Combination Of Force Field Research Articles

Evaluation of implicit solvent models in molecular dynamics simulation of α-Synuclein

We report conventional and accelerated molecular dynamics simulations of α-Synuclein, designed to assess performance of using different starting conformation, solvation environment and force field combination. Backbone and sidechain chemical shifts, radius of gyration, presence of β-hairpin structures in KTK(E/Q)GV repeats and secondary structure percentages were used to evaluate how variations in forcefield, solvation model and simulation protocol provide results that correlate with experimental findings. We show that with suitable choice of forcefield and solvent, ff03ws and OBC implicit model, respectively, acceptable reproduction of experimental data on size and secondary structure is obtained by both conventional and accelerated MD. In contrast to the implicit solvent model, simulations in explicit TIP4P/2005 solvent do not properly represent size or secondary structure of α-Synuclein. Communicated by Ramaswamy H. Sarma

Conformer-Specific Spectroscopy and IR-Induced Isomerization of a Model γ-Peptide: Ac-γ4-Phe-NHMe.

Single-conformation IR and UV spectroscopy of the prototypical capped γ-peptide Ac-γ4-Phe-NHMe (γ4F) was carried out under jet-cooled conditions in the gas phase in order to understand its innate conformational preferences in the absence of a solvent. We obtained conformer-specific IR and UV spectra and compared the results with calculations to make assignments and explore the differences between the γ2- and γ4-substituted molecules. We found four conformers of γ4F in our experiment. Three conformers form nine-membered hydrogen-bonded rings (C9) enclosed by an NH···O═C H-bond but differing in their phenyl ring positions (a, g+, and g-). The fourth conformer forms a strained seven-membered hydrogen-bonded ring in which the amide groups lie in a nominally anti-parallel arrangement stacked on top of one another (labeled S7). This conformer is a close analogue of the amide-stacked conformer (S) found previously in γ2F, in which the Phe side chain is substituted at the γ2 position, Ac-γ2-Phe-NHMe (J. Am. Chem. Soc. 2009, 131, 14243-14245). IR population transfer spectroscopy was used to determine the fractional abundances of the γ4F conformers in the expansion. A combination of force field and density functional theory calculations is used to map out the conformational potential energy surfaces for γ4F and compare it with its γ2F counterpart. Based on this analysis, the phenyl ring prefers to take up structures that facilitate NH···π interactions in γ4F or avoid phenyl interactions with the C═O group in γ2F. The disconnectivity graph for γ4F reveals separate basins associated with the C9 and amide-stacked conformational families, which are separated by a barrier of about 42 kJ/mol. The overall shape of the potential energy surface bears a resemblance to peptides and proteins that have a misfolding pathway that competes with the formation of the native structure.

Modeling the Structure and Interactions of Intrinsically Disordered Peptides with Multiple Replica, Metadynamics-Based Sampling Methods and Force-Field Combinations.

Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure–function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and force fields. Nevertheless, differences in fine details emerge from varying combinations of force-fields and sampling methods. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which are common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field and sampling method combinations for accurate structural and thermodynamic information in the study of disordered proteins.

Comparison of different force field combinations for ligand binding free energy calculations with amber

AMBER has supported alchemical free energy simulation and has been used for drug design research for decades since the 1980s. However, the system preparation of alchemical free energy simulation is a time-consuming and error-prone process for a large number of ligands. To address this issue, we have recently presented CHARMM-GUI Free Energy Calculator that can provide input and postprocessing scripts for AMBER-TI free energy calculations. In particular, CHARMM-GUI supports various AMBER force fields (FFs) and researchers can choose any FF combinations based on their preference and research need.

Recent Advances in First-Principles Based Molecular Dynamics.

First-principles molecular dynamics (FPMD) and its quantum mechanical-molecular mechanical (QM/MM) extensions are powerful tools to follow the real-time dynamics of a broad variety of systems in their ground as well as electronically excited states. The continued advances in computational power have enabled simulations of QM regions of larger sizes for more extended time scales. In addition, development of the parallel algorithms has boosted the performance of QM/MM methods even on existing computer architectures. In the case of density functional-based FPMD, systems of several hundreds to thousands of atoms can now be customarily simulated for tens to hundreds of picoseconds. In spite of this progress, the time scale limitations remain severe, especially when high-rung exchange-correlation functionals or high-level wave function based quantum mechanical methods are used. To ameliorate this, a large number of enhanced sampling methods have been introduced but most of the approaches that have been developed to increase the efficiency of FPMD based simulations sacrifice the real-time dynamics in favor of enhancing sampling. Here, we present some recent advances in boosting the efficiency of FPMD based simulations while keeping the full dynamic information. These include a highly efficient recent implementation of FPMD-based QM/MM simulations that not only enables fully flexible combinations of different electronic structure methods and force fields via a highly efficient communication library, it also fully exploits parallelism for both quantum and classical descriptions. The second type of acceleration methods we discuss is a large family of specially devised multiple-time-step algorithms that make use of suitable breakups of the total nuclear forces into fast components that can be calculated via lower level methods and slowly varying correction forces evaluated with a high-level method at long time intervals. The computational gain of this scheme mostly depends on the cost difference between the two methods and advantageous combinations can yield large speedups without compromising the accuracy of the high-level method. And finally, the third class of FPMD acceleration methods presented here are machine learning models to accelerated FPMD and their powerful combinations with multiple-time-step techniques. The combination of all the approaches enables substantial speedups of FPMD simulations of several orders of magnitude while fully preserving the real-time dynamics and accuracy.

Molecular dynamics insight into the adsorption and distribution of bitumen subfractions on Na-montmorillonite surface

How bitumen works with clay minerals is an essential matter for the application of nano-clay minerals (e. g., montmorillonite, vermiculite) in bitumen modification. In this paper, the combination of ClayFF and consistent-valence force field (CVFF) is developed to characterize the bitumen-clay interaction. The adsorption configuration, distribution pattern of bitumen subfractions on the Na-montmorillonite surface and thermal effect are systematacially investigated by examining the evolution of bitumen model at different temperatures based on the molecular dynamics simulation. For comparision, 12 isolated bitumen monomers and bitumen SARA fractions (saturates, aromatics, resins, asphaltenes) are attached to Na-montmorillonite surface respectively. The results show that asphaltenes have preference for parallel adsorption near bitumen-clay interface, but the tightly adsorbed configuration can be disrupted by their self-aggregation and light fractions. The distribution pattern is highly influenced by the adsorption strength and molecular diffusion, despite non-negligible spatial effect. Herein, the interaction energy of isolated monomers with clay platelet shows the adsorption strength of SARA fractions in the order of asphaltenes > resins > aromatics > saturates, while the diffusion can be ranked as: Saturates > Resins > Aromatics > Asphaltenes. The distribution pattern of bitumen inferred from the synergy of interaction strength and diffusion suggests that the bitumen exhibits stratified property on clay surface, the asphaltenes and resins content is likely to be higher in the range (1.0～1.5 nm) close to the surface. As for the thermal effect, it is observed that the asphaltenes and resins desorb from the clay surface as the temperature rises as aromatics dominates the adsorption zone, also supported by the finding that asphaltenes dimers are formed and the interaction energy of bitumen with clay platelet decreases to 72.98% at elevated temperature, which implies the thermal effect can reverse the distribution by inconsistently increasing the diffusion of bitumen subfractions. Overall, these findings are helpful for understanding bitumen-clay interaction, optimizing processing temperature and screening surfactant to improve compatibility of nano-clay modifiers with bitumen.

Balanced Solvent Model for Intrinsically Disordered and Ordered Proteins.

Intrinsically disordered proteins (IDPs) have no fixed three-dimensional (3D) structures under physiological conditions, with the content being about 51% in human proteomics. IDPs are associated with many human diseases, such as cancer, diabetes, and neurodegenerative diseases. Because IDPs do not crystallize and have diverse conformers, traditional experimental methods such as crystallization and NMR can hardly capture their conformation ensemble and just provide average structural characters of IDPs. Therefore, molecular dynamics (MD) simulations become a valuable complement to the experimental data. However, the accuracy of molecular dynamics simulation for IDPs depends on the combination of force fields and solvent models. Recently, we released an environment-specific force field (ESFF1) for IDPs, which can well reproduce the local structural properties (such as J-coupling and secondary chemical shifts). However, there is still a large deviation for the radius of gyration (Rg). Therefore, a solvent model combined with ESFF1 is necessary to capture the local and global characters for IDPs and ordered proteins. Here, we investigated the underestimation or overestimation of the solvent interaction for four solvent models (TIP3P, TIP4P-Ew, TIP4P-D, OPC) under ESFF1 and found the important ε parameter of the solvent model to play a key role in scaling Rg. A near-linear relationship between the simulation Rg and the ε parameter was used to develop the new solvent model, named TIP4P-B. The results indicate that the simulated Rg with TIP4P-B is in better agreement with the experimental observations than the other four solvent models. Simultaneously, TIP4P-B can also maintain the advantages of the ESFF1 force field for the local structural properties. Additionally, TIP4P-B can successfully sample the conformation of ordered proteins. These findings confirm that TIP4P-B is a balanced solvent model and can improve sampling Rg performance for folded proteins and IDPs.

Nonconverged Constraints Cause Artificial Temperature Gradients in Lipid Bilayer Simulations.

Molecular dynamics (MD) simulations have become an indispensable tool to investigate phase separation in model membrane systems. In particular, simulations based on coarse-grained (CG) models have found widespread use due to their increased computational efficiency, allowing for simulations of multicomponent lipid bilayers undergoing phase separation into liquid-ordered and liquid-disordered domains. Here, we show that a significant temperature difference between molecule types can artificially arise in CG MD membrane simulations with the standard Martini simulation parameters in GROMACS. In particular, the linear constraint solver (LINCS) algorithm does not converge with its default settings, resulting in serious temperature differences between molecules in a time step-dependent manner. We demonstrate that the underlying reason for this behavior is the presence of highly constrained moieties, such as cholesterol. Their presence can critically impact numerous structural and dynamic membrane properties obtained from such simulations. Furthermore, any preference of these molecules toward a certain membrane phase can lead to spatial temperature gradients, which can amplify the degree of phase separation or even induce it in compositions that would otherwise mix well. We systematically investigated the effect of the integration time step and LINCS settings on membrane properties. Our data show that for cholesterol-containing membranes, a time step of 20 fs should be combined with at least lincs_iter = 2 and lincs_order = 12, while using a time step of 30 fs requires at least lincs_iter = 3 and lincs_order = 12 to bring the temperature differences to a level where they do not perturb central membrane properties. Moreover, we show that in cases where stricter LINCS settings are computationally too demanding, coupling the lipids in multiple groups to the temperature bath offers a practical workaround to the problem, although the validity of this approach should be further verified. Finally, we show that similar temperature gradients can also emerge in atomistic simulations using the CHARMM force field in combination with settings that allow for a 5 fs integration step.

Coordination and Thermophysical Properties of Transition Metal Chlorocomplexes in LiCl-KCl Eutectic.

Eutectic LiCl-KCl molten salt is often used in molten salt reactors as the primary coolant due to its high thermal capacity and high solubility of fission products. Thermophysical properties, such as density, heat capacity, and viscosity, are important parameters for engineering applications of molten salts but may be significantly influenced by metal solutes from corrosion of metallic structural materials. The behavior of the LiCl-KCl eutectic composition is well researched, yet the effects on these properties due to chlorocomplex formation from metals dissolved in the salt are less well known. These properties are often difficult to accurately measure from experimental methods due to the issues arising from the dissolved species, such as volatility. Here, we applied a combination of quantum mechanics molecular dynamics (QM-MD) and deep machine learning force field (DP-FF) molecular dynamics simulations to investigate the structural and thermophysical properties of LiCl-KCl eutectic as well as the influence of dissolved transition metal chlorocomplexes NiCl2 and CrCl3 at low concentrations. We find that the dissolution of Ni and Cr in the LiCl-KCl system forms the local tetrahedral (NiCl4)2- and octahedral (CrCl6)3- chlorocomplexes, respectively, which do not have a significant impact on the overall liquid salt structures. In addition, the thermodynamic properties including diffusion constant and specific heat capacity are not significantly affected by these chlorocomplexes. However, the viscosity significantly increases in the temperature range of 673-773 K. This study thus provides essential information for evaluating the effects of dissolved metals on the thermophysical and transport properties of molten salts.

Forcefield evaluation and accelerated molecular dynamics simulation of Zn(II) binding to N-terminus of amyloid-β

We report conventional and accelerated molecular dynamics simulation of Zn(II) bound to the N-terminus of amyloid-β. By comparison against NMR data for the experimentally determined binding mode, we find that certain combinations of forcefield and solvent model perform acceptably in describing the size, shape and secondary structure, and that there is no appreciable difference between implicit and explicit solvent models. We therefore used the combination of ff14SB forcefield and GBSA solvent model to compare the result of different binding modes of Zn(II) to the same peptide, using accelerated MD to enhance sampling and comparing the free peptide simulated in the same way. We show that Zn(II) imparts significant rigidity to the peptide, disrupts the secondary structure and pattern of salt bridges seen in the free peptide, and induces closer contact between residues. Free energy surfaces in 1 or 2 dimensions further highlight the effect of metal coordination on peptide’s spatial extent. We also provide evidence that accelerated MD provides improved sampling over conventional MD by visiting as many or more configurations in much shorter simulation times.

ReaxFF-MPNN machine learning potential: a combination of reactive force field and message passing neural networks.

Reactive force field (ReaxFF) is a powerful computational tool for exploring material properties. In this work, we proposed an enhanced reactive force field model, which uses message passing neural networks (MPNN) to compute the bond order and bond energies. MPNN are a variation of graph neural networks (GNN), which are derived from graph theory. In MPNN or GNN, molecular structures are treated as a graph and atoms and chemical bonds are represented by nodes and edges. The edge states correspond to the bond order in ReaxFF and are updated by message functions according to the message passing algorithms. The results are very encouraging; the investigation of the potential, such as the potential energy surface, reaction energies and equation of state, are greatly improved by this simple improvement. The new potential model, called reactive force field with message passing neural networks (ReaxFF-MPNN), is provided as an interface in an atomic simulation environment (ASE) with which the original ReaxFF and ReaxFF-MPNN potential models can do MD simulations and geometry optimizations within the ASE. Furthermore, machine learning, based on an active learning algorithm and gradient optimizer, is designed to train the model. We found that the active learning machine not only saves the manual work to collect the training data but is also much more effective than the general optimizer.

Diffusivity of α-, β-, γ-cyclodextrin and the inclusion complex of β-cyclodextrin: Ibuprofen in aqueous solutions; A molecular dynamics simulation study

Cyclodextrins (CDs) are widely used in drug delivery, catalysis, food and separation processes. In this work, a comprehensive simulation study on the diffusion of the native α-, β- and γ-CDs in aqueous solutions is carried out using Molecular Dynamics simulations. The effect of the system size on the computed self-diffusivity is investigated and it is found that the required correction can be as much as 75% of the final value. The effect of the water force field is examined and it is shown that the q4md-CD/TIP4P/2005 force field combination predicts the experimentally measured self-diffusion coefficients of CDs very accurately. The self-diffusion coefficients of the three native CDs were also computed in aqueous-NaCl solutions using the Joung and Cheatham (JC) and the Madrid-2019 force fields. It is found that Na+ ions have higher affinity towards the CDs when the JC force field is used and for this reason the predicted diffusivity of CDs is lower compared to simulations using the Madrid-2019 force field. As a model system for drug delivery and waste-water treatment applications, the diffusion of the β-CD:Ibuprofen inclusion complex in water is studied. In agreement with experiments for similar components, it is shown that the inclusion complex and the free β-CD have almost equal self-diffusion coefficients. Our analysis revealed that this is most likely caused by the almost full inclusion of the ibuprofen in the cavity of the β-CD. Our findings show that Molecular Dynamics simulation can be used to provide reasonable diffusivity predictions, and to obtain molecular-level understanding useful for industrial applications of CDs.

Reactive and electron force field molecular dynamics simulations of electric field assisted ethanol oxidation reactions

In this research, a combination of reactive force field (ReaxFF) and electron force field (eFF) molecular dynamics (MD) simulations is constructed to reveal the fundamental mechanisms for the influence of the electric field on ethanol oxidation reactions at atomic and subatomic scales. In total, 21 ReaxFF MD simulations and 35 eFF MD simulations have been conducted. ReaxFF MD results indicate that the ethanol oxidation reaction is a two-stage process where the electric field plays varied roles in each stage. The first stage features the decomposition of ethanol molecules, in which the electric field influences the decomposition reaction rate by changing the kinetic energy of carbon-containing molecules/radicals on the order of 100–1000 kJ/mol and altering the molecular conformation and thereby the bond dissociation energy. At the second stage where oxygen molecules participate in the reaction, the electric field affects reactions by modifying the reaction pathways. The application of the eFF MD simulations, for the first time, extends our understanding of the electric field effects on ethanol oxidation reaction to subatomic scales. The results indicate that the electric field modifies the electron energy on the order of 10–100 kJ/mol. The present study also offers interpretation of previous findings on electric field effects on reaction pathways and fluorescence experimental observations, and provides support for both “ionic wind” and chemistry-driven hypotheses. This research provides unprecedented insight into reactions aided by the electric field, which potentially can facilitate the design of realistic field-assisted combustion systems.

Protein Surface Printer for Exploring Protein Domains

The surface of proteins is vital in determining protein functions. Herein, a program, Protein Surface Printer (PSP), is built that performs multiple functions in quantifying protein surface domains. Two proteins, PETase and cytochrome P450, are used to validate that the program supports atomistic simulations with different combinations of programs and force fields. A case study is conducted on the structural analysis of the spike proteins of SARS-CoV-2 and SARS-CoV and the human cell receptor ACE2. Although the surface domains of both spike proteins are highly similar, their receptor-binding domains (RBDs) and the O-linked glycan domains are structurally different. The O-linked glycan domain of SARS-CoV-2 is highly positively charged, which may promote binding to negatively charged human cells.

Using the generalized Born surface area model to fold proteins yields more effective sampling while qualitatively preserving the folding landscape.

Protein folding is a long-standing problem and has been widely investigated using molecular dynamics simulations with both explicit and implicit solvents. However, to what extent the folding mechanisms observed in two water models agree remains an open question. In this study, ab initio folding simulations of ten proteins with different topologies are performed in two combinations of force fields and water models (ff14SB+TIP3P and ff14SBonlysc+GB-Neck2). Interestingly, the latter combination not only folds more proteins but also provides a better balance of different secondary structures than the former in the same number of integration time steps. More importantly, the folding pathways found in the two types of simulations are conserved and they may only differ in their weights. Our results suggest that simulations with an implicit solvent may also be suitable for the investigation of the mechanism of protein folding.

The Effect of Force-Field Parameters on Cytochrome P450-Membrane Interactions: Structure and Dynamics

The simulation of membrane proteins requires compatible protein and lipid force fields that reproduce the properties of both the protein and the lipid bilayer. Cytochrome P450 enzymes are bitopic membrane proteins with a transmembrane helical anchor and a large cytosolic globular domain that dips into the membrane. As such, they are representative and challenging examples of membrane proteins for simulations, displaying features of both peripheral and integral membrane proteins. We performed molecular dynamics simulations of three cytochrome P450 isoforms (2C9, 2C19 and 1A1) in a 2-oleoyl-1-palmitoyl-sn-glycerol-3-phosphocholine bilayer using two AMBER force field combinations: GAFF-LIPID with ff99SB for the protein, and LIPID14 with ff14SB for the protein. Comparison of the structural and dynamic properties of the proteins, the lipids and the protein-membrane interactions shows differing sensitivity of the cytochrome P450 isoforms to the choice of force field, with generally better agreement with experiment for the LIPID14 + ff14SB combination.

Inclusion Complexation of Organic Micropollutants with β-Cyclodextrin.

Recently, β-cyclodextrin (βCD)-based polymers with enhanced adsorption kinetics and high removal capacity of organic micropollutants (OMPs) and uptake rates have been synthesized and tested experimentally. Although the exact physical–chemical mechanisms via which these polymers capture the various types of OMPs are not yet fully understood, it is suggested that the inclusion complex formation of OMPs with βCD is very important. In this study, the inclusion complex formation of OMPs with βCD in an aqueous solution is investigated by using the well-established attach–pull–release method in force field-based molecular dynamics simulations. A representative set of OMPs is selected based on the measured occurrences in surface and ground waters and the directives published by the European Union. To characterize the formation of the inclusion complex, the binding free energies, enthalpies, and entropies are computed and compared to experimental values. It is shown that computations using the q4md-CD/GAFF/Bind3P force field combination yield binding free energies that are in reasonable agreement with the experimental results for all OMPs studied. The binding enthalpies are decomposed into the main contributing interaction types. It is shown that, for all studied OMPs, the van der Waals interactions are favorable for the inclusion complexion and the hydrogen bond formation of the guest with the solvent and βCD plays a crucial role in the binding mechanism. Our findings show that MD simulations can adequately describe the inclusion complex formation of βCD with OMPs, which is the first step toward understanding the underlying mechanisms via which the βCD-based polymers capture OMPs.

Effect of Polymer Concentration on the Structure and Dynamics of Short Poly(N,N-dimethylaminoethyl methacrylate) in Aqueous Solution: A Combined Experimental and Molecular Dynamics Study

A combined experimental and molecular dynamics (MD) study is performed to investigate the effect of polymer concentration on the zero shear rate viscosity η0 of a salt-free aqueous solution of poly(N,N-dimethylaminoethyl methacrylate) (PDMAEMA), a flexible thermoresponsive weak polyelectrolyte with a bulky 3-methyl-1,1-diphenylpentyl unit as the terminal group. The study is carried out at room temperature (T = 298 K) with relatively short PDMAEMA chains (each containing N = 20 monomers or repeat units) at a fixed degree of ionization (α+ = 100%). For the MD simulations, a thorough validation of several molecular mechanics force fields is first undertaken for assessing their capability to accurately reproduce the experimental observations and established theoretical laws. The generalized Amber force field in combination with the restrained electrostatic potential charge fitting method is eventually adopted. Three characteristic concentration regimes are considered: the dilute (from 5 to 10 wt %), the semidilute (from 10 to 20 wt %), and the concentrated (from 20 to 29 wt %); the latter two are characterized by polymer concentrations cp higher than the characteristic overlap concentration cp*. The structural behavior of the PDMAEMA chains in the solution is assessed by calculating the square root of their mean-square radius of gyration ⟨Rg2⟩0.5, the square root of the average square chain end-to-end distance ⟨Ree2⟩0.5, the ratio ⟨Ree2⟩/⟨Rg2⟩, and the persistence length Lp. It is observed that at low polymer concentrations, PDMAEMA chains adopt a stiffer and slightly extended conformation because of excluded-volume effects (a good solvent is considered in this study) and electrostatic repulsions within the polymer chains. As the polymer concentration increases above 20 wt %, the PDMAEMA chains adopt more flexible conformations, as the excluded-volume effects seize and the charge repulsion within the polymer chains subsides. The effect of total polymer concentration on PDMAEMA chain dynamics in the solution is assessed by calculating the orientational relaxation time τc of the chain, the center-of-mass diffusion coefficient D, and the zero shear rate viscosity η0; the latter is also measured experimentally here and found to be in excellent agreement with the MD predictions.

A combined force field for the silica/nickel system

ABSTRACTSilica and nickel are frequently used in the synthesis of carbon nanotubes by the chemical vapour deposition (CVD) process. The molecular simulation of this process requires the knowledge of force fields to model the interactions occurring between those species at the atomic scale. This work proposes a combined force field to model the silica/nickel system when these components are in contact as substrate and catalyst, respectively, in the CVD process. The proposed combined force field includes the Lennard–Jones (n–m) potential for modelling the silicon/nickel pair interactions and the Buckingham potential for the oxygen/nickel pair interactions. The combined force field is completed by the Tersoff potential to model silica (SiO2) and the Sutton–Chen potential for the cohesive forces present in the nickel clusters. Parameters for the Lennard–Jones (n–m) and Buckingham pair potentials were fitted, by the least squares technique, to interaction energies data for the silica/nickel system. The energies were obtained from Ab-initio (DFT) calculations using the VASP code. It was found that the combined force field reproduces adequately, by molecular dynamics simulation, the adherence (adsorption) of nickel clusters on the silica surface. Keeping stable this configuration is crucial in modelling the carbon nanotubes synthesis by the CVD process.

The Role of Post-translational Modifications on the Energy Landscape of Huntingtin N-Terminus.

Huntington disease is a neurodegenerative disease characterized by a polymorphic tract of polyglutamine repeats in exon 1 of the huntingtin protein, which is thought to be responsible for protein aggregation and neuronal death. The polyglutamine tract is preceded by a 17-residue sequence that is intrinsically disordered. This region is subject to phosphorylation, acetylation and other post-translational modifications in vivo, which modulate its secondary structure, aggregation and, subcellular localization. We used Molecular Dynamics simulations with a novel Hamiltonian-replica-exchange-based enhanced sampling method, SWISH, and an optimal combination of water and protein force fields to study the effects of phosphorylation and acetylation as well as cross-talk between these modifications on the huntingtin N-terminus. The simulations, validated by circular dichroism, were used to formulate a mechanism by which the modifications influence helical conformations. Our findings have implications for understanding the structural basis underlying the effect of PTMs in the aggregation and cellular properties of huntingtin.