Molecular dynamics simulations using the drude polarizable force field on GPUs with OpenMM: Implementation, validation, and benchmarks

Pyroglutamylation modulates electronic properties and the conformational ensemble of the amyloid β-peptide

Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by the formation of extracellular amyloid-β (Aβ) plaques. The underlying cause of AD is unknown, however, post-translational modifications (PTMs) of Aβ have been found in AD patients and are thought to play a role in protein aggregation. One such PTM is pyroglutamylation, which can occur at two sites in Aβ, Glu3 and Glu11. This modification of Aβ involves the truncation and charge-neutralization of N-terminal glutamate, causing Aβ to become more hydrophobic and prone to aggregation. The molecular mechanism by which the introduction of pyroglutamate (pE) promotes aggregation has not been determined. To gain a greater understanding of the role that charge neutralization and truncation of the N-terminus plays on Aβ conformational sampling, we used the Drude polarizable force field (FF) to perform molecular dynamics simulations on AβpE3-42 and AβpE11-42 and comparing their properties to previous simulations of Aβ1-42. The Drude polarizable FF allows for a more accurate representation of electrostatic interactions, therefore providing novel insights into the role that charge plays in protein dynamics. Here, we report the parametrization of pE in the Drude polarizable FF and the effect of pyroglutamylation on Aβ. We found that AβpE3-42 and AβpE11-42 alter the permanent and induced dipoles of the peptide. Specifically, we found that AβpE3-42 and AβpE11-42 have modification-specific backbone and sidechain polarization response and perturbed solvation properties that shift the Aβ conformational ensemble.

Efficient Sampling of Cavity Hydration in Proteins with Nonequilibrium Grand Canonical Monte Carlo and Polarizable Force Fields

Prediction of the hydration levels of protein cavities and active sites is important to both mechanistic analysis and ligand design. Due to the unique microscopic environment of these buried water molecules, a polarizable model is expected to be crucial for an accurate treatment of protein internal hydration in simulations. Here we adapt a nonequilibrium candidate Monte Carlo approach for conducting grand canonical Monte Carlo simulations with the Drude polarizable force field. The GPU implementation enables the efficient sampling of internal cavity hydration levels in biomolecular systems. We also develop an enhanced sampling approach referred to as B-walking, which satisfies detailed balance and readily combines with grand canonical integration to efficiently calculate quantitative binding free energies of water to protein cavities. Applications of these developments are illustrated in a solvent box and the polar ligand binding site in trypsin. Our simulation results show that including electronic polarization leads to a modest but clear improvement in the description of water position and occupancy compared to the crystal structure. The B-walking approach enhances the range of water sampling in different chemical potential windows and thus improves the accuracy of water binding free energy calculations.

Reparameterization of Polarizable Force Fields for Studying Ion Transfer across Liquid-Liquid Interfaces

We have developed a general scheme for refining classical polarizable molecular dynamics (MD) force fields that can accurately describe the molecular interactions in systems with liquid-liquid interfaces. While ab initio MD (AIMD) simulations can naturally describe molecular interactions, they are often so computationally expensive that simulating large system sizes and/or long time scales is usually infeasible. To resolve this, we parameterized efficient and accurate classical polarizable force fields that use AIMD reference data by minimizing both the relative entropy and the root mean squared deviation in atomic forces. We utilized our new multiscale models to study chloride ion transfer across the water-dichloromethane (DCM) interface with and without the tetraethylammonium cation as the phase-transfer catalyst. Our calculated free-energy barrier for the water-DCM interface is consistent with the other reported simulation results. We further analyzed the ion-transfer process by studying the hydration shell structures around the chloride ion and the ion-pair formation to better understand the mechanism. We observed that electronic polarizability is an important factor for the studied phase-transfer catalyst to lower the free-energy barrier of the ion transfer. Using the water-benzene interface system as an additional example, we show that our parameterization scheme provides a general route for modeling different liquid-liquid interface systems even when the experimental data or force field parameters are not readily available.

Solvation-Tuned Photoacid as a Stable Light-Driven pH Switch for CO2 Capture and Release

Photoacids are organic molecules that release protons under illumination, providing spatiotemporal control of the pH. Such light-driven pH switches offer the ability to cyclically alter the pH of the medium and are highly attractive for a wide variety of applications, including CO2 capture. Although photoacids such as protonated merocyanine can enable fully reversible pH cycling in water, they have a limited chemical stability against hydrolysis (<24 h). Moreover, these photoacids have low solubility, which limits the pH-switching ability in a buffered solution such as dissolved CO2. In this work, we introduce a simple pathway to dramatically increase stability and solubility of photoacids by tuning their solvation environment in binary solvent mixtures. We show that a preferential solvation of merocyanine by aprotic solvent molecules results in a 60% increase in pH modulation magnitude when compared to the behavior in pure water and can withstand stable cycling for >350 h. Our results suggest that a very high stability of merocyanine photoacids can be achieved in the right solvent mixtures, offering a way to bypass complex structural modifications of photoacid molecules and serving as the key milestone toward their application in a photodriven CO2 capture process.

What to Make of Zero: Resolving the Statistical Noise from Conformational Reorganization in Alchemical Binding Free Energy Estimates with Metadynamics Sampling

We introduce the self-relative binding free energy (self-RBFE) approach to evaluate the intrinsic statistical variance of dual-topology alchemical binding free energy estimators. The self-RBFE is the relative binding free energy between a ligand and a copy of the same ligand, and its true value is zero. Nevertheless, because the two copies of the ligand move independently, the self-RBFE value produced by a finite-length simulation fluctuates and can be used to measure the variance of the model. The results of this validation provide evidence that a significant fraction of the errors observed in benchmark studies reflect the statistical fluctuations of unconverged estimates rather than the models' accuracy. Furthermore, we find that ligand reorganization is a significant contributing factor to the statistical variance of binding free energy estimates and that metadynamics-accelerated conformational sampling of the torsional degrees of freedom of the ligand can drastically reduce the time to convergence.

Implementation and Validation of an OpenMM Plugin for the Deep Potential Representation of Potential Energy

Machine learning potentials, particularly the deep potential (DP) model, have revolutionized molecular dynamics (MD) simulations, striking a balance between accuracy and computational efficiency. To facilitate the DP model's integration with the popular MD engine OpenMM, we have developed a versatile OpenMM plugin. This plugin supports a range of applications, from conventional MD simulations to alchemical free energy calculations and hybrid DP/MM simulations. Our extensive validation tests encompassed energy conservation in microcanonical ensemble simulations, fidelity in canonical ensemble generation, and the evaluation of the structural, transport, and thermodynamic properties of bulk water. The introduction of this plugin is expected to significantly expand the application scope of DP models within the MD simulation community, representing a major advancement in the field.

Improving the Accuracy of Physics-Based Hydration-Free Energy Predictions by Machine Learning the Remaining Error Relative to the Experiment

The accuracy of computational models of water is key to atomistic simulations of biomolecules. We propose a computationally efficient way to improve the accuracy of the prediction of hydration-free energies (HFEs) of small molecules: the remaining errors of the physics-based models relative to the experiment are predicted and mitigated by machine learning (ML) as a postprocessing step. Specifically, the trained graph convolutional neural network attempts to identify the "blind spots" in the physics-based model predictions, where the complex physics of aqueous solvation is poorly accounted for, and partially corrects for them. The strategy is explored for five classical solvent models representing various accuracy/speed trade-offs, from the fast analytical generalized Born (GB) to the popular TIP3P explicit solvent model; experimental HFEs of small neutral molecules from the FreeSolv set are used for the training and testing. For all of the models, the ML correction reduces the resulting root-mean-square error relative to the experiment for HFEs of small molecules, without significant overfitting and with negligible computational overhead. For example, on the test set, the relative accuracy improvement is 47% for the fast analytical GB, making it, after the ML correction, almost as accurate as uncorrected TIP3P. For the TIP3P model, the accuracy improvement is about 39%, bringing the ML-corrected model's accuracy below the 1 kcal/mol threshold. In general, the relative benefit of the ML corrections is smaller for more accurate physics-based models, reaching the lower limit of about 20% relative accuracy gain compared with that of the physics-based treatment alone. The proposed strategy of using ML to learn the remaining error of physics-based models offers a distinct advantage over training ML alone directly on reference HFEs: it preserves the correct overall trend, even well outside of the training set.

Performance and Analysis of the Alchemical Transfer Method for Binding-Free-Energy Predictions of Diverse Ligands

The Alchemical Transfer Method (ATM) is herein validated against the relative binding-free energies (RBFEs) of a diverse set of protein-ligand complexes. We employed a streamlined setup workflow, a bespoke force field, and AToM-OpenMM software to compute the RBFEs of the benchmark set prepared by Schindler and collaborators at Merck KGaA. This benchmark set includes examples of standard small R-group ligand modifications as well as more challenging scenarios, such as large R-group changes, scaffold hopping, formal charge changes, and charge-shifting transformations. The novel coordinate perturbation scheme and a dual-topology approach of ATM address some of the challenges of single-topology alchemical RBFE methods. Specifically, ATM eliminates the need for splitting electrostatic and Lennard-Jones interactions, atom mapping, defining ligand regions, and postcorrections for charge-changing perturbations. Thus, ATM is simpler and more broadly applicable than conventional alchemical methods, especially for scaffold-hopping and charge-changing transformations. Here, we performed well over 500 RBFE calculations for eight protein targets and found that ATM achieves accuracy comparable to that of existing state-of-the-art methods, albeit with larger statistical fluctuations. We discuss insights into the specific strengths and weaknesses of the ATM method that will inform future deployments. This study confirms that ATM can be applied as a production tool for RBFE predictions across a wide range of perturbation types within a unified, open-source framework.

Structure and Dynamics of Confined Water Inside Diphenylalanine Peptide Nanotubes

Diphenylalanine (FF) peptides exhibit a unique ability to self-assemble into nanotubes with confined water molecules playing pivotal roles in their structure and function. This study investigates the structure and dynamics of diphenylalanine peptide nanotubes (FFPNTs) using all-atom molecular dynamics (MD) and grand canonical Monte Carlo combined with MD (GCMC/MD) simulations with both the CHARMM additive and Drude polarizable force fields. The occupancy and dynamics of confined water molecules were also examined. It was found that less than 2 confined water molecules per FF help stabilize the FFPNTs on the x-y plane. Analyses of the kinetics of confined water molecules revealed distinctive transport behaviors for bound and free water, and their respective diffusion coefficients were compared. Our results validate the importance of polarizable force field models in studying peptide nanotubes and provide insights into our understanding of nanoconfined water.

Drude Polarizable Lipid Force Field with Explicit Treatment of Long-Range Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids

Accurate empirical force fields of lipid molecules are a critical component of molecular dynamics simulation studies aimed at investigating properties of monolayers, bilayers, micelles, vesicles, and liposomes, as well as heterogeneous systems, such as protein-membrane complexes, bacterial cell walls, and more. While the majority of lipid force field-based simulations have been performed using pairwise-additive nonpolarizable models, advances have been made in the development of the polarizable force field based on the classical Drude oscillator model. In the present study, we undertake further optimization of the Drude lipid force field, termed Drude2023, including improved treatment of the phosphate and glycerol linker region of PC and PE headgroups, additional optimization of the alkene group in monounsaturated lipids, and inclusion of long-range Lennard-Jones interactions using the particle-mesh Ewald method. Initial optimization targeted quantum mechanical (QM) data on small model compounds representative of the linker region. Subsequent optimization targeted QM data on larger model compounds, experimental data, and dihedral potentials of mean force from the CHARMM36 additive lipid force field using a parameter reweighting protocol. The use of both experimental and QM target data during the reweighting protocol is shown to produce physically reasonable parameters that reproduce a collection of experimental observables. Target data for optimization included surface area/lipid for DPPC, DSPC, DMPC, and DLPC bilayers and nuclear magnetic resonance (NMR) order parameters for DPPC bilayers. Validation data include prediction of membrane thickness, scattering form factors, electrostatic potential profiles, compressibility moduli, surface area per lipid, water permeability, NMR T1 relaxation times, diffusion constants, and monolayer surface tensions for a variety of saturated and unsaturated lipid mono- and bilayers. Overall, the agreement with experimental data is quite good, though the results are less satisfactory for the NMR T1 relaxation times for carbons near the ester groups. Notable improvements compared to the additive C36 force field were obtained for membrane dipole potentials, lipid diffusion coefficients, and water permeability with the exception of monounsaturated lipid bilayers. It is anticipated that the optimized polarizable Drude2023 force field will help generate more accurate molecular simulations of pure bilayers and heterogeneous systems containing membranes, advancing our understanding of the role of electronic polarization in these systems.

How Does Electronic Polarizability or Scaled-Charge Affect the Interfacial Properties of Room Temperature Ionic Liquids?

The room temperature ionic liquid (RTIL) air-liquid interface plays an important role in many applications. Herein, we present molecular dynamics simulation results for the air-liquid interface of a common RTIL, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide, [C4mim][NTf2]. To elucidate the effects of electronic polarizability and scaled-charge ions on the properties of the RTIL air-liquid interface, we employ three different kinds of force fields: a nonpolarizable force field (FF) with united ion charges (FixQ), a nonpolarizable FF with scaled-charge by 0.8 (ScaleQ), and a polarizable FF (Drude). To identify whether the ions reside at the interface or not, the method of identification of the truly interfacial molecules is used. The structural and dynamical properties in the interfacial, subinterfacial, and central layers are evaluated. In general for bulk liquids, the FixQ model predicts too-ordered structures and too-sluggish dynamics, while the ScaleQ model can serve as a simple cure. However, the ScaleQ model cannot reproduce the results of the Drude model at the interface, due to an inappropriate scaled-down charge near the interface.

Electrochemical Properties and Local Structure of the TEMPO/TEMPO+ Redox Pair in Ionic Liquids

Redox-active organic species play an important role in catalysis, energy storage, and biotechnology. One of the representatives is the 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) radical, used as a mediator in organic synthesis and considered a safe alternative to heavy metals. In order to develop a TEMPO-based system with well-controlled electrochemical and catalytic properties, a reaction medium should be carefully chosen. Being highly conductive, stable, and low flammability fluids, ionic liquids (ILs) seem to be promising solvents with easily adjustable physical and solvation properties. In this work, we give an insight into the local structure of ILs around TEMPO and its oxidized form, TEMPO⁺, underlining striking differences in the solvation of these two species. The analysis is coupled with a study of thermodynamics and kinetics of oxidation in the frame of Marcus theory. Our systematic investigation includes imidazolium, pyrrolydinium, and phosphonium families combined with anions of different size, polarity, and flexibility, opting to provide a clear and comprehensive picture of the impact of the nature of IL ions on the behavior of radical/cation redox pairs. The obtained results will help to explain experimentally observed effects and to rationalize the design of TEMPO/IL systems.

Computer-Aided Drug Design: An Update

Computer-aided drug design (CADD) approaches are playing an increasingly important role in understanding the fundamentals of ligand-receptor interactions and helping medicinal chemists design therapeutics. About 5 years ago, we presented a chapter devoted to an overview of CADD methods and covered typical CADD protocols including structure-based drug design (SBDD) and ligand-based drug design (LBDD) approaches that were frequently used in the antibiotic drug design process. Advances in computational hardware and algorithms and emerging CADD methods are enhancing the accuracy and ability of CADD in drug design and development. In this chapter, an update to our previous chapter is provided with a focus on new CADD approaches from our laboratory and other peers that can be employed to facilitate the development of antibiotic therapeutics.

Fast Polarizable Water Model for Atomistic Simulations

Simulating water accurately has been a major challenge in atomistic simulations for decades. Inclusion of electronic polarizability effects holds considerable promise, yet existing approaches suffer from significant computational overheads compared to the widely used nonpolarizable water models. We have developed a globally optimal polarizable water model, OPC3-pol, that explicitly accounts for electronic polarizability with minimal impact on the computational efficiency. OPC3-pol reproduces five key bulk water properties at room temperature with an average relative error of 0.6%. In atomistic simulations, OPC3-pol's computational efficiency is in between that of 3- and 4-point nonpolarizable models; the model supports increased (4 fs) integration time step. OPC3-pol is tested in simulations of globular protein ubiquitin and a B-DNA dodecamer with several AMBER force fields, ff99SB, ff14SB, ff19SB, and OL15, demonstrating structure stability close to reference on multi-microsecond time scale. Simulation of an intrinsically disordered amyloid β-peptide yields an ensemble with the radius of gyration of a random coil. The proposed water model can be trivially adopted by any package that supports standard nonpolarizable force fields and water models; its intended use is in long classical atomistic simulations where water polarization effects are expected to be important.

Effects of Familial Alzheimer's Disease Mutations on the Folding Free Energy and Dipole-Dipole Interactions of the Amyloid β-Peptide

Familial Alzheimer's disease (FAD) mutations of the amyloid β-peptide (Aβ) are known to lead to early onset and more aggressive Alzheimer's disease. FAD mutations such as "Iowa" (D23N), "Arctic" (E22G), "Italian" (E22K), and "Dutch" (E22Q) have been shown to accelerate Aβ aggregation relative to the wild-type (WT). The mechanism by which these mutations facilitate increased aggregation is unknown, but each mutation results in a change in the net charge of the peptide. Previous studies have used nonpolarizable force fields to study Aβ, providing some insight into how this protein unfolds. However, nonpolarizable force fields have fixed charges that lack the ability to redistribute in response to changes in local electric fields. Here, we performed polarizable molecular dynamics simulations on the full-length Aβ42 of WT and FAD mutations and calculated folding free energies of the Aβ15-27 fragment via umbrella sampling. By studying both the full-length Aβ42 and a fragment containing mutations and the central hydrophobic cluster (residues 17-21), we were able to systematically study how these FAD mutations impact secondary and tertiary structure and the thermodynamics of folding. Electrostatic interactions, including those between permanent and induced dipoles, affected side-chain properties, salt bridges, and solvent interactions. The FAD mutations resulted in shifts in the electronic structure and solvent accessibility at the central hydrophobic cluster and the hydrophobic C-terminal region. Using umbrella sampling, we found that the folding of the WT and E22 mutants is enthalpically driven, whereas the D23N mutant is entropically driven, arising from a different unfolding pathway and peptide-bond dipole response. Together, the unbiased, full-length, and umbrella sampling simulations of fragments reveal that the FAD mutations perturb nearby residues and others in hydrophobic regions to potentially alter solubility. These results highlight the role electronic polarizability plays in amyloid misfolding and the role of heterogeneous microenvironments that arise as conformational change takes place.

Polarizable Force Field of Intrinsically Disordered Proteins with CMAP and Reweighting Optimization

Intrinsically disordered proteins (IDPs) are highly structurally heterogeneous without a specific tertiary structure under physiology conditions and play key roles in the development of human diseases. Due to the characteristics of diverse conformations, as one of the important methods, molecular dynamics simulation can complement information for experimental methods. Because of the enrichment for charged amino acids for IDPs, polarizable force fields should be a good choice for the simulation of IDPs. However, current polarizable force fields are limited in sampling conformer features of IDPs. Therefore, a polarizable force field was released and named Drude2019IDP based on Drude2019 with reweighting and grid-based potential energy correction map optimization. In order to evaluate the performance of Drude2019IDP, 16 dipeptides, 18 short peptides, 3 representative IDPs, and 5 structural proteins were simulated. The results show that the NMR observables driven by Drude2019IDP are in better agreement with the experiment data than those by Drude2019 on short peptides and IDPs. Drude2019IDP can sample more diverse conformations than Drude2019. Furthermore, the performances of the two force fields are similar to the sample ordered proteins. These results confirm that the developed Drude2019IDP can improve the reproduction of conformers for intrinsically disordered proteins and can be used to gain insight into the paradigm of sequence-disorder for IDPs.

Relative binding free energy calculations with transformato: A molecular dynamics engine-independent tool

We present the software package transformato for the setup of large-scale relative binding free energy calculations. Transformato is written in Python as an open source project (https://github.com/wiederm/transformato); in contrast to comparable tools, it is not closely tied to a particular molecular dynamics engine to carry out the underlying simulations. Instead of alchemically transforming a ligand L₁ directly into another L₂, the two ligands are mutated to a common core. Thus, while dummy atoms are required at intermediate states, in particular at the common core state, none are present at the physical endstates. To validate the method, we calculated 76 relative binding free energy differences ΔΔGL1→L2bind for five protein–ligand systems. The overall root mean squared error to experimental binding free energies is 1.17 kcal/mol with a Pearson correlation coefficient of 0.73. For selected cases, we checked that the relative binding free energy differences between pairs of ligands do not depend on the choice of the intermediate common core structure. Additionally, we report results with and without hydrogen mass reweighting. The code currently supports OpenMM, CHARMM, and CHARMM/OpenMM directly. Since the program logic to choose and construct alchemical transformation paths is separated from the generation of input and topology/parameter files, extending transformato to support additional molecular dynamics engines is straightforward.

Ion-Dependent Conformational Plasticity of Telomeric G-Hairpins and G-Quadruplexes

Telomeric DNA is guanine-rich and can adopt structures such as G-quadruplexes (GQs) and G-hairpins. Telomeric GQs influence genome stability and telomerase activity, making understanding of enzyme-GQ interactions and dynamics important for potential drug design. GQs have a characteristic tetrad core, which is connected by loop regions. Within this architecture are G-hairpins, fold-back motifs that are thought to represent the first intermediate in GQ folding. To better understand the relationship between G-hairpin motifs and GQs, we performed polarizable simulations of a two-tetrad telomeric GQ and an isolated SC11 telomeric G-hairpin. The telomeric GQ contains a G-triad, which functions as part of the tetrad core or linker regions, depending on local conformational change. This triad and another motif below the tetrad core frequently bound ions and may represent druggable sites. Further, we observed the unbiased formation of a G-triad and a G-tetrad in simulations of the SC11 G-hairpin and found that cations can be partially hydrated while facilitating the formation of these motifs. Finally, we demonstrated that K⁺ ions form specific interactions with guanine bases, while Na⁺ ions interact nonspecifically with bases in the structure. Together, these simulations provide new insights into the influence of ions on GQs, G-hairpins, and G-triad motifs.

Electronic Polarization at the Interface between the p53 Transactivation Domain and Two Binding Partners

Intrinsically disordered proteins (IDPs) are an abundant class of highly charged proteins that participate in numerous crucial biological processes, often in regulatory roles. IDPs do not have one major free energy minimum with a dominant structure, instead existing as conformational ensembles of multiple semistable conformations. p53 is a prototypical protein with disordered regions and binds to many structurally diverse partners, making it a useful model for exploring the role of electrostatic interactions at IDP binding interfaces. In this study, we used the Drude-2019 force field to simulate the p53 transactivation domain with two protein partners to probe the role of electrostatic interactions in IDP protein-protein interactions. We found that the Drude-2019 polarizable force field reasonably reproduced experimental chemical shifts of the p53 transactivation domain (TAD) in one complex for which these data are available. We also found that the proteins in these complexes displayed dipole response at specific residues of each protein and that residues primarily involved in binding showed a large percent change in dipole moment between the unbound and complexed states. Probing the role of electrostatic interactions in IDP binding can allow us greater fundamental understanding of these interactions and may help with targeting p53 or its partners for drug design.

Recent Developments in Polarizable Molecular Dynamics Simulations of Electrolyte Solutions

Polarizable molecular dynamics simulations are a fast progressing field in the scientific research of ionic liquids. The fundamentals of polarizable simulations, as well as their application to ionic liquids, were summarized in a review [Bedrov, D.; Piquemal, J.-P.; Borodin, O.; MacKerell, Jr., A. D.; Roux, B.; Schröder, C. Molecular Dynamics Simulations of Ionic Liquids and Electrolytes Using Polarizable Force Fields. Chem. Rev. 2019, 119, 7940–7995] in 2019. Since then, new methods to treat intermolecular interaction of induced dipoles in these highly charged systems were developed. This concerns the damping of these interactions and additional charge transfer as well as the prediction of ionic materials with ultrahigh refractive indices. In addition to the progress of the polarizable force fields, also thermostats and barostats for polarizable simulations evolved recently.

Deep Neural Network Model to Predict the Electrostatic Parameters in the Polarizable Classical Drude Oscillator Force Field

The Drude polarizable force field (FF) captures electronic polarization effects via auxiliary Drude particles that are attached to non-hydrogen atoms, distinguishing it from commonly used additive FFs that rely on fixed charges. The Drude FF currently includes parameters for biomolecules such as proteins, nucleic acids, lipids, and carbohydrates and small-molecule representative of those classes of molecules as well as a range of atomic ions. Extension of the Drude FF to novel small druglike molecules is challenging as it requires the assignment of partial charges, atomic polarizabilities, and Thole scaling factors. In the present article, deep neural network (DNN) models are trained on quantum mechanical (QM)-based partial charges and atomic polarizabilities along with Thole scale factors trained to target QM molecular dipole moments and polarizabilities. Training of the DNN model used a collection of 39 421 molecules with molecular weights up to 200 Da and containing H, C, N, O, P, S, F, Cl, Br, or I atoms. The DNN model utilizes bond connectivity, including 1,2, 1,3, 1,4, and 1,5 terms and distances of Drude FF atom types as the feature vector to build the model, allowing it to capture both local and nonlocal effects in the molecules. Novel methods have been developed to determine restrained electrostatic potential (RESP) charges on atoms and external points representing lone pairs and to determine Thole scale factors, which have no QM analogue. A penalty scheme is devised as a performance predictor of the trained model. Validation studies show that these DNN models can precisely predict molecular dipole and polarizabilities of Food and Drug Administration (FDA)-approved drugs compared to reference MP2 calculations. The availability of the DNN model allowing for the rapid estimation of the Drude electrostatic parameters will facilitate its applicability to a wider range of molecular species.

Relative Binding Free Energy Calculations for Ligands with Diverse Scaffolds with the Alchemical Transfer Method

We present an extension of the alchemical transfer method (ATM) for the estimation of relative binding free energies of molecular complexes applicable to conventional, as well as scaffold-hopping, alchemical transformations. Named ATM-RBFE, the method is implemented in the free and open-source OpenMM molecular simulation package and aims to provide a simpler and more generally applicable route to the calculation of relative binding free energies than what is currently available. ATM-RBFE is based on sound statistical mechanics theory and a novel coordinate perturbation scheme designed to swap the positions of a pair of ligands such that one is transferred from the bulk solvent to the receptor binding site while the other moves simultaneously in the opposite direction. The calculation is conducted directly in a single solvent box with a system prepared with conventional setup tools, without splitting of electrostatic and nonelectrostatic transformations, and without pairwise soft-core potentials. ATM-RBFE is validated here against the absolute binding free energies of the SAMPL8 GDCC host-guest benchmark set and against protein-ligand benchmark sets that include complexes of the estrogen receptor ERα and those of the methyltransferase EZH2. In each case the method yields self-consistent and converged relative binding free energy estimates in agreement with absolute binding free energies and reference literature values, as well as experimental measurements.

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.

Impact of Electronic Polarization on Preformed, β-Strand Rich Homogenous and Heterogeneous Amyloid Oligomers

Amyloids are a subset of intrinsically disordered proteins (IDPs) that self-assemble into cross-[Formula: see text] oligomers and fibrils. The structural plasticity of amyloids leads to sampling of metastable, low-molecular-weight oligomers that contribute to cytotoxicity. Of interest are amyloid-[Formula: see text] (A[Formula: see text] and islet amyloid polypeptide (IAPP), which are involved in the pathology of Alzheimer’s disease and Type 2 diabetes mellitus, respectively. In addition to forming homogenous oligomers and fibrils, these species have been found to cross-aggregate in heterogeneous structures. Biophysical properties, including electronic effects, that are unique or conserved between homogenous and heterogeneous amyloids oligomers are thus far unexplored. Here, we simulated homogenous and heterogeneous amyloid oligomers of A[Formula: see text] and IAPP[Formula: see text] fragments using the Drude oscillator model to investigate the impact of electronic polarization on the structural morphology and stability of preformed hexamers. Upon simulation of preformed, [Formula: see text]-strand rich oligomers with Drude, structural rearrangement occurred causing some loss of [Formula: see text]-strand structure in favor of random coil content for all oligomers. Homogenous A[Formula: see text] was the most stable system, deriving stability from low polarization in hydrophobic residues and through salt bridge formation. Changes in polarization were observed primarily for A[Formula: see text] residues in heterogeneous cross-amyloid systems, displaying a decrease in charged residue dipole moments and an increase in hydrophobic sidechain dipole moments. This work is the first study utilizing the Drude-2019 force field with amyloid oligomers, providing insight into the impact of electronic effects on oligomer structure and highlighting the importance of different microenvironments on amyloid oligomer stability.

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. In addition, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. The capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

Global Optimization of the Lennard-Jones Parameters for the Drude Polarizable Force Field

Molecular dynamics (MD) simulations based on atomic models play an important role in the drug-discovery process to screen molecules, estimate binding free energies, and optimize lead compounds in chemical space. Accurate computations of thermodynamic and kinetic properties using MD simulations are highly dependent on the accuracy of the underlying atomic force field. In this context, going beyond the nonpolarizable fixed-charge model by accounting explicitly for induced polarization is highly desirable. The CHARMM polarizable force field based on classical Drude oscillators, in which an auxiliary charged particle is attached via a harmonic spring to its parent nucleus, offers both a computationally convenient and rigorous framework to model explicitly induced electronic polarization in MD simulations. For any molecule of interest, electrostatic partial charges, atomic polarizabilities, and Thole shielding factors, as well as bonded parameters can either be determined from ab initio calculations or ascribed from the knowledge-based library of the CHARMM Generalized force field. While this approach is fairly reliable in general, it is well understood that the overall accuracy of the models with respect to thermodynamic properties such as bulk density, enthalpies, and solvation free energies is particularly sensitive to the nonbonded Lennard-Jones (LJ) parameters. In the present study, we systematically refined the set of LJ parameters for the atom types available in the Drude force field to best match the experimental thermodynamic properties for 416 small druglike organic molecules. To further test the transferability of the optimized parameters, the hydration free energy of 372 molecules was computed. The calculations resulted in a small average error of 0.46 kcal/mol and a Pearson R of 0.9, representing a significant improvement over the additive GAFF force field in our previous study, where an average error of ∼2 kcal/mol was obtained. Such an improvement is consistent with the ability of the polarizable Drude model to more accurately model interactions in different environments. The effort provides a roadmap for the global optimization of force field parameters using experimental data. It is hoped that the present effort will further the application of the Drude polarizable force field in molecular simulations including drug design and discovery.

Physics-based, neural network force fields for reactive molecular dynamics: Investigation of carbene formation from [EMIM+][OAc-]

Reactive molecular dynamics simulations enable a detailed understanding of solvent effects on chemical reaction mechanisms and reaction rates. While classical molecular dynamics using reactive force fields allows significantly longer simulation time scales and larger system sizes compared with ab initio molecular dynamics, constructing reactive force fields is a difficult and complex task. In this work, we describe a general approach following the empirical valence bond framework for constructing ab initio reactive force fields for condensed phase simulations by combining physics-based methods with neural networks (PB/NNs). The physics-based terms ensure the correct asymptotic behavior of electrostatic, polarization, and dispersion interactions and are compatible with existing solvent force fields. NNs are utilized for a versatile description of short-range orbital interactions within the transition state region and accurate rendering of vibrational motion of the reacting complex. We demonstrate our methodology for a simple deprotonation reaction of the 1-ethyl-3-methylimidazolium cation with acetate to form 1-ethyl-3-methylimidazol-2-ylidene and acetic acid. Our PB/NN force field exhibits ∼1 kJ mol^-1 mean absolute error accuracy within the transition state region for the gas-phase complex. To characterize the solvent modulation of the reaction profile, we compute potentials of mean force for the gas-phase reaction as well as the reaction within a four-ion cluster and benchmark against ab initio molecular dynamics simulations. We find that the surrounding ionic environment significantly destabilizes the formation of the carbene product, and we show that this effect is accurately captured by the reactive force field. By construction, the PB/NN potential may be directly employed for simulations of other solvents/chemical environments without additional parameterization.

Preparing and Analyzing Polarizable Molecular Dynamics Simulations with the Classical Drude Oscillator Model

Molecular dynamics (MD) simulations performed with force fields that include explicit electronic polarization are becoming more prevalent in the field. The increasing emergence of these simulations is a result of continual refinement against a range of theoretical and empirical target data, optimization of software algorithms for higher performance, and availability of graphical processing unit hardware to further accelerate the simulations. Polarizable MD simulations are likely to be most impactful in biomolecular systems in which heterogeneous environments or unique microenvironments exist that would lead to inaccuracies in simulations performed with fixed-charge, nonpolarizable force fields. The further adoption of polarizable MD simulations will benefit from tutorial material that specifically addresses preparing and analyzing their unique features. In this chapter, we introduce common protocols for preparing routine biomolecular systems containing proteins, including both a globular protein in aqueous solvent and a transmembrane model peptide in a phospholipid bilayer. Details and example input files are provided for preparation of the simulation system using CHARMM, performing the simulations with OpenMM, and analyzing interesting dipole moment properties in CHARMM.

Polarizable and non-polarizable force fields: Protein folding, unfolding, and misfolding

Molecular dynamics simulations are an invaluable tool to characterize the dynamic motions of proteins in atomistic detail. However, the accuracy of models derived from simulations inevitably relies on the quality of the underlying force field. Here, we present an evaluation of current non-polarizable and polarizable force fields (AMBER ff14SB, CHARMM 36m, GROMOS 54A7, and Drude 2013) based on the long-standing biophysical challenge of protein folding. We quantify the thermodynamics and kinetics of the β-hairpin formation using Markov state models of the fast-folding mini-protein CLN025. Furthermore, we study the (partial) folding dynamics of two more complex systems, a villin headpiece variant and a WW domain. Surprisingly, the polarizable force field in our set, Drude 2013, consistently leads to destabilization of the native state, regardless of the secondary structure element present. All non-polarizable force fields, on the other hand, stably characterize the native state ensembles in most cases even when starting from a partially unfolded conformation. Focusing on CLN025, we find that the conformational space captured with AMBER ff14SB and CHARMM 36m is comparable, but the ensembles from CHARMM 36m simulations are clearly shifted toward disordered conformations. While the AMBER ff14SB ensemble overstabilizes the native fold, CHARMM 36m and GROMOS 54A7 ensembles both agree remarkably well with experimental state populations. In addition, GROMOS 54A7 also reproduces experimental folding times most accurately. Our results further indicate an over-stabilization of helical structures with AMBER ff14SB. Nevertheless, the presented investigations strongly imply that reliable (un)folding dynamics of small proteins can be captured in feasible computational time with current additive force fields.

Molecular insight into optimizing the N- and P-doped fullerenes for urea removal in wearable artificial kidneys

Urea is the result of the breakdown of proteins in the liver, the excess of which circulates in the blood and is adsorbed by the kidneys. However, in the case of kidney diseases, some products, specifically urea, cannot be removed from the blood by the kidneys and causes serious health problems. The end-stage renal disease (ESRD) patients are not able to purify their blood, which endangers their life. ESRD patients require dialysis, a costly and difficult method of urea removal from the blood. Wearable artificial kidneys (WAKs) are consequently designed to remove the waste from blood. Regarding the great amount of daily urea production in the body, WAKs should contain strong and selective urea adsorbents. Fullerenes-which possess fascinating chemical properties-have been considered herein to develop novel urea removal adsorbents. Molecular dynamics (MD) has enabled researchers to study the interaction of different materials and can pave the way toward facilitating the development of wearable devices. In this study, urea adsorption by N-doped fullerenes and P-doped fullerenes were assessed through MD simulations. The urea adsorption was simulated by five samples of fullerenes, with phosphorous and different nitrogen dopant contents. For comparing the urea adsorption capacity in the performed simulations, detailed characteristics-including the energy analysis, radius of gyration, radial distribution function (RDF), root-mean-square fluctuation (RMSD), and H-bond analyses were investigated. It had been determined that the fullerene containing 8% nitrogen-with the highest reduction in the radius of gyration, the maximum RDF, a high adsorption energy, and a high number of hydrogen bonds-adsorbs urea more efficiently.

Cation competition and recruitment around the c-kit1 G-quadruplex using polarizable simulations

Nucleic acid-ion interactions are fundamentally important to the physical, energetic, and conformational properties of DNA and RNA. These interactions help fold and stabilize highly ordered secondary and tertiary structures, such as G-quadruplexes (GQs), which are functionally relevant in telomeres, replication initiation sites, and promoter sequences. The c-kit proto-oncogene encodes for a receptor tyrosine kinase and is linked to gastrointestinal stromal tumors, mast cell disease, and leukemia. This gene contains three unique GQ-forming sequences that have proposed antagonistic effects on gene expression. The dominant GQ, denoted c-kit1, has been shown to decrease expression of c-kit transcripts, making the c-kit1 GQ a promising drug target. Toward disease intervention, more information is needed regarding its conformational dynamics and ion binding properties. Therefore, we performed molecular dynamics simulations of the c-kit1 GQ with K⁺, Na⁺, Li⁺, and mixed salt solutions using the Drude-2017 polarizable force field. We evaluated GQ structure, ion sampling, core energetics, ion dehydration and binding, and ion competition and found that each analysis supported the known GQ-ion specificity trend (K⁺ > Na⁺ > Li⁺). We also found that K⁺ ions coordinate in the tetrad core antiprismatically, whereas Na⁺ and Li⁺ align coplanar to guanine tetrads, partially because of their attraction to surrounding water. Further, we showed that K⁺ occupancy is higher around the c-kit1 GQ and its nucleobases than Na⁺ and Li⁺, which tend to interact with backbone and sugar moieties. Finally, we showed that K⁺ binding to the c-kit1 GQ is faster and more frequent than Na⁺ and Li⁺. Such descriptions of GQ-ion dynamics suggest the rate of dehydration as the dominant factor for preference of K⁺ by DNA GQs and provide insight into noncanonical nucleic acids for which little experimental data exist.

Effect of side chain modifications in imidazolium ionic liquids on the properties of the electrical double layer at a molybdenum disulfide electrode

Knowledge of how the molecular structures of ionic liquids (ILs) affect their properties at electrified interfaces is key to the rational design of ILs for electric applications. Polarizable molecular dynamics simulations were performed to investigate the structural, electrical, and dynamic properties of electric double layers (EDLs) formed by imidazolium dicyanamide ([ImX1][DCA]) at the interface with the molybdenum disulfide electrode. The effect of side chain of imidazolium on the properties of EDLs was analyzed by using 1-ethyl-3-methylimidazolium ([Im21]), 1-octyl-3-methylimidazolium ([Im81]), 1-benzyl-3-methylimidazolium ([ImB1]), and 1-(2-hydroxyethyl)-3-methylimidazolium ([ImO1]) as cations. Using [Im21] as reference, we find that the introduction of octyl or benzyl groups significantly alters the interfacial structures near the cathode because of the reorientation of cations. For [Im81], the positive charge on the cathode induces pronounced polar and non-polar domain separation. In contrast, the hydroxyl group has a minor effect on the interfacial structures. [ImB1] is shown to deliver slightly larger capacitance than other ILs even though it has larger molecular volume than [Im21]. This is attributed to the limiting factor for capacitance being the strong association between counter-ions, instead of the free space available to ions at the interface. For [Im81], the charging mechanism is mainly the exchange between anions and octyl tails, while for the other ILs, the mechanism is mainly the exchange of counter-ions. Analysis on the charging process shows that the charging speed does not correlate strongly with macroscopic bulk dynamics like viscosity. Instead, it is dominated by local displacement and reorientation of ions.

Determination of van der Waals Parameters Using a Double Exponential Potential for Nonbonded Divalent Metal Cations in TIP3P Solvent

A double exponential (DE) functional form for Lennard-Jones (LJ) interactions, proposed in our previous study, has many advantages over LJ potentials including a natural softcore characteristic for the convenience of the pathway-based free-energy calculations, fast convergence, and flexibility in use. In this work, we put the first step on the application of the DE functional form by identifying a DE potential, coined DE-TIP3P, for molecular simulations using the TIP3P water model. The developed DE-TIP3 potential was better than LJ potential in reproducing the experimental water properties. Afterward, we developed the nonbonded models of 15 divalent metal ions, which frequently appear and play vital roles in biological systems, to be consistent with the DE-TIP3P potential and TIP3P water model. Our nonbonded models were as good as the complicated nonbonded dummy cationic models by Jiang et al. and the nonbonded 12-6-4 LJ models by Li and Merz in reproducing the experimental properties of those ions. Moreover, our nonbonded models achieved a better performance than the compromise (CM) LJ models and 12-6-4 LJ models, developed by Li and Merz, in reproducing the properties of MgCl₂ in aqueous solution.

Extension of the CL&Pol Polarizable Force Field to Electrolytes, Protic Ionic Liquids, and Deep Eutectic Solvents

The polarizable CL&Pol force field presented in our previous study, Transferable, Polarizable Force Field for Ionic Liquids (J. Chem. Theory Comput. 2019, 15, 5858, DOI: http://doi.org/10.1021/acs.jctc.9b0068910.1021/acs.jctc.9b00689), is extended to electrolytes, protic ionic liquids (PIL), deep eutectic solvents (DES), and glycols. These systems are problematic in polarizable simulations because they contain either small, highly charged ions or strong hydrogen bonds, which cause trajectory instabilities due to the pull exerted on the induced dipoles. We use a Tang-Toennies (TT) function to dampen, or smear, the interactions between charges and induced dipole at a short range involving small, highly charged atoms (such as hydrogen or lithium), thus preventing the "polarization catastrophe". The new force field gives stable trajectories and is validated through comparison with experimental data on density, viscosity, and ion diffusion coefficients of liquid systems of the above-mentioned classes. The results also shed light on the hydrogen-bonding pattern in ethylammonium nitrate, a PIL, for which the literature contains conflicting views. We describe the implementation of the TT damping function, of the temperature-grouped Nosé-Hoover thermostat for polarizable molecular dynamics (MD) and of the periodic perturbation method for viscosity evaluation from non-equilibrium trajectories in the LAMMPS MD code. The main result of this work is the wider applicability of the CL&Pol polarizable force field to new, important classes of fluids, achieving robust trajectories and a good description of equilibrium and transport properties in challenging systems. The fragment-based approach of CL&Pol will allow ready extension to a wide variety of PILs, DES, and electrolytes.

Polarization Effects in Water-Mediated Selective Cation Transport across a Narrow Transmembrane Channel

Despite the progress in modeling complex molecular systems of ever-increasing complexity, a quantitatively accurate computational treatment of ion permeation through narrow membrane channels remains challenging. An important factor to reach this goal is induced electronic polarization, which is likely to impact the permeation rate of small ions through narrow molecular pores. In this work, we extended the recently developed polarizable force field based on the classical Drude oscillators to assess the role of induced polarization effects on the energetics of sodium and potassium ion transport across the gramicidin A (gA) ion channel. The inclusion of induced polarization lowers barriers present in 1D potential of mean force (PMF) for cation permeation by ∼50% compared to those obtained with the additive force field. Conductance properties calculated with 1D PMFs from Drude simulations are in better agreement with experimental results. Polarization of single-file water molecules and protein atoms forming the narrow pore has a direct impact on the free-energy barriers and cation-specific solid-state NMR chemical shifts. Sensitivity analysis indicates that small changes to water-channel interactions can alter the free energy barrier for ion permeation. These results, illustrating polarization effects present in the complex electrostatic environment of the gA channel, have broad implications for revising proposed mechanisms of ion permeation and selectivity in a variety of ion channels.

Potential treatment of Parkinson's disease using new-generation carbon nanotubes: a biomolecular in silico study

Background: One of the underlying mechanisms of Parkinson's disease is the aggregation of α-synuclein proteins, including amyloids and Lewy bodies in the brain. Aim: To study the inhibitory effect of doped carbon nanotubes (CNTs) on amyloid aggregation. Materials & methods: Molecular dynamics tools were utilized to simulate the influence of CNTs doped with phosphorus, nitrogen and bromine and nitrogen on the formation of α-synuclein amyloid. Results: The CNTs exhibited strong interactions with α-synuclein, with phosphorus-doped CNTs having the most substantial interactions. Conclusion: Doped-CNTs, especially phosphorus-doped carbon nanotube could effectively prevent α-synuclein amyloid formation, thus, it could be considered as a potential treatment for Parkinson's disease. However, further in vitro and clinical investigations are required.

Methylguanidinium at the Air/Water Interface: A Simulation Study with the Drude Polarizable Force Field

Methylguanidinium is an important molecular ion, which also serves as the model compound for the arginine side chain. We studied the structure and dynamics of the methylguanidium ion at the air/water interface by molecular dynamics simulations employing the Drude polarizable force field. We found out that methylguanidinium accumulated at the interface, with a majority adopting tilted conformations. We also demonstrated that methylguanidinium and guanidinium ions had different preference toward the air/water interface. Detailed analysis of induced dipole moments showed how ions adjusted their charge distribution at the interface and revealed how the anisotropy in molecular polarizability impacted the orientation of molecular ions. Our results illustrate the importance of explicitly including the electronic polarization effects in modeling interfacial properties.

Ion Binding Properties and Dynamics of the bcl-2 G-Quadruplex Using a Polarizable Force Field

G-quadruplexes (GQs) are topologically diverse, highly thermostable noncanonical nucleic acid structures that form in guanine-rich sequences in DNA and RNA. GQs are implicated in transcriptional and translational regulation and genome maintenance, and deleterious alterations to their structures contribute to diseases such as cancer. The expression of the B-cell lymphoma 2 (Bcl-2) antiapoptotic protein, for example, is under transcriptional control of a GQ in the promoter of the bcl-2 gene. Modulation of the bcl-2 GQ by small molecules is of interest for chemotherapeutic development but doing so requires knowledge of the factors driving GQ folding and stabilization. To develop a greater understanding of the electrostatic properties of the bcl-2 promoter GQ, we performed molecular dynamics simulations using the Drude-2017 polarizable force field and compared relevant outcomes to the nonpolarizable CHARMM36 force field. Our simulation outcomes highlight the importance of dipole-dipole interactions in the bcl-2 GQ, particularly during the recruitment of a bulk K⁺ ion to the solvent-exposed face of the tetrad stem. We also predict and characterize an "electronegative pocket" at the tetrad-long loop junction that induces local backbone conformational change and may induce local conformational changes at cellular concentrations of K⁺. These outcomes suggest that moieties within the bcl-2 GQ can be targeted by small molecules to modulate bcl-2 GQ stability.

Milestoning: An Efficient Approach for Atomically Detailed Simulations of Kinetics in Biophysics

Recent advances in theory and algorithms for atomically detailed simulations open the way to the study of the kinetics of a wide range of molecular processes in biophysics. The theories propose a shift from the traditionally very long molecular dynamic trajectories, which are exact but may not be efficient in the study of kinetics, to the use of a large number of short trajectories. The short trajectories exploit a mapping to a mesh in coarse space and allow for efficient calculations of kinetics and thermodynamics. In this review, I focus on one theory: Milestoning is a theory and an algorithm that offers a hierarchical calculation of properties of interest, such as the free energy profile and the mean first passage time. Approximations to the true long-time dynamics can be computed efficiently and assessed at different steps of the investigation. The theory is discussed and illustrated using two biophysical examples: ion permeation through a phospholipid membrane and protein translocation through a channel.

Statistical mechanics of polarizable force fields based on classical Drude oscillators with dynamical propagation by the dual-thermostat extended Lagrangian

Polarizable force fields based on classical Drude oscillators offer a practical and computationally efficient avenue to carry out molecular dynamics (MD) simulations of large biomolecular systems. To treat the polarizable electronic degrees of freedom, the Drude model introduces a virtual charged particle that is attached to its parent nucleus via a harmonic spring. Traditionally, the need to relax the electronic degrees of freedom for each fixed set of nuclear coordinates is achieved by performing an iterative self-consistent field (SCF) calculation to satisfy a selected tolerance. This is a computationally demanding procedure that can increase the computational cost of MD simulations by nearly one order of magnitude. To avoid the costly SCF procedure, a small mass is assigned to the Drude particles, which are then propagated as dynamic variables during the simulations via a dual-thermostat extended Lagrangian algorithm. To help clarify the significance of the dual-thermostat extended Lagrangian propagation in the context of the polarizable force field based on classical Drude oscillators, the statistical mechanics of a dual-temperature canonical ensemble is formulated. The conditions for dynamically maintaining the dual-temperature properties in the case of the classical Drude oscillator are analyzed using the generalized Langevin equation.

Recent developments in empirical atomistic force fields for nucleic acids and applications to studies of folding and dynamics

Nucleic acids play critical roles in carrying genetic information, participating in catalysis, and preserving chromosomal structure. Despite over a century of study, efforts to understand the dynamics and structure-function relationships of DNA and RNA at the atomic level are still ongoing. Molecular dynamics (MD) simulations augment experiments by providing atomistic resolution and quantitative relationships between structure and conformational energy. Steady advancements in computer hardware, software, and atomistic force fields (FFs) over 40 years have facilitated new discoveries. Here, we review nucleic acid FF development with emphasis on recent refinements that have improved descriptions of important nucleic acid properties. We then discuss several key examples of successes and challenges in modeling nucleic acid structure and dynamics using the latest FFs.

Graphene-Based Nanoparticles as Potential Treatment Options for Parkinson's Disease: A Molecular Dynamics Study

INTRODUCTION

The study of abnormal aggregation of proteins in different tissues of the body has recently earned great attention from researchers in various fields of science. Concerning neurological diseases, for instance, the accumulation of amyloid fibrils can contribute to Parkinson's disease, a progressively severe neurodegenerative disorder. The most prominent features of this disease are the degeneration of neurons in the substantia nigra and accumulation of α-synuclein aggregates, especially in the brainstem, spinal cord, and cortical areas. Dopamine replacement therapies and other medications have reduced motor impairment and had positive consequences on patients' quality of life. However, if these medications are stopped, symptoms of the disease will recur even more severely. Therefore, the improvement of therapies targeting more basic mechanisms like prevention of amyloid formation seems to be critical. It has been shown that the interactions between monolayers like graphene and amyloids could prevent their fibrillation.

METHODS

For the first time, the impact of four types of last-generation graphene-based nanostructures on the prevention of α-synuclein amyloid fibrillation was investigated in this study by using molecular dynamics simulation tools.

RESULTS

Although all monolayers were shown to prevent amyloid fibrillation, nitrogen-doped graphene (N-Graphene) caused the most instability in the secondary structure of α-synuclein amyloids. Moreover, among the four monolayers, N-Graphene was shown to present the highest absolute value of interaction energy, the lowest contact level of amyloid particles, the highest number of hydrogen bonds between water and amyloid molecules, the highest instability caused in α-synuclein particles, and the most significant decrease in the compactness of α-synuclein protein.

DISCUSSION

Ultimately, it was concluded that N-Graphene could be the most effective monolayer to disrupt amyloid fibrillation, and consequently, prevent the progression of Parkinson's disease.

Engineering the pH-Sensitivity of the Graphene and Carbon Nanotube Based Nanomedicines in Smart Cancer Therapy by Grafting Trimetyl Chitosan

PURPOSE

The aim of this study was to introduce a smart and responsive drug carrier for Doxorubicin (DOX) and Paclitaxel (PAX) for desirable therapeutic application.

METHOD

Loading and releasing of DOX and PAX from smart and pH-sensitive functionalized single-walled carbon nanotube (SWCNTs) and graphene carriers have been simulated by molecular dynamics. The influences of chitosan polymer on proposed carriers have been studied, and both carriers were functionalized with carboxyl groups to improve the loading and releasing properties of the drugs.

RESULTS

The results showed that DOX could be well adsorbed on both functionalized SWCNTs and graphene. In contrast, there was a weak electrostatic and Van der Waals interaction between both these drugs and carriers at cancerous tissues, which is highly favorable for cancer therapy. Adding trimethyl chitosan (TMC) polymer to carriers facilitated DOX release at acidic tissues. Furthermore, at blood pH, the PAX loaded on the functionalized SWCNTs carrier represented the highest dispersion of the drug while the DOX-graphene showed the highest concentration of the drug at a point. In addition, the mean-square displacement (MSD) results of PAX-graphene indicated that the PAX could be adsorbed quickly and be released slowly. Finally, functionalized graphene-TMC-PAX is a smart drug system with responsive behavior and controllable drug release, which are essential in cancer therapy.

CONCLUSION

Simultaneous application of the carboxyl group and TMC can optimize the pH sensitivity of the SWCNTs and graphene to prepare a novel and smart drug carrier for cancer therapy.

Molecular insight into the smart functionalized TMC-Fullerene nanocarrier in the pH-responsive adsorption and release of anti-cancer drugs

The Doxorubicin (DOX) and Paclitaxel (PAX) are widely used for cancer-therapy. Herein, in the efforts devoted to developing smart drug carriers, the loading and releasing of the DOX and PAX on the pH sensitive functionalized Fullerene carrier was investigated by molecular dynamics (MD) simulations. The effects of chitosan polymer as a functionalizing agent of the Fullerene carrier was also studied. In addition, the Fullerene carrier was functionalized with carboxyl groups in order to improve the loading and releasing properties of the DOX and PAX. The results showed the DOX is well adsorbed on Fullerene which was functionalized with carboxyl group and it was released controllably in cancerous tissues. According to the results of the electrostatic and Van der Waals interactions, it was found that the functionalized Fullerene can be a proper carrier for DOX in comparison with PAX. Adding the trimethyl chitosan (TMC) polymer to the carrier could improve the Van der Waals attractions of the PAX and Fullerene which indicates that by passing the time at acidic pH, the Van der Waals energy reaches zero that leads to promote the release of the PAX in cancerous tissues. The carboxyl group which was employed as a functionalizing agent could also increase the number of hydrogen bonds for the PAX and DOX at acidic and neutral pH, respectively. Moreover, a significant rise in the number of hydrogen bonds between the PAX and Fullerene at neutral pH was achieved by adding the TMC to the carrier. A more decrease of gyration radius was obtained for the DOX at acidic pH which confirms that the DOX with TMC-Fullerene is a more stable carrier. So, this smart nanomedicine system is introduced as an promising composition for smart cancer therapy.

Balanced polarizable Drude force field parameters for molecular anions: phosphates, sulfates, sulfamates, and oxides

Polarizable force fields are emerging as a more accurate alternative to additive force fields in terms of modeling and simulations of a variety of chemicals including biomolecules. Explicit treatment of induced polarization in charged species such as phosphates and sulfates offers the potential for achieving an improved atomistic understanding of the physical forces driving their interactions with their environments. To help achieve this, in this study we present balanced Drude polarizable force field parameters for molecular ions including phosphates, sulfates, sulfamates, and oxides. Better balance was primarily achieved in the relative values of minimum interaction energies and distances of the anionic model compounds with water at the Drude and quantum mechanical (QM) model chemistries. Parametrization involved reoptimizing available parameters as well as extending the force field to new molecules with the goal of achieving self-consistency with respect to the Lennard-Jones and electrostatic parameters targeting QM and experimental hydration free energies. The resulting force field parameters achieve consistent treatment across the studied anions, facilitating more balanced simulations of biomolecules and small organic molecules in the context of the classical Drude polarizable force field. Graphical abstract.

Further Optimization and Validation of the Classical Drude Polarizable Protein Force Field

The CHARMM Drude-2013 polarizable force field (FF) was developed to include the explicit treatment of induced electronic polarizability, resulting in a more accurate description of the electrostatic interactions in molecular dynamics (MD) simulations. While the Drude-2013 protein FF has shown success in improving the folding properties of α-helical peptides and to reproduce experimental observables in simulations up to 1 μs, some limitations were noted regarding the stability of β-sheet structures in simulations longer than 100 ns as well as larger deviations from crystal structures in simulations of a number of proteins compared to the additive CHARMM36 protein FF. The origin of the instability has been identified and appears to be primarily due to overestimated atomic polarizabilities and induced dipole-dipole interactions on the Cβ, Cγ, and Cδ side chain atoms. To resolve this and other issues, a number of aspects of the model were revisited, resulting in Drude-2019 protein FF. Backbone parameters were optimized targeting the conformational properties of the (Ala)5 peptide in solution along with gas phase properties of the alanine dipeptide. Dipeptides that contain N-acetylated and N'-methylamidated termini, excluding Gly, Pro, and Ala, were used as models to optimize the atomic polarizabilities and Thole screening factors on selected Cβ, Cγ, and Cδ carbons by targeting quantum mechanical (QM) dipole moments and molecular polarizabilities. In addition, to obtain better conformational properties, side chain χ1 and χ2 dihedral parameters were optimized targeting QM data for the respective side chain dipeptide conformations as well as Protein Data Bank survey data based on the χ1, χ2 sampling from Hamiltonian replica-exchange MD simulations of (Ala)4-X-(Ala)4 in solution, where X is the amino acid of interest. Further improvements include optimizing nonbonded interactions between charged residues to reproduce QM interaction energies of the charged-protein model compounds and experimental osmotic pressures. Validation of the optimized Drude protein FF includes MD simulations of a collection of peptides and proteins including β-sheet structures, as well as transmembrane ion channels. Results showed that the updated Drude-2019 protein FF yields smaller overall root-mean-square differences of proteins as compared to the additive CHARMM36m and Drude-2013 FFs as well as similar or improved agreement with experimental NMR properties, allowing for long time scale simulation studies of proteins and more complex biomolecular systems in conjunction with the remainder of the Drude polarizable FF.