering that both G380R and G375C show the constitutive activation, the formation of the N-terminal contacts of the TM helices can be generally important for the activation mechanism. © 2019 Wiley Periodicals, Inc.

Replica-Exchange Methods for Biomolecular Simulations

In this study, a replica-exchange method was developed to overcome conformational sampling difficulties in computer simulations of spin glass or other systems with rugged free-energy landscapes. This method was then applied to the protein-folding problem in combination with molecular dynamics (MD) simulation. Owing to its simplicity and sampling efficiency, the replica-exchange method has been applied to many other biological problems and has been continuously improved. The method has often been combined with other sampling techniques, such as umbrella sampling, free-energy perturbation, metadynamics, and Gaussian accelerated MD (GaMD). In this chapter, we first summarize the original replica-exchange molecular dynamics (REMD) method and discuss how new algorithms related to the original method are implemented to add new features. Heterogeneous and flexible structures of an N-glycan in a solution are simulated as an example of applications by REMD, replica exchange with solute tempering, and GaMD. The sampling efficiency of these methods on the N-glycan system and the convergence of the free-energy changes are compared. REMD simulation protocols and trajectory analysis using the GENESIS software are provided to facilitate the practical use of advanced simulation methods.

Computational insights into lipid assisted peptide misfolding and aggregation in neurodegeneration

An overview of recent advances in computational investigation of peptide–lipid interactions in neurodegeneration – Alzheimer's, Parkinson's and Huntington's disease.

Refining protein structures using enhanced sampling techniques with restraints derived from an ensemble-based model

This paper reports a method for high-accuracy protein structural refinement, which is a direct extension of the method in our recent publication (Zang, J Chem Phys 2018; 149:072319). It combines a parallel continuous simulated tempering (PCST) method with a temperature-dependent restraint and a blind model selection scheme. In this work, a single-reference-based restraint in previous work was changed to an ensemble-based model (EBM), in which the non-bonded Lennard-Jones term for each contacting atomic pair in previous restraining potential was replaced by a multi-Gaussian function whose parameters are derived from an ensemble of structures such as the ones from various CASP participating groups. The purpose of EBM is to take advantage of partial "correctness" distributed among members of the structural ensemble. Totally 18 targets were refined from the refinement category of CASP10, CASP11 and CASP12. In Top-1 group, 11 out of 18 targets had better models (greater GDT_TS scores) than the CASPR participants. In Top-5 group, nine out of 18 were better. Our results show that PCST-EBM method can considerably improve the low-accuracy structures.

Flexible selection of the solute region in replica exchange with solute tempering: Application to protein-folding simulations

Replica-exchange molecular dynamics (REMD) and their variants have been widely used in simulations of the biomolecular structure and dynamics. Replica exchange with solute tempering (REST) is one of the methods where temperature of a pre-defined solute molecule is exchanged between replicas, while solvent temperatures in all the replicas are kept constant. REST greatly reduces the number of replicas compared to the temperature REMD, while replicas at low temperatures are often trapped under their conditions, interfering with the conformational sampling. Here, we introduce a new scheme of REST, referred to as generalized REST (gREST), where the solute region is defined as a part of a molecule or a part of the potential energy terms, such as the dihedral-angle energy term or Lennard-Jones energy term. We applied this new method to folding simulations of a β-hairpin (16 residues) and a Trp-cage (20 residues) in explicit water. The protein dihedral-angle energy term is chosen as the solute region in the simulations. gREST reduces the number of replicas necessary for good random walks in the solute-temperature space and covers a wider conformational space compared to the conventional REST2. Considering the general applicability, gREST should become a promising tool for the simulations of protein folding, conformational dynamics, and an in silico drug design.

Improving low-accuracy protein structures using enhanced sampling techniques

In this paper, we report results of using enhanced sampling and blind selection techniques for high-accuracy protein structural refinement. By combining a parallel continuous simulated tempering (PCST) method, previously developed by Zang et al. [J. Chem. Phys. 141, 044113 (2014)], and the structure based model (SBM) as restraints, we refined 23 targets (18 from the refinement category of the CASP10 and 5 from that of CASP12). We also designed a novel model selection method to blindly select high-quality models from very long simulation trajectories. The combined use of PCST-SBM with the blind selection method yielded final models that are better than initial models. For Top-1 group, 7 out of 23 targets had better models (greater global distance test total scores) than the critical assessment of structure prediction participants. For Top-5 group, 10 out of 23 were better. Our results justify the crucial position of enhanced sampling in protein structure prediction and refinement and demonstrate that a considerable improvement of low-accuracy structures is achievable with current force fields.

Communication: Self-assembly of a model supramolecular polymer studied by replica exchange with solute tempering

Conventional molecular-dynamics (cMD) simulation has a well-known limitation in accessible time and length scales, and thus various enhanced sampling techniques have been proposed to alleviate the problem. In this paper, we explore the utility of replica exchange with solute tempering (REST) (i.e., a variant of Hamiltonian replica exchange methods) to simulate the self-assembly of a supramolecular polymer in explicit solvent and compare the performance with temperature-based replica exchange MD (T-REMD) as well as cMD. As a test system, we consider a relatively simple all-atom model of supramolecular polymerization (namely, benzene-1,3,5-tricarboxamides in methylcyclohexane solvent). Our results show that both REST and T-REMD are able to predict highly ordered polymer structures with helical H-bonding patterns, in contrast to cMD which completely fails to obtain such a structure for the present model. At the same time, we have also experienced some technical challenge (i.e., aggregation-dispersion transition and the resulting bottleneck for replica traversal), which is illustrated numerically. Since the computational cost of REST scales more moderately than T-REMD, we expect that REST will be useful for studying the self-assembly of larger systems in solution with enhanced rearrangement of monomers.

Equilibrium Ensembles for Insulin Folding from Bias-Exchange Metadynamics

Earliest events in the aggregation process, such as single molecule reconfiguration, are extremely important and the most difficult to characterize in experiments. To this end, we have used well-tempered bias exchange metadynamics simulations to determine the equilibrium ensembles of an insulin molecule under amyloidogenic conditions of low pH and high temperature. A bin-based clustering method that uses statistics accumulated in bias exchange metadynamics trajectories was employed to construct a detailed thermodynamic and kinetic model of insulin folding. The highest lifetime, lowest free-energy ensemble identified consisted of native conformations adopted by a folded insulin monomer in solution, namely, the R-, the R^f-, and the T-states of insulin. The lowest free-energy structure had a root mean square deviation of only 0.15 nm from native x-ray structure. The second longest-lived metastable state was an unfolded, compact monomer with little similarity to the native structure. We have identified three additional long-lived, metastable states from the bin-based model. We then carried out an exhaustive structural characterization of metastable states on the basis of tertiary contact maps and per-residue accessible surface areas. We have also determined the lowest free-energy path between two longest-lived metastable states and confirm earlier findings of non-two-state folding for insulin through a folding intermediate. The ensemble containing the monomeric intermediate retained 58% of native hydrophobic contacts, however, accompanied by a complete loss of native secondary structure. We have discussed the relative importance of nativelike versus nonnative tertiary contacts for the folding transition. We also provide a simple measure to determine the importance of an individual residue for folding transition. Finally, we have compared and contrasted this intermediate with experimental data obtained in spectroscopic, crystallographic, and calorimetric measurements during early stages of insulin aggregation. We have also determined stability of monomeric insulin by incubation at a very low concentration to isolate protein-protein interaction effects.

Thermodynamic and structural effect of urea and guanidine chloride on the helical and on a hairpin fragment of GB1 from molecular simulations

With the help of molecular-dynamics simulations, we studied the effect of urea and guanidine chloride on the thermodynamic and structural properties of the helical fragment of protein GB1, comparing them with those of its second beta hairpin. We showed that the helical fragment in different solvents populates an ensemble of states that is more complex than that of the hairpin, and thus the associated experimental observables (circular-dichroism spectra, secondary chemical shifts, m values), that we back-calculated from the simulations and compared with the actual data, are more difficult to interpret. We observed that in the case of both peptides, urea binds tightly to their backbone, while guanidine exerts its denaturing effect in a more subtle way, strongly affecting the electrostatic properties of the solution. This difference can have consequences in the way denaturation experiments are interpreted. Proteins 2017; 85:753-763. © 2016 Wiley Periodicals, Inc.

Inclusion of lipopeptides into the DMPC lipid bilayers prevents Aβ peptide insertion

Lipopeptides prevent penetration of Alzheimer's Aβ peptides into lipid bilayers.

Free-Energy Landscape of the Amino-Terminal Fragment of Huntingtin in Aqueous Solution

The first exon of Huntingtin-a protein with multiple biological functions whose misfolding is related to Huntington's disease-modulates its localization, aggregation, and function within the cell. It is composed of a 17-amino-acid amphipathic segment (Htt17), an amyloidogenic segment of consecutive glutamines (QN), and a proline-rich segment. Htt17 is of fundamental importance: it serves as a membrane anchor to control the localization of huntingtin, it modulates huntingtin's function through posttranslational modifications, and it controls the self-assembly of the amyloidogenic QN segment into oligomers and fibrils. Experimentally, the conformational ensemble of the Htt17 monomer, as well as the impact of the polyglutamine and proline-rich segments, remains, however, mostly uncharacterized at the atomic level due to its intrinsic flexibility. Here, we unveil the free-energy landscape of Htt17, Htt17Q17, and Htt17Q17P11 using Hamiltonian replica exchange combined with well-tempered metadynamics. We characterize the free-energy landscape of these three fragments in terms of a few selected collective variables. Extensive simulations reveal that the free energy of Htt17 is dominated by a broad ensemble of configurations that agree with solution NMR chemical shifts. Addition of Q17 at its carboxy-terminus reduces the extent of the main basin to more extended configurations of Htt17 with lower helix propensity. Also, the aliphatic carbons of Q17 partially sequester the nonpolar amino acids of Htt17. For its part, addition of Q17P11 shifts the overall landscape to a more extended and helical Htt17 stabilized by interactions with Q17 and P11, which almost exclusively form a PPII-helix, as well as by intramolecular H-bonds and salt bridges. Our characterization of Huntingtin's amino-terminus provides insights into the structural origin of its ability to oligomerize and interact with phospholipid bilayers, processes closely linked to the biological functions of this protein.

Efficient sampling over rough energy landscapes with high barriers: A combination of metadynamics with integrated tempering sampling

In order to efficiently overcome high free energy barriers embedded in a complex energy landscape and calculate overall thermodynamics properties using molecular dynamics simulations, we developed and implemented a sampling strategy by combining the metadynamics with (selective) integrated tempering sampling (ITS/SITS) method. The dominant local minima on the potential energy surface (PES) are partially exalted by accumulating history-dependent potentials as in metadynamics, and the sampling over the entire PES is further enhanced by ITS/SITS. With this hybrid method, the simulated system can be rapidly driven across the dominant barrier along selected collective coordinates. Then, ITS/SITS ensures a fast convergence of the sampling over the entire PES and an efficient calculation of the overall thermodynamic properties of the simulation system. To test the accuracy and efficiency of this method, we first benchmarked this method in the calculation of ϕ - ψ distribution of alanine dipeptide in explicit solvent. We further applied it to examine the design of template molecules for aromatic meta-C-H activation in solutions and investigate solution conformations of the nonapeptide Bradykinin involving slow cis-trans isomerizations of three proline residues.

Free energy surface of an intrinsically disordered protein: comparison between temperature replica exchange molecular dynamics and bias-exchange metadynamics

Intrinsically disordered proteins (IDPs), which are expected to be largely unstructured under physiological conditions, make up a large fraction of eukaryotic proteins. Molecular dynamics simulations have been utilized to probe structural characteristics of these proteins, which are not always easily accessible to experiments. However, exploration of the conformational space by brute force molecular dynamics simulations is often limited by short time scales. Present literature provides a number of enhanced sampling methods to explore protein conformational space in molecular simulations more efficiently. In this work, we present a comparison of two enhanced sampling methods: temperature replica exchange molecular dynamics and bias exchange metadynamics. By investigating both the free energy landscape as a function of pertinent order parameters and the per-residue secondary structures of an IDP, namely, human islet amyloid polypeptide, we found that the two methods yield similar results as expected. We also highlight the practical difference between the two methods by describing the path that we followed to obtain both sets of data.

Estimation of the free energy of adsorption of a polypeptide on amorphous SiO2 from molecular dynamics simulations and force spectroscopy experiments

Estimating the free energy of adsorption of materials-binding peptides is fundamental to quantify their interactions across bio/inorganic interfaces, but is difficult to achieve both experimentally and theoretically. We employ a combination of molecular dynamics (MD) simulations and dynamical force-spectroscopy experiments based on atomic force microscopy (AFM) to estimate the free energy of adsorption ΔGads of a (GCRL) tetrapeptide on amorphous SiO2 in pure water. The results of both equilibrium, advanced sampling MD and non-equilibrium, steered MD are compared with those of two different approaches used to extract ΔGads from the dependence of experimentally measured adhesion forces on the applied AFM loading rates. In order to obtain unambiguous peak forces and bond loading rates from steered MD trajectories, we have developed a novel numerical protocol based on a piecewise-harmonic fit of the adhesion work profile along each trajectory. The interpretation of the experiments has required a thorough quantitative characterization of the elastic properties of polyethylene glycol linker molecules used to tether (GCRL)15 polypeptides to AFM cantilevers, and of the polypeptide itself. All obtained ΔGads values fall within a relatively narrow window between -5 and -9 kcal mol(-1), but can be associated with large relative error bars of more than 50%. Among the different approaches compared, Replica Exchange with Solute Tempering simulations augmented with MetaDynamics (RESTMetaD) and fitting of dynamic force spectroscopy experiments with the model of Friddle and De Yoreo lead to the most reliable ΔGads estimates.

Enhanced Conformational Sampling Using Replica Exchange with Collective-Variable Tempering

The computational study of conformational transitions in RNA and proteins with atomistic molecular dynamics often requires suitable enhanced sampling techniques. We here introduce a novel method where concurrent metadynamics are integrated in a Hamiltonian replica-exchange scheme. The ladder of replicas is built with different strengths of the bias potential exploiting the tunability of well-tempered metadynamics. Using this method, free-energy barriers of individual collective variables are significantly reduced compared with simple force-field scaling. The introduced methodology is flexible and allows adaptive bias potentials to be self-consistently constructed for a large number of simple collective variables, such as distances and dihedral angles. The method is tested on alanine dipeptide and applied to the difficult problem of conformational sampling in a tetranucleotide.

Computational prediction of circular dichroism spectra and quantification of helicity loss upon peptide adsorption on silica

Circular dichroism (CD) spectroscopy is one of the few experimental techniques sensitive to the structural changes that peptides undergo when they adsorb on inorganic material surfaces, a problem of deep significance in medicine, biotechnology, and materials science. Although the theoretical calculation of the CD spectrum of a molecule in a given conformation can be routinely performed, the inverse problem of extracting atomistic structural details from a measured spectrum is not uniquely determined. Especially complicated is the case of oligopeptides, whose folding/unfolding energy landscapes are often very broad and shallow. This means that the CD spectra measured for either dissolved or adsorbed peptides arise from a multitude of different structures, each present with a probability dictated by their relative free-energy variations, according to Boltzmann statistics. Here we present a modeling method based on replica exchange with solute tempering in combination with metadynamics, which allows us to predict both the helicity loss of a small peptide upon interaction with silica colloids in water and to compute the full CD spectra of the adsorbed and dissolved states, in quantitative agreement with experimental measurements. In our method, the CD ellipticity Θ for any given wavelength λ is calculated as an external collective variable by means of reweighting the biased trajectory obtained using the peptide-SiO2 surface distance and the structural helicity as two independent, internal collective variables. Our results also provide support for the often-employed hypothesis that the Θ intensity at λ = 222 nm is linearly correlated with the peptides' fractional helicity.

Characterization of the free-energy landscapes of proteins by NMR-guided metadynamics

The use of free-energy landscapes rationalizes a wide range of aspects of protein behavior by providing a clear illustration of the different states accessible to these molecules, as well as of their populations and pathways of interconversion. The determination of the free-energy landscapes of proteins by computational methods is, however, very challenging as it requires an extensive sampling of their conformational spaces. We describe here a technique to achieve this goal with relatively limited computational resources by incorporating nuclear magnetic resonance (NMR) chemical shifts as collective variables in metadynamics simulations. As in this approach the chemical shifts are not used as structural restraints, the resulting free-energy landscapes correspond to the force fields used in the simulations. We illustrate this approach in the case of the third Ig-binding domain of protein G from streptococcal bacteria (GB3). Our calculations reveal the existence of a folding intermediate of GB3 with nonnative structural elements. Furthermore, the availability of the free-energy landscape enables the folding mechanism of GB3 to be elucidated by analyzing the conformational ensembles corresponding to the native, intermediate, and unfolded states, as well as the transition states between them. Taken together, these results show that, by incorporating experimental data as collective variables in metadynamics simulations, it is possible to enhance the sampling efficiency by two or more orders of magnitude with respect to standard molecular dynamics simulations, and thus to estimate free-energy differences among the different states of a protein with a k(B)T accuracy by generating trajectories of just a few microseconds.

Drug-DNA intercalation: from discovery to the molecular mechanism

The ability of small molecules to perturb the natural structure and dynamics of nucleic acids is intriguing and has potential applications in cancer therapeutics. Intercalation is a special binding mode where the planar aromatic moiety of a small molecule is inserted between a pair of base pairs, causing structural changes in the DNA and leading to its functional arrest. Enormous progress has been made to understand the nature of the intercalation process since its idealistic conception five decades ago. However, the biological functions were detected even earlier. In this review, we focus mainly on the acridine and anthracycline types of drugs and provide a brief overview of the development in the field through various experimental methods that led to our present understanding of the subject. Subsequently, we discuss the molecular mechanism of the intercalation process, free-energy landscapes, and kinetics that was revealed recently through detailed and rigorous computational studies.

(Ala)(4)-X-(Ala)4 as a model system for the optimization of the χ1 and χ2 amino acid side-chain dihedral empirical force field parameters

Amino acid side-chain fluctuations play an essential role in the structure and function of proteins. Accordingly, in theoretical studies of proteins, it is important to have an accurate description of their conformational properties. Recently, new side-chain torsion parameters were introduced into the CHARMM and Amber additive force fields and evaluated based on the conformational properties of the individual side-chains using protein simulations in explicit solvent. While effective for validation, molecular dynamics simulations of proteins must be extended into the microsecond regime to obtain full convergence of the side-chain conformations, limiting their use for force field optimization. To address this, we systematically test the utility of explicit solvent simulations of (Ala)(4)-X-(Ala)(4) peptides, where X represents the amino acids, as model systems for the optimization of χ(1) and χ(2) side-chain parameters. The effect of (Ala)(4)-X-(Ala)(4) backbone conformation was tested by constraining the backbone in the α-helical, C5, C7(eq), and PPII conformations and performing exhaustive sampling using Hamiltonian replica exchange simulations. Rotamer distributions from protein and the (Ala)(4)-X-(Ala)(4) simulations showed the highest correlation for the C7(eq) and PPII conformations, although agreement was the best for the α-helical conformation for Asn. Hydrogen bond analysis indicates the utility of the C7(eq) and PPII conformations to be due to specific side-chain-backbone hydrogen bonds not being oversampled, thereby allowing sampling of a range of side-chain conformations consistent with the distributions occurring in full proteins. It is anticipated that the (Ala)(4)-X-(Ala)(4) model system will allow for iterative force field optimization targeting condensed-phase conformational distributions of side-chains.

Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles

While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large number of applications, limitations in the model with respect to the equilibrium between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non Gly, Pro) backbone CMAP potential has been refined against experimental solution NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mechanical energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mechanical energy surfaces, followed by additional empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against data not used to guide parametrization: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equilibrium folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for the modeling and simulation studies of proteins, including studies of protein folding, assembly and functionally relevant conformational changes.

Energy landscape of the prion protein helix 1 probed by metadynamics and NMR

The characterization of the structural dynamics of proteins, including those that present a substantial degree of disorder, is currently a major scientific challenge. These dynamics are biologically relevant and govern the majority of functional and pathological processes. We exploited a combination of enhanced molecular simulations of metadynamics and NMR measurements to study heterogeneous states of proteins and peptides. In this way, we determined the structural ensemble and free-energy landscape of the highly dynamic helix 1 of the prion protein (PrP-H1), whose misfolding and aggregation are intimately connected to a group of neurodegenerative disorders known as transmissible spongiform encephalopathies. Our combined approach allowed us to dissect the factors that govern the conformational states of PrP-H1 in solution, and the implications of these factors for prion protein misfolding and aggregation. The results underline the importance of adopting novel integrated approaches that take advantage of experiments and theory to achieve a comprehensive characterization of the structure and dynamics of biological macromolecules.

All-atom models of the membrane-spanning domain of HIV-1 gp41 from metadynamics

The 27-residue membrane-spanning domain (MSD) of the HIV-1 glycoprotein gp41 bears conserved sequence elements crucial to the biological function of the virus, in particular a conserved GXXXG motif and a midspan arginine. However, structure-based explanations for the roles of these and other MSD features remain unclear. Using molecular dynamics and metadynamics calculations of an all-atom, explicit solvent, and membrane-anchored model, we study the conformational variability of the HIV-1 gp41 MSD. We find that the MSD peptide assumes a stable tilted α-helical conformation in the membrane. However, when the side chain of the midspan Arg (694) "snorkels" to the outer leaflet of the viral membrane, the MSD assumes a metastable conformation where the highly-conserved N-terminal core (between Lys(681) and Arg(694) and containing the GXXXG motif) unfolds. In contrast, when the Arg(694) side chain snorkels to the inner leaflet, the MSD peptide assumes a metastable conformation consistent with experimental observations where the peptide kinks at Phe(697) to facilitate Arg(694) snorkeling. Both of these models suggest specific ways that gp41 may destabilize viral membrane, priming the virus for fusion with a target cell.