An improved nucleic acid parameter set for the GROMOS force field

Accurately Modeling RNA Stem-Loops in an Implicit Solvent Environment

Ribonucleic acid (RNA) molecules can adopt a variety of secondary and tertiary structures in solution, with stem-loops being one of the more common motifs. Here, we present a systematic analysis of 15 RNA stem-loop sequences simulated with molecular dynamics simulations in an implicit solvent environment. Analysis of RNA cluster ensembles showed that the stem-loop structures can generally adopt the A-form RNA in the stem region. Loop structures are more sensitive, and experimental structures could only be reproduced with modification of CH···O interactions in the force field, combined with an implicit solvent nonpolar correction to better model base stacking interactions. Accurately modeling RNA with current atomistic physics-based models remains challenging, but the RNA systems studied herein may provide a useful benchmark set for testing other RNA modeling methods in the future.

On the Validation of Protein Force Fields Based on Structural Criteria

Molecular dynamics simulations depend critically on the quality of the force field used to describe the interatomic interactions and the extent to which it has been validated for use in a specific application. Using a curated test set of 52 high-resolution structures, 39 derived from X-ray diffraction and 13 solved using NMR, we consider the extent to which different parameter sets of the GROMOS protein force field can be distinguished based on comparing a range of structural criteria, including the number of backbone hydrogen bonds, the number of native hydrogen bonds, polar and nonpolar solvent-accessible surface area, radius of gyration, the prevalence of secondary structure elements, J-coupling constants, nuclear Overhauser effect (NOE) intensities, positional root-mean-square deviations (RMSD), and the distribution of backbone ϕ and ψ dihedral angles. It is shown that while statistically significant differences between the average values of individual metrics could be detected, these were in general small. Furthermore, improvements in agreement in one metric were often offset by loss of agreement in another. The work establishes a framework and test set against which protein force fields can be validated. It also highlights the danger of inferring the relative quality of a given force field based on a small range of structural properties or small number of proteins.

Toward a general neural network force field for protein simulations: Refining the intramolecular interaction in protein

Molecular dynamics (MD) is an extremely powerful, highly effective, and widely used approach to understanding the nature of chemical processes in atomic details for proteins. The accuracy of results from MD simulations is highly dependent on force fields. Currently, molecular mechanical (MM) force fields are mainly utilized in MD simulations because of their low computational cost. Quantum mechanical (QM) calculation has high accuracy, but it is exceedingly time consuming for protein simulations. Machine learning (ML) provides the capability for generating accurate potential at the QM level without increasing much computational effort for specific systems that can be studied at the QM level. However, the construction of general machine learned force fields, needed for broad applications and large and complex systems, is still challenging. Here, general and transferable neural network (NN) force fields based on CHARMM force fields, named CHARMM-NN, are constructed for proteins by training NN models on 27 fragments partitioned from the residue-based systematic molecular fragmentation (rSMF) method. The NN for each fragment is based on atom types and uses new input features that are similar to MM inputs, including bonds, angles, dihedrals, and non-bonded terms, which enhance the compatibility of CHARMM-NN to MM MD and enable the implementation of CHARMM-NN force fields in different MD programs. While the main part of the energy of the protein is based on rSMF and NN, the nonbonded interactions between the fragments and with water are taken from the CHARMM force field through mechanical embedding. The validations of the method for dipeptides on geometric data, relative potential energies, and structural reorganization energies demonstrate that the CHARMM-NN local minima on the potential energy surface are very accurate approximations to QM, showing the success of CHARMM-NN for bonded interactions. However, the MD simulations on peptides and proteins indicate that more accurate methods to represent protein-water interactions in fragments and non-bonded interactions between fragments should be considered in the future improvement of CHARMM-NN, which can increase the accuracy of approximation beyond the current mechanical embedding QM/MM level.

Machine Learning Methods for Small Data Challenges in Molecular Science

Small data are often used in scientific and engineering research due to the presence of various constraints, such as time, cost, ethics, privacy, security, and technical limitations in data acquisition. However, big data have been the focus for the past decade, small data and their challenges have received little attention, even though they are technically more severe in machine learning (ML) and deep learning (DL) studies. Overall, the small data challenge is often compounded by issues, such as data diversity, imputation, noise, imbalance, and high-dimensionality. Fortunately, the current big data era is characterized by technological breakthroughs in ML, DL, and artificial intelligence (AI), which enable data-driven scientific discovery, and many advanced ML and DL technologies developed for big data have inadvertently provided solutions for small data problems. As a result, significant progress has been made in ML and DL for small data challenges in the past decade. In this review, we summarize and analyze several emerging potential solutions to small data challenges in molecular science, including chemical and biological sciences. We review both basic machine learning algorithms, such as linear regression, logistic regression (LR), k-nearest neighbor (KNN), support vector machine (SVM), kernel learning (KL), random forest (RF), and gradient boosting trees (GBT), and more advanced techniques, including artificial neural network (ANN), convolutional neural network (CNN), U-Net, graph neural network (GNN), Generative Adversarial Network (GAN), long short-term memory (LSTM), autoencoder, transformer, transfer learning, active learning, graph-based semi-supervised learning, combining deep learning with traditional machine learning, and physical model-based data augmentation. We also briefly discuss the latest advances in these methods. Finally, we conclude the survey with a discussion of promising trends in small data challenges in molecular science.

Extension of the CHARMM Classical Drude Polarizable Force Field to N- and O-Linked Glycopeptides and Glycoproteins

Molecular dynamic simulations are an effective tool to study complex molecular systems and are contingent upon the availability of an accurate and reliable molecular mechanics force field. The Drude polarizable force field, which allows for the explicit treatment of electronic polarization in a computationally efficient fashion, has been shown to reproduce experimental properties that were difficult or impossible to reproduce with the CHARMM additive force field, including peptide folding cooperativity, RNA hairpin structures, and DNA base flipping. Glycoproteins are essential components of glycoconjugate vaccines, antibodies, and many pharmaceutically important molecules, and an accurate polarizable force field that includes compatibility between the protein and carbohydrate aspect of the force field is essential to study these types of systems. In this work, we present an extension of the Drude polarizable force field to glycoproteins, including both N- and O-linked species. Parameter optimization focused on the dihedral terms using a reweighting protocol targeting NMR solution J-coupling data for model glycopeptides. Validation of the model include eight model glycopeptides and four glycoproteins with multiple N- and O-linked glycosylations. The new glycoprotein carbohydrate force field can be used in conjunction with the remainder of Drude polarizable force field through a variety of MD simulation programs including GROMACS, OPENMM, NAMD, and CHARMM and may be accessed through the Drude Prepper module in the CHARMM-GUI.

Molecular Evolution of the Pseudomonas aeruginosa DNA Gyrase gyrA Gene

DNA gyrase plays important roles in genome replication in various bacteria, including Pseudomonasaeruginosa. The gyrA gene encodes the gyrase subunit A protein (GyrA). Mutations in GyrA are associated with resistance to quinolone-based antibiotics. We performed a detailed molecular evolutionary analyses of the gyrA gene and associated resistance to the quinolone drug, ciprofloxacin, using bioinformatics techniques. We produced an evolutionary phylogenetic tree using the Bayesian Markov Chain Monte Carlo (MCMC) method. This tree indicated that a common ancestor of the gene was present over 760 years ago, and the offspring formed multiple clusters. Quinolone drug-resistance-associated amino-acid substitutions in GyrA, including T83I and D87N, emerged after the drug was used clinically. These substitutions appeared to be positive selection sites. The molecular affinity between ciprofloxacin and the GyrA protein containing T83I and/or D87N decreased significantly compared to that between the drug and GyrA protein, with no substitutions. The rate of evolution of the gene before quinolone drugs were first used in the clinic, in 1962, was significantly lower than that after the drug was used. These results suggest that the gyrA gene evolved to permit the bacterium to overcome quinolone treatment.

Understanding the Interactions between Triolein and Cosolvent Binary Mixtures Using Molecular Dynamics Simulations

Biodiesel is one of the emerging renewable sources of energy to replace fossil-fuel-based resources. It is produced by a transesterification reaction in which a triglyceride reacts with methanol in the presence of a catalyst. The reaction is slow because of the low solubility of methanol in triglycerides, which results in low concentrations of methanol available to react with triglyceride. To speed up the reaction, cosolvents are added to create a single phase which helps to improve the concentration of methanol in the triglyceride phase. In this study, molecular dynamics simulations are used to help understand the role of cosolvents in the solvation of triglyceride (triolein). Six binary mixtures of triolein/cosolvent were used to study the solvation of triolein at 298.15 K. Results of 100 ns simulations at constant temperature and pressure to simulate mixing experiments show that in the first 10 ns all the binary mixtures remain largely unmixed. However, for the cosolvents that are fully miscible with triolein, the partial densities across the simulation boxes show that the systems are fully mixed in the final 10 ns. Some solvents were found to interact strongly with the polar part of triolein, while others interacted with the aliphatic part. The radial distribution functions and clustering of the solvents around triolein were also used as indicators for solvation. The presence of cosolvents also influenced the conformation of triolein molecules. In the presence of solvents that solubilize it, triolein preferred a propeller conformation but took up a trident conformation when there is less or no solubilization. The results show that tetrahydrofuran is the best solvent at solubilizing triolein, followed by cyclopentyl methyl ether, diethyl ether, and hexane. With 1,4-dioxane, the solubility improves with an increase in temperature. The miscibility of a solvent in triolein is aided by its ability to interact with both the polar and nonpolar parts of triolein.

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.

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.

Multipolar Description of Atom-Atom Electrostatic Interaction Energies in Single/Double-Stranded DNAs

Molecular force field simulation is an effective method to explore the properties of DNA molecules in depth. Almost all current popular force fields calculate atom-atom electrostatic interaction energies for DNAs based on the atomic charge and dipole or quadrupole moments, without considering high-rank atomic multipole moments for more accurate electrostatics. Actually, the distribution of electrons around atomic nuclei is not spherically symmetric but is geometry dependent. In this work, a multipole expansion method that allows us to combine polarizability and anisotropy was applied. One single-stranded DNA and one double-stranded DNA were selected as pilot systems. Deoxynucleotides were cut out from pilot systems and capped by mimicking the original DNA environment. Atomic multipole moments were integrated instead of fixed-point charges to calculate atom-atom electrostatic energies to improve the accuracy of force fields for DNA simulations. Also, the applicability of modeling the behavior of both single-stranded and double-stranded DNAs was investigated. The calculation results indicated that the models can be transferred from pilot systems to test systems, which is of great significance for the development of future DNA force fields.

Molecular Dynamics and In Vitro Quantification of Safrole DNA Adducts Reveal DNA Adduct Persistence Due to Limited DNA Distortion Resulting in Inefficient Repair

The formation and repair of N²-(trans-isosafrol-3'-yl)-2'-deoxyguanosine (S-3'-N²-dG) DNA adduct derived from the spice and herbal alkenylbenzene constituent safrole were investigated. DNA adduct formation and repair were studied in vitro and using molecular dynamics (MD) simulations. DNA adduct formation was quantified using liquid chromatography-mass spectrometry (LCMS) in wild type and NER (nucleotide excision repair) deficient CHO cells and also in HepaRG cells and primary rat hepatocytes after different periods of repair following exposure to safrole or 1'-hydroxysafrole (1'-OH safrole). The slower repair of the DNA adducts found in NER deficient cells compared to that in CHO wild type cells indicates a role for NER in repair of S-3'-N²-dG DNA adducts. However, DNA repair in liver cell models appeared to be limited, with over 90% of the adducts remaining even after 24 or 48 h recovery. In our further studies, MD simulations indicated that S-3'-N²-dG adduct formation causes only subtle changes in the DNA structure, potentially explaining inefficient activation of NER. Inefficiency of NER mediated repair of S-3'-N²-dG adducts points at persistence and potential bioaccumulation of safrole DNA adducts upon daily dietary exposure.

Molecular modelling of sorption processes of a range of diverse small organic molecules in Leonardite humic acid

Soil organic matter (SOM) is abundant in the environment and plays an important role in several biogeochemical processes, including microbial activity, soil aggregation, plant growth and carbon storage. One of its key functions is the retention and release of various chemical compounds, primarily governed by the sorption process, which strongly affects the environmental fate of nutrients and pollutants. Sorption largely depends on the composition of SOM, as well as its structure, dynamics and the thermodynamic conditions. Although several approaches are available, experimental characterization of sorption mechanisms is not easy. Computational models for predicting sorption coefficients often require a wealth of experimental data for training and are only applicable to compounds and conditions related to the training dataset. Here, we use molecular dynamics (MD) simulations to study the sorption of a range of small organic compounds. As a model SOM system we use the standard Leonardite humic acid (LHA) sample, which physicochemical properties have recently been characterized computationally in detail. This model allowed us to estimate sorption propensities of the systems at two different hydration levels (water activities close to 0 and 1), showing a remarkable correlation with experimental data. Importantly, this molecular modelling approach based on perturbation free-energy calculations is rigorously derived from statistical thermodynamics and requires no experimental sorption data for training. It is therefore in principle applicable to any SOM model or thermodynamic condition. Moreover, the power of MD simulations to provide high-resolution insight into atomistic and molecular interactions was employed to explore how sorbate molecules associate with the LHA matrix and which contacts they form. The heteroatoms of both sorbate and sorbent play an important role and water molecules are identified as further key players in facilitating the sorption process.

HIGHLIGHTS

Modelling of the sorption processes in soil organic matter at atomistic level.Rigorous, physics-based approach applicable to a range of SOM systems and conditions.Remarkable level of matching with experimental data with additional insight into the molecular mechanism.Interactions between the sorbate and local environment strongly affects the sorption process.

Insight into the sequence-structure relationship of TLR cytoplasm's Toll/Interleukin-1 receptor domain towards understanding the conserved functionality of TLR 2 heterodimer in mammals

The signaling response of TLR2 to ligands has always been as a homodimer or in heterodimerization with TLR1/TLR6. The Toll/Interleukin-1 Receptor (TIR) domain of the TLR cytoplasmic region regulates the dimerization and interactions with adaptor molecules to build an active signaling complex. To understand the conservation of functionality of the TLR2-heterodimers between the distantly related species human(h) and mice(m), the pattern of TIR-TIR interaction in heterodimers has been studied through the sequence-structural point of view. Comparative analysis of primary sequence and structural pattern of TLRs(1/2/6) corroborates higher sequence homology between TLR1 and TLR6. Molecular docking analysis of TLR2-TLR1 and TLR2-TLR6 cytoplasmic dimers in both mouse and human have identified that for interaction the BB loop/near-BB loop residues of TLR2 are involved with the near-DD loop of TLR1 and DD loop residues of TLR6 within the TIR domains, which may cause to differential signaling. Molecular dynamics simulation of dimers for both human and mice species recognize stable interface between near-BB/BB loop region of TLR2 and discrete near-DD and DD loop region of TLR1 and TLR6 respectively. The observed dimerization pattern in both the species is further supported by Alanine scanning mutation study. However, Solvent Accessible Surface Area (SASA) of BB and DD loop regions of the cytoplasmic monomers and the heterodimers suggests that while TLR2 BB loop is actively associated as the dimer interface with its heterodimer partners in both the species, the DD loop acts as the active interfacing region in hTLR1 and mTLR6. Communicated by Ramaswamy H. Sarma.

Molecular Dynamics Simulations with NAMD2

X-ray diffraction crystallography is the primary technique to determine the three-dimensional structures of biomolecules. Although a robust method, X-ray crystallography is not able to access the dynamical behavior of macromolecules. To do so, we have to carry out molecular dynamics simulations taking as an initial system the three-dimensional structure obtained from experimental techniques or generated using homology modeling. In this chapter, we describe in detail a tutorial to carry out molecular dynamics simulations using the program NAMD2. We chose as a molecular system to simulate the structure of human cyclin-dependent kinase 2.

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.

NWChem: Past, present, and future

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

Molecular dynamics simulations of two double-helical hexamer fragments of iota-carrageenan in aqueous solution

The gelation of anionic carrageenans is known to occur through a coil-to-helix transition followed by further aggregation or association on which positive counterions play a significant role. In the present work, molecular dynamics (MD) simulations were performed on two double-helical iota-carrageenan hexamer fragments along with their sodium counterions using the Carbohydrate Solution Force Field (CSFF) in an aqueous (TIP4P) solution with the GROMACS molecular dynamics package. Results showed a counterion condensation between the two double helices and that the subsequent forces of interaction between them were predominantly attractive. By varying the distance separating the two double helices, the effect of distance on the counterion distribution and the forces of attraction was also investigated. In the presence of counterions, an increase in the forces of attraction was observed as the distance between the two double helices decreases which can be attributed to the greater counterion density between the two like-charged oligosaccharides.

Cellular levels and molecular dynamics simulations of estragole DNA adducts point at inefficient repair resulting from limited distortion of the double-stranded DNA helix

Estragole, naturally occurring in a variety of herbs and spices, can form DNA adducts after bioactivation. Estragole DNA adduct formation and repair was studied in in vitro liver cell models, and a molecular dynamics simulation was used to investigate the conformation dependent (in)efficiency of N²-(trans-isoestragol-3'-yl)-2'-deoxyguanosine (E-3'-N²-dG) DNA adduct repair. HepG2, HepaRG cells, primary rat hepatocytes and CHO cells (including CHO wild-type and three NER-deficient mutants) were exposed to 50 μM estragole or 1'-hydroxyestragole and DNA adduct formation was quantified by LC-MS immediately following exposure and after a period of repair. Results obtained from CHO cell lines indicated that NER plays a role in repair of E-3'-N²-dG adducts, however, with limited efficiency since in the CHO wt cells 80% DNA adducts remained upon 24 h repair. Inefficiency of DNA repair was also found in HepaRG cells and primary rat hepatocytes. Changes in DNA structure resulting from E-3'-N²-dG adduct formation were investigated by molecular dynamics simulations. Results from molecular dynamics simulations revealed that conformational changes in double-stranded DNA by E-3'-N²-dG adduct formation are small, providing a possible explanation for the restrained repair, which may require larger distortions in the DNA structure. NER-mediated enzymatic repair of E-3'-N²-dG DNA adducts upon exposure to estragole will be limited, providing opportunities for accumulation of damage upon repeated daily exposure. The inability of this enzymatic repair is likely due to a limited distortion of the DNA double-stranded helix resulting in inefficient activation of nucleotide excision repair.

Improved Modeling of Cation-π and Anion-Ring Interactions Using the Drude Polarizable Empirical Force Field for Proteins

Cation-π interactions are noncovalent interactions between a π-electron system and a positively charged ion that are regarded as a strong noncovalent interaction and are ubiquitous in biological systems. Similarly, though less studied, anion-ring interactions are present in proteins along with in-plane interactions of anions with aromatic rings. As these interactions are between a polarizing ion and a polarizable π system, the accuracy of the treatment of these interactions in molecular dynamics (MD) simulations using additive force fields (FFs) may be limited. In the present work, to allow for a better description of ion-π interactions in proteins in the Drude-2013 protein polarizable FF, we systematically optimized the parameters for these interactions targeting model compound quantum mechanical (QM) interaction energies with atom pair-specific Lennard-Jones parameters along with virtual particles as selected ring centroids introduced to target the QM interaction energies and geometries. Subsequently, MD simulations were performed on a series of protein structures where ion-π pairs occur to evaluate the optimized parameters in the context of the Drude-2013 FF. The resulting FF leads to a significant improvement in reproducing the ion-π pair distances observed in experimental protein structures, as well as a smaller root-mean-square differences and fluctuations of the overall protein structures from experimental structures. Accordingly, the optimized Drude-2013 protein polarizable FF is suggested for use in MD simulations of proteins where cation-π and anion-ring interactions are critical. © 2019 Wiley Periodicals, Inc.

Pairwise-additive and polarizable atomistic force fields for molecular dynamics simulations of proteins

Protein force fields have been undergoing continual development since the first complete parameter sets were introduced nearly four decades ago. The functional forms that underlie these models have many common elements for the treatment of bonded and nonbonded forces, which are reviewed here. The most widely used force fields to date use a fixed-charge convention in which electronic polarization effects are treated via a mean-field approximation during partial charge assignment. Despite success in modeling folded proteins over many years, the fixed-charge assumption has limitations that cannot necessarily be overcome within their potential energy equations. To overcome these limitations, several force fields have recently been derived that explicitly treat electronic polarization effects with straightforward extensions of the potential energy functions used by nonpolarizable force fields. Here, we review the history of the most popular nonpolarizable force fields (AMBER, CHARMM, OPLS, and GROMOS) as well as studies that have validated them and applied them to studies of protein folding and misfolding. Building upon these force fields are more recent polarizable interaction potentials, including fluctuating charge models, POSSIM, AMOEBA, and the classical Drude oscillator. These force fields differ in their implementations but all attempt to model electronic polarization in a computationally tractable manner. Despite their recent emergence in the field of protein folding, several studies have already applied these polarizable models to challenging problems in this domain, including the role of polarization in folding free energies and sequence-specific effects on the stability of α-helical structures.

Correcting electrostatic artifacts due to net-charge changes in the calculation of ligand binding free energies

Alchemically derived free energies are artifacted when the perturbed moiety has a nonzero net charge. The source of the artifacts lies in the effective treatment of the electrostatic interactions within and between the perturbed atoms and remaining (partial) charges in the simulated system. To treat the electrostatic interactions effectively, lattice-summation (LS) methods or cutoff schemes in combination with a reaction-field contribution are usually employed. Both methods render the charging component of the calculated free energies sensitive to essential parameters of the system like the cutoff radius or the box side lengths. Here, we discuss the results of three previously published studies of ligand binding. These studies presented estimates of binding free energies that were artifacted due to the charged nature of the ligands. We show that the size of the artifacts can be efficiently calculated and raw simulation data can be corrected. We compare the corrected results with experimental estimates and nonartifacted estimates from path-sampling methods. Although the employed correction scheme involves computationally demanding continuum-electrostatics calculations, we show that the correction estimate can be deduced from a small sample of configurations rather than from the entire ensemble. This observation makes the calculations of correction terms feasible for complex biological systems. To show the general applicability of the proposed procedure, we also present results where the correction scheme was used to correct independent free energies obtained from simulations employing a cutoff scheme or LS electrostatics. In this work, we give practical guidelines on how to apply the appropriate corrections easily.

Hamiltonian Reweighing To Refine Protein Backbone Dihedral Angle Parameters in the GROMOS Force Field

Molecular dynamics simulations of proteins depend critically on the underlying force field, which may be parameterized against experimental data or high-quality quantum calculations. Here, we develop search algorithms based on Monte Carlo and steepest descent calculations to optimize the backbone dihedral angle parameters from a single reference simulation. We apply these tools to improve the agreement between simulations of single, capped amino acids and experimentally determined J values and secondary structure propensities of these molecules. The parameters are further refined based on simulations of a set of seven proteins and finally validated in simulations on a large set of 52 protein structures. Improvements in the dihedral angle distributions are observed, and structural propensities of the proteins are reproduced very well. Overall, the GROMOS 54A8_bb parameter set forms an improvement to previous parameter sets, both for small molecules and for protein simulations.

Solution structure of macromolecules using small angle neutron scattering and molecular simulations

An introductory account of using molecular simulations to deduce solution structure of macromolecules using small angle neutron scattering data is presented for biologists. The presence of a liquid solution provides mobility to the molecules, making it difficult to pin down their structure. Here a simple introduction to molecular dynamics and Monte Carlo techniques is followed by a recipe to use the output of the simulations along with the scattering data in order to infer the structure of macromolecules when they are placed in a liquid solution. Some practical issues to be watched for are also highlighted.

Molecular Dynamics Simulations of Membrane Proteins: An Overview

Simulations of membrane proteins have been rising in popularity in the past decade. Advancements in technology and force fields made it possible to simulate behavior of membrane proteins. Membrane protein simulations can now be used as supporting evidence for experimental findings, for elucidating protein mechanisms, and validating protein crystal structures. Unrelated to experimental data, these simulations can also serve to investigate larger scale processes like protein sorting, protein-membrane interactions, and more. In this review, the history as well as the state-of-the-art methodologies in membrane protein simulations will be summarized. An emphasis will be put on how to set up the system and on the current models for the different components of the simulation system. An overview of the available tools for membrane protein simulation will be given, and current limitations and prospects will also be discussed.

AMOEBA Polarizable Atomic Multipole Force Field for Nucleic Acids

The AMOEBA polarizable atomic multipole force field for nucleic acids is presented. Valence and electrostatic parameters were determined from high-level quantum mechanical data, including structures, conformational energy, and electrostatic potentials, of nucleotide model compounds. Previously derived parameters for the phosphate group and nucleobases were incorporated. A total of over 35 μs of condensed-phase molecular dynamics simulations of DNA and RNA molecules in aqueous solution and crystal lattice were performed to validate and refine the force field. The solution and/or crystal structures of DNA B-form duplexes, RNA duplexes, and hairpins were captured with an average root-mean-squared deviation from NMR structures below or around 2.0 Å. Structural details, such as base pairing and stacking, sugar puckering, backbone and χ-torsion angles, groove geometries, and crystal packing interfaces, agreed well with NMR and/or X-ray. The interconversion between A- and B-form DNAs was observed in ethanol-water mixtures at 328 K. Crystal lattices of B- and Z-form DNA and A-form RNA were examined with simulations. For the RNA tetraloop, single strand tetramers, and HIV TAR with 29 residues, the simulated conformational states, 3 J-coupling, nuclear Overhauser effect, and residual dipolar coupling data were compared with NMR results. Starting from a totally unstacked/unfolding state, the rCAAU tetranucleotide was folded into A-form-like structures during ∼1 μs molecular dynamics simulations.

Molecular Modeling of Multidrug Properties of Resistance Nodulation Division (RND) Transporters

Efflux pumps of the resistance nodulation division (RND) superfamily are among the major contributors to intrinsic and acquired multidrug resistance in Gram-negative bacteria. Structural information on AcrAB-TolC and MexAB-OprM, major efflux pumps of Escherichia coli and Pseudomonas aeruginosa respectively, boosted intensive research aimed at understanding the molecular mechanisms ruling the active extrusion processes. In particular, several studies were devoted to the understanding of the determinants behind the extraordinary broad specificity of the RND transporters AcrB and MexB. In this chapter, we discuss the ever-growing role computational methods have been playing in deciphering key structural and dynamical features of these transporters and of their interaction with substrates and inhibitors. We further discuss and illustrate examples from our lab of how molecular docking, homology modeling, all-atom molecular dynamics simulations and in silico free energy estimations can all together give precious insights into the processes of recognition and extrusion of substrates, as well as on the possible inhibition strategies.

Ion-induced modification of the sucrose network and its impact on melting of freeze-dried liposomes. DSC and molecular dynamics study

Disaccharides play an important role in survival of anhydrobiotic organisms during extreme environmental conditions. A key protection feature is their capability to form the hydrogen bond (HB) network in a similar fashion as the one made by water. Since various ions also affect the HB network in completely hydrated systems, it is of a great interest to understand how they impact preservation when incorporated in a disaccharide network. To address this, we employ a combination of experimental and modeling techniques to study behavior of multilamellar 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) liposomes freeze-dried with sucrose in presence of NaCl or NaH₂PO₄·H₂O at various concentrations (0.01-1M). Differential scanning calorimetry (DSC) was employed in order to determine the cooperative unit size (CUS), the number of lipid molecules that constitute a domain of cooperative motion in the liposome, and the melting temperature (T_m). In the absence of salt CUS was estimated to be 122±12, whereas in the presence of NaCl CUS increases more (347±34 for c=1M) than for NaH₂PO₄·H₂O (193±26 for 1M). When it comes to T_m, the situation is reversed; NaCl induces increase by about 1K, while NaH₂PO₄·H₂O by about 10K. These findings clearly demonstrate how different interaction forces-hydrogen bonding, charge pairing, and van der Waals interactions between acyl chains-affect CUS and T_m. Their interplay and contribution of particular interaction was further analyzed with molecular dynamics (MD) simulations. This analysis demonstrated that the HB network of DMPC and sucrose is partially disrupted in the presence of NaCl ions, and even to a greater extent in the case of NaH₂PO₄·H₂O ions. Notably, H₂PO₄^- ions outcompete and replace the sucrose molecules at the DMPC surface, which in turn alters the nature of the DMPC-surrounding interactions, from a weaker HB-dominated to a stronger CP-dominated interaction network.

doGlycans-Tools for Preparing Carbohydrate Structures for Atomistic Simulations of Glycoproteins, Glycolipids, and Carbohydrate Polymers for GROMACS

Carbohydrates constitute a structurally and functionally diverse group of biological molecules and macromolecules. In cells they are involved in, e.g., energy storage, signaling, and cell–cell recognition. All of these phenomena take place in atomistic scales, thus atomistic simulation would be the method of choice to explore how carbohydrates function. However, the progress in the field is limited by the lack of appropriate tools for preparing carbohydrate structures and related topology files for the simulation models. Here we present tools that fill this gap. Applications where the tools discussed in this paper are particularly useful include, among others, the preparation of structures for glycolipids, nanocellulose, and glycans linked to glycoproteins. The molecular structures and simulation files generated by the tools are compatible with GROMACS.

Hydrogen bond strength in membrane proteins probed by time-resolved 1H-detected solid-state NMR and MD simulations

¹H-detected solid-state NMR in combination with ¹H/²D exchange steps allows for the direct identification of very strong hydrogen bonds in membrane proteins. On the example of the membrane-embedded potassium channel KcsA, we quantify the longevity of such very strong hydrogen bonds by combining time-resolved ¹H-detected solid-state NMR experiments and molecular dynamics simulations. In particular, we show that the carboxyl-side chain of the highly conserved residue Glu51 is involved in ultra-strong hydrogen bonds, which are fully-water-exposed and yet stable for weeks. The astonishing stability of these hydrogen bonds is important for the structural integrity of potassium channels, which we further corroborate by computational studies.

Polarizable Force Field for DNA Based on the Classical Drude Oscillator: II. Microsecond Molecular Dynamics Simulations of Duplex DNA

The structure and dynamics of DNA are governed by a sensitive balance between base stacking and pairing, hydration, and interactions with ions. Force-field models that include explicit representations of electronic polarization are capable of more accurately modeling the subtle details of these interactions versus commonly used additive force fields. In this work, we validate our recently refined polarizable force field for DNA based on the classical Drude oscillator model, in which electronic degrees of freedom are represented as negatively charged particles attached to their parent atoms via harmonic springs. The previous version of the force field, called Drude-2013, produced stable A- and B-DNA trajectories on the order of hundreds of nanoseconds, but deficiencies were identified that included weak base stacking ultimately leading to distortion of B-DNA duplexes and unstable Z-DNA. As a result of extensive refinement of base nonbonded terms and bonded parameters in the deoxyribofuranose sugar and phosphodiester backbone, we demonstrate that the new version of the Drude DNA force field is capable of simulating A- and B-forms of DNA on the microsecond time scale and the resulting conformational ensembles agree well with a broad set of experimental properties, including solution X-ray scattering profiles. In addition, simulations of Z-form duplex DNA in its crystal environment are stable on the order of 100 ns. The revised force field is to be called Drude-2017.

Polarizable Force Field for DNA Based on the Classical Drude Oscillator: I. Refinement Using Quantum Mechanical Base Stacking and Conformational Energetics

Empirical force fields seek to relate the configuration of a set of atoms to its energy, thus yielding the forces governing its dynamics, using classical physics rather than more expensive quantum mechanical calculations that are computationally intractable for large systems. Most force fields used to simulate biomolecular systems use fixed atomic partial charges, neglecting the influence of electronic polarization, instead making use of a mean-field approximation that may not be transferable across environments. Recent hardware and software developments make polarizable simulations feasible, and to this end, polarizable force fields represent the next generation of molecular dynamics simulation technology. In this work, we describe the refinement of a polarizable force field for DNA based on the classical Drude oscillator model by targeting quantum mechanical interaction energies and conformational energy profiles of model compounds necessary to build a complete DNA force field. The parametrization strategy employed in the present work seeks to correct weak base stacking in A- and B-DNA and the unwinding of Z-DNA observed in the previous version of the force field, called Drude-2013. Refinement of base nonbonded terms and reparametrization of dihedral terms in the glycosidic linkage, deoxyribofuranose rings, and important backbone torsions resulted in improved agreement with quantum mechanical potential energy surfaces. Notably, we expand on previous efforts by explicitly including Z-DNA conformational energetics in the refinement.

Designing synthetic RNA for delivery by nanoparticles

The rapid development of synthetic biology and nanobiotechnology has led to the construction of various synthetic RNA nanoparticles of different functionalities and potential applications. As they occur naturally, nucleic acids are an attractive construction material for biocompatible nanoscaffold and nanomachine design. In this review, we provide an overview of the types of RNA and nucleic acid's nanoparticle design, with the focus on relevant nanostructures utilized for gene-expression regulation in cellular models. Structural analysis and modeling is addressed along with the tools available for RNA structural prediction. The functionalization of RNA-based nanoparticles leading to prospective applications of such constructs in potential therapies is shown. The route from the nanoparticle design and modeling through synthesis and functionalization to cellular application is also described. For a better understanding of the fate of targeted RNA after delivery, an overview of RNA processing inside the cell is also provided.

Electronic absorption spectra of pyridine and nicotine in aqueous solution with a combined molecular dynamics and polarizable QM/MM approach

The electronic absorption spectra of pyridine and nicotine in aqueous solution have been computed using a multistep approach. The computational protocol consists in studying the solute solvation with accurate molecular dynamics simulations, characterizing the hydrogen bond interactions, and calculating electronic transitions for a series of configurations extracted from the molecular dynamics trajectories with a polarizable QM/MM scheme based on the fluctuating charge model. Molecular dynamics simulations and electronic transition calculations have been performed on both pyridine and nicotine. Furthermore, the contributions of solute vibrational effect on electronic absorption spectra have been taken into account in the so called vertical gradient approximation. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

Microscopic Characterization of Membrane Transporter Function by In Silico Modeling and Simulation

Membrane transporters mediate one of the most fundamental processes in biology. They are the main gatekeepers controlling active traffic of materials in a highly selective and regulated manner between different cellular compartments demarcated by biological membranes. At the heart of the mechanism of membrane transporters lie protein conformational changes of diverse forms and magnitudes, which closely mediate critical aspects of the transport process, most importantly the coordinated motions of remotely located gating elements and their tight coupling to chemical processes such as binding, unbinding and translocation of transported substrate and cotransported ions, ATP binding and hydrolysis, and other molecular events fueling uphill transport of the cargo. An increasing number of functional studies have established the active participation of lipids and other components of biological membranes in the function of transporters and other membrane proteins, often acting as major signaling and regulating elements. Understanding the mechanistic details of these molecular processes require methods that offer high spatial and temporal resolutions. Computational modeling and simulations technologies empowered by advanced sampling and free energy calculations have reached a sufficiently mature state to become an indispensable component of mechanistic studies of membrane transporters in their natural environment of the membrane. In this article, we provide an overview of a number of major computational protocols and techniques commonly used in membrane transporter modeling and simulation studies. The article also includes practical hints on effective use of these methods, critical perspectives on their strengths and weak points, and examples of their successful applications to membrane transporters, selected from the research performed in our own laboratory.

Assessing the Current State of Amber Force Field Modifications for DNA

The utility of molecular dynamics (MD) simulations to model biomolecular structure, dynamics, and interactions has witnessed enormous advances in recent years due to the availability of optimized MD software and access to significant computational power, including GPU multicore computing engines and other specialized hardware. This has led researchers to routinely extend conformational sampling times to the microsecond level and beyond. The extended sampling time has allowed the community not only to converge conformational ensembles through complete sampling but also to discover deficiencies and overcome problems with the force fields. Accuracy of the force fields is a key component, along with sampling, toward being able to generate accurate and stable structures of biopolymers. The Amber force field for nucleic acids has been used extensively since the 1990s, and multiple artifacts have been discovered, corrected, and reassessed by different research groups. We present a direct comparison of two of the most recent and state-of-the-art Amber force field modifications, bsc1 and OL15, that focus on accurate modeling of double-stranded DNA. After extensive MD simulations with five test cases and two different water models, we conclude that both modifications are a remarkable improvement over the previous bsc0 force field. Both force field modifications show better agreement when compared to experimental structures. To ensure convergence, the Drew–Dickerson dodecamer (DDD) system was simulated using 100 independent MD simulations, each extended to at least 10 μs, and the independent MD simulations were concatenated into a single 1 ms long trajectory for each combination of force field and water model. This is significantly beyond the time scale needed to converge the conformational ensemble of the internal portions of a DNA helix absent internal base pair opening. Considering all of the simulations discussed in the current work, the MD simulations performed to assess and validate the current force fields and water models aggregate over 14 ms of simulation time. The results suggest that both the bsc1 and OL15 force fields render average structures that deviate significantly less than 1 Å from the average experimental structures. This can be compared to similar but less exhaustive simulations with the CHARMM 36 force field that aggregate to the ∼90 μs time scale and also perform well but do not produce structures as close to the DDD NMR average structures (with root-mean-square deviations of 1.3 Å) as the newer Amber force fields. On the basis of these analyses, any future research involving double-stranded DNA simulations using the Amber force fields should employ the bsc1 or OL15 modification.

Assessing protein conformational sampling and structural stability via de novo design and molecular dynamics simulations

Molecular dynamics and de novo techniques, associated to quality parameter sets, have excelled at determining the structure of small proteins with high accuracy. To achieve a detailed description of protein conformations, these methods must critically assess the thermodynamic features of the molecular ensembles. Here, a comparison of the conformational ensemble generated by molecular dynamics and de novo techniques were carried out for six Top7-based proteins carrying gp41 HIV-1 epitopes. The native Top7, a highly stable computationally designed protein, was used as benchmark. Structural stability, flexibility, and secondary structure content were assessed. The consistency of the latter was compared to experimental circular dichroism spectra for all proteins. While both methods are capable to identify the stable from unstable chimeric proteins, the sampled conformational space and flexibility differ significantly in both methods. Molecular dynamics simulations seem to better describe secondary structure content and identify regions responsible for conformational instability. The de novo method, as implemented in Rosetta-a prime tool for protein design, overestimates secondary structure content. On the other hand, its empirical energy function is capable to predict the threshold for protein stability.

An Empirical Polarizable Force Field Based on the Classical Drude Oscillator Model: Development History and Recent Applications

Molecular mechanics force fields that explicitly account for induced polarization represent the next generation of physical models for molecular dynamics simulations. Several methods exist for modeling induced polarization, and here we review the classical Drude oscillator model, in which electronic degrees of freedom are modeled by charged particles attached to the nuclei of their core atoms by harmonic springs. We describe the latest developments in Drude force field parametrization and application, primarily in the last 15 years. Emphasis is placed on the Drude-2013 polarizable force field for proteins, DNA, lipids, and carbohydrates. We discuss its parametrization protocol, development history, and recent simulations of biologically interesting systems, highlighting specific studies in which induced polarization plays a critical role in reproducing experimental observables and understanding physical behavior. As the Drude oscillator model is computationally tractable and available in a wide range of simulation packages, it is anticipated that use of these more complex physical models will lead to new and important discoveries of the physical forces driving a range of chemical and biological phenomena.