Multilevel summation method for electrostatic force evaluation

Functional Characterization of a CruP-Like Isomerase in Dunaliella

Dunaliella bardawil is a marine unicellular green algal that produces large amounts of β-carotene and is a model organism for studying the carotenoid synthesis pathway. However, there are still many mysteries about the enzymes of the D. bardawil lycopene synthesis pathway that have not been revealed. Here, we have identified a CruP-like lycopene isomerase, named DbLyISO, and successfully cloned its gene from D. bardawil. DbLyISO showed a high homology with CruPs. We constructed a 3D model of DbLyISO and performed molecular docking with lycopene, as well as molecular dynamics testing, to identify the functional characteristics of DbLyISO. Functional activity of DbLyISO was also performed by overexpressing gene in both E. coli and D. bardawil. Results revealed that DbLyISO acted at the C-5 and C-13 positions of lycopene, catalyzing its cis-trans isomerization to produce a more stable trans structure. These results provide new ideas for the development of a carotenoid series from engineered bacteria, algae, and plants.

Deconstructing Electrostatics of Functionalized Metal Nanoparticles from Molecular Dynamics Simulations

Gold nanoparticles (NPs) with different surface functionalizations can selectively interact with specific proteins, allowing a wide range of possible applications in biotechnology and biomedicine. To prevent their tendency to aggregate and to modulate their interaction with charged biomolecules or substrates (e.g., for biosensing applications), they can be functionalized with charged groups, introducing a mutual interaction which can be modulated by changing the ionic strength of the solvent. In silico modeling of these systems is often addressed with low-resolution models, which must account for these effects in the, often implicit, solvent representation. Here, we present a systematic conformational dynamic characterization of ligand-coated gold nanoparticles with different sizes, charges, and functionalizations by means of atomistic molecular dynamics simulations. Based on these, we deconstruct their electrostatic properties and propose a general representation of their average-long-range interactions extendable to different sizes, charges, and ionic strengths. This study clarifies in detail the role of the different features of the NP (charge, size, structure) and of the ionic strength in determining the details of the interparticle interaction and represents the first step toward a general strategy for the parametrization of NP coarse-grained models able to account for varying ionic strengths.

ANKH: A Generalized O(N) Interpolated Ewald Strategy for Molecular Dynamics Simulations

To evaluate electrostatics interactions, molecular dynamics (MD) simulations rely on Particle Mesh Ewald (PME), an O(Nlog(N)) algorithm that uses Fast Fourier Transforms (FFTs) or, alternatively, on O(N) Fast Multipole Methods (FMM) approaches. However, the FFTs low scalability remains a strong bottleneck for large-scale PME simulations on supercomputers. On the opposite, FFT-free FMM techniques are able to deal efficiently with such systems but they fail to reach PME performances for small- to medium-size systems, limiting their real-life applicability. We propose ANKH, a strategy grounded on interpolated Ewald summations and designed to remain efficient/scalable for any size of systems. The method is generalized for distributed point multipoles, and so for induced dipoles, which makes it suitable for high performance simulations using new generation polarizable force fields toward exascale computing.

Atomistic Modeling of Jet Formation in Charged Droplets

The first atomistic simulations that reveal the mechanism of Rayleigh fission are presented. It is demonstrated that simple ion or macroion ejection takes place through droplet deformation from a spherical into a distinct "tear" shape that contains a conical protrusion. We assert that the latter state is a free-energy minimum along an order parameter that measures the degree of droplet asphericity. The charged droplet's long-time evolution proceeds by alternating between the two minima above and below the critical value that are reached through solvent evaporation and ion ejection, respectively. For the first time, this mechanism allows one to explain the nature of the progeny droplets and the percentage of charge lost during fission. The cone half angle is estimated and found to be in good agreement with the value predicted from the solution of the electrostatic equation for the dielectric liquid. It is found that the conical deformation is independent of the effect of electrohydrodynamic forces reported in experiments. Contrary to the experimental observations of two diametrically opposite jets for droplets suspended in the electric field, we find that a single jet is formed at the Rayleigh limit. The study provides insight into the mechanism of capture of a macroion in jets appearing in electrospray ionization mass spectrometry (ESI-MS) experiments and may explain the tolerance of the ESI-MS spectrum to salt contamination of the sample.

Review of Electrostatic Force Calculation Methods and Their Acceleration in Molecular Dynamics Packages Using Graphics Processors

Molecular dynamics (MD) simulations probe the conformational repertoire of macromolecular systems using Newtonian dynamic equations. The time scales of MD simulations allow the exploration of biologically relevant phenomena and can elucidate spatial and temporal properties of the building blocks of life, such as deoxyribonucleic acid (DNA) and protein, across microsecond (μs) time scales using femtosecond (fs) time steps. A principal bottleneck toward extending MD calculations to larger time scales is the long-range electrostatic force measuring component of the naive nonbonded force computation algorithm, which scales with a complexity of (N, number of atoms). In this review, we present various methods to determine electrostatic interactions in often-used open-source MD packages as well as the implementation details that facilitate acceleration of the electrostatic interaction calculation.

Accelerators for Classical Molecular Dynamics Simulations of Biomolecules

Atomistic Molecular Dynamics (MD) simulations provide researchers the ability to model biomolecular structures such as proteins and their interactions with drug-like small molecules with greater spatiotemporal resolution than is otherwise possible using experimental methods. MD simulations are notoriously expensive computational endeavors that have traditionally required massive investment in specialized hardware to access biologically relevant spatiotemporal scales. Our goal is to summarize the fundamental algorithms that are employed in the literature to then highlight the challenges that have affected accelerator implementations in practice. We consider three broad categories of accelerators: Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs), and Application Specific Integrated Circuits (ASICs). These categories are comparatively studied to facilitate discussion of their relative trade-offs and to gain context for the current state of the art. We conclude by providing insights into the potential of emerging hardware platforms and algorithms for MD.

Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.

Molecular Modeling is an Enabling Approach to Complement and Enhance Channelopathy Research

Hundreds of human membrane proteins form channels that transport necessary ions and compounds, including drugs and metabolites, yet details of their normal function or how function is altered by genetic variants to cause diseases are often unknown. Without this knowledge, researchers are less equipped to develop approaches to diagnose and treat channelopathies. High-resolution computational approaches such as molecular modeling enable researchers to investigate channelopathy protein function, facilitate detailed hypothesis generation, and produce data that is difficult to gather experimentally. Molecular modeling can be tailored to each physiologic context that a protein may act within, some of which may currently be difficult or impossible to assay experimentally. Because many genomic variants are observed in channelopathy proteins from high-throughput sequencing studies, methods with mechanistic value are needed to interpret their effects. The eminent field of structural bioinformatics integrates techniques from multiple disciplines including molecular modeling, computational chemistry, biophysics, and biochemistry, to develop mechanistic hypotheses and enhance the information available for understanding function. Molecular modeling and simulation access 3D and time-dependent information, not currently predictable from sequence. Thus, molecular modeling is valuable for increasing the resolution with which the natural function of protein channels can be investigated, and for interpreting how genomic variants alter them to produce physiologic changes that manifest as channelopathies. © 2022 American Physiological Society. Compr Physiol 12:3141-3166, 2022.

Free energy landscape of RNA binding dynamics in start codon recognition by eukaryotic ribosomal pre-initiation complex

Specific interaction between the start codon, 5'-AUG-3', and the anticodon, 5'-CAU-3', ensures accurate initiation of translation. Recent studies show that several near-cognate start codons (e.g. GUG and CUG) can play a role in initiating translation in eukaryotes. However, the mechanism allowing initiation through mismatched base-pairs at the ribosomal decoding site is still unclear at an atomic level. In this work, we propose an extended simulation-based method to evaluate free energy profiles, through computing the distance between each base-pair of the triplet interactions involved in recognition of start codons in eukaryotic translation pre-initiation complex. Our method provides not only the free energy penalty for mismatched start codons relative to the AUG start codon, but also the preferred pathways of transitions between bound and unbound states, which has not been described by previous studies. To verify the method, the binding dynamics of cognate (AUG) and near-cognate start codons (CUG and GUG) were simulated. Evaluated free energy profiles agree with experimentally observed changes in initiation frequencies from respective codons. This work proposes for the first time how a G:U mismatch at the first position of codon (GUG)-anticodon base-pairs destabilizes the accommodation in the initiating eukaryotic ribosome and how initiation at a CUG codon is nearly as strong as, or sometimes stronger than, that at a GUG codon. Our method is expected to be applied to study the affinity changes for various mismatched base-pairs.

Multilevel summation for periodic electrostatics using B-splines

Fast methods for calculating two-body interactions have many applications, and for molecular science and cosmology, it is common to employ periodic boundary conditions. However, for the 1/r potential, the energy and forces are ill-defined. Adopted here is the model given by the classic Ewald sum. For the fast calculation of two-body forces, the most celebrated method is the fast multipole method and its tree-code predecessor. However, molecular simulations typically employ mesh-based approximations and the fast Fourier transform. Both types of methods have significant drawbacks, which, in most respects, are overcome by the less well-known multilevel summation method (MSM). Presented here is a realization of the MSM, which can be regarded as a multilevel extension of the (smoothed) particle mesh Ewald (PME) method, but with the Ewald softening replaced by one having a finite range. The two-level (single-grid) version of MSM requires fewer tuning parameters than PME and is marginally faster. Additionally, higher-level versions of MSM scale well to large numbers of processors, whereas PME and other two-level methods do not. Although higher-level versions of MSM are less efficient on a single processor than the two-level version, evidence suggests that they are more efficient than other methods that scale well, such as the fast multipole method and tree codes.

Midtown splines: An optimal charge assignment for electrostatics calculations

Transferring particle charges to and from a grid plays a central role in the particle-mesh algorithms widely used to evaluate the electrostatic energy in molecular dynamics (MD) simulations. The computational cost of this transfer process represents a substantial part of the overall time required for simulation and is primarily determined by the size of the support (the set of grid nodes at which the transfer function is evaluated). The accuracy of the resulting approximation depends on the form of the transfer function, of which several have been proposed, as well as the size and shape of its support. Here, we show how to derive the transfer function that yields maximal asymptotic accuracy for a given support in the limit of fine grid resolution, finding that all such functions are splines, and we determine these functions (which we refer to as midtown splines) for a variety of choices of support to find optimally efficient transfer functions at accuracy levels relevant to MD simulations. We describe midtown splines that achieve fourth- and sixth-order accuracy in the grid spacing while requiring a support size of 32 and 88 grid nodes, respectively, compared to the 64 and 216 nodes required by the most widely used transfer functions (B-splines). At accuracy levels typically used in MD simulations, the use of midtown splines thus cuts the time required for charge spreading by roughly a factor of two.

Assembly of a patchy protein into variable 2D lattices via tunable multiscale interactions

Self-assembly of molecular building blocks into higher-order structures is exploited in living systems to create functional complexity and represents a powerful strategy for constructing new materials. As nanoscale building blocks, proteins offer unique advantages, including monodispersity and atomically tunable interactions. Yet, control of protein self-assembly has been limited compared to inorganic or polymeric nanoparticles, which lack such attributes. Here, we report modular self-assembly of an engineered protein into four physicochemically distinct, precisely patterned 2D crystals via control of four classes of interactions spanning Ångström to several-nanometer length scales. We relate the resulting structures to the underlying free-energy landscape by combining in-situ atomic force microscopy observations of assembly with thermodynamic analyses of protein-protein and -surface interactions. Our results demonstrate rich phase behavior obtainable from a single, highly patchy protein when interactions acting over multiple length scales are exploited and predict unusual bulk-scale properties for protein-based materials that ensue from such control.

As nanoscale building blocks, proteins offer unique advantages, including monodispersity and atomically tunable interactions, but their self-assembly is limited compared to inorganic or polymeric nanoparticles. Here, the authors show modular self-assembly of an engineered protein into four physicochemically distinct patterned 2D crystals via control of four classes of interactions.

Scalable molecular dynamics on CPU and GPU architectures with NAMD

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Fast multipole method for three-dimensional systems with periodic boundary condition in two directions

We derived a new expression for the electrostatic interaction of three-dimensional charge-neutral systems with two-dimensional periodic boundary conditions (slab geometry) using a fast multipole method (FMM). Contributions from all the image cells are expressed as a sum of real and reciprocal space terms, and a self-interaction term. The reciprocal space contribution consists of two parts: zero and nonzero terms of the absolute value of the reciprocal lattice vector. To test the new expressions, electrostatic interactions were calculated for a randomly placed charge distribution in a cubic box and liquid water produced by molecular dynamics calculation. The accuracy could be controlled by the degree of expansion of the FMM. In the present expression, the computational complexity of the electrostatic interaction of N-particle systems is order N, which is superior to that of the conventional two-dimensional periodic Ewald method for a slab geometry and the particle mesh Ewald method with a large empty space at an interface of the unit cell. © 2020 Wiley Periodicals, Inc.

A treecode based on barycentric Hermite interpolation for electrostatic particle interactions

A particle-cluster treecode based on barycentric Hermite interpolation is presented for fast summation of electrostatic particle interactions in 3D. The interpolation nodes are Chebyshev points of the 2nd kind in each cluster. It is noted that barycentric Hermite interpolation is scale-invariant in a certain sense that promotes the treecode’s efficiency. Numerical results for the Coulomb and screened Coulomb potentials show that the treecode run time scales like O(N log N), where N is the number of particles in the system. The advantage of the barycentric Hermite treecode is demonstrated in comparison with treecodes based on Taylor approximation and barycentric Lagrange interpolation.

Periodic Coulomb Tree Method: An Alternative to Parallel Particle Mesh Ewald

Particle mesh Ewald (PME) is generally the method of choice for handling electrostatics in simulations with periodic boundary conditions. The excellent efficiency of PME on low processor counts is largely due to the use of the fast Fourier transform (FFT). However, due to the FFT's high communication cost, PME scales poorly in parallel. We develop a periodic Coulomb tree (PCT) method for electrostatic interactions in periodic boundary conditions as an alternative to PME in parallel simulations. We verify the accuracy of PCT by comparison of structural and dynamical properties of three different systems obtained via MD simulations using PME and PCT and provide parallel timing comparisons of the two methods on up to 1024 cores.

Structure and stimuli-responsiveness of all-DNA dendrimers: theory and experiment

We present a comprehensive theoretical and experimental study of the solution phase properties of a DNA-based family of nanoparticles - dendrimer-like DNA molecules (DL-DNA). These charged DNA dendrimers are novel macromolecular aggregates, which hold high promise in targeted self-assembly of soft matter systems in the bulk and at interfaces. To describe the behaviour of this family of dendrimers (with generations ranging from G1 to G7), we use a theoretical model in which base-pairs of a single DL-DNA molecule are modeled by charged monomers, whose interactions are chosen to mimic the equilibrium properties of DNA correctly. Experimental results on the sizes and conformations of DL-DNA are based on static and dynamic light scattering; and molecular dynamics simulations are employed to model the equilibrium properties of DL-DNA, which compare favorably to the findings from experiments while at the same time providing a host of additional information and insight into the molecular structure of the nanostructures. We also examine the salt-responsiveness of these macromolecules, finding that despite the strong screening of electrostatic interactions brought about by the added salt, the macromolecules shrink only slightly, their size robustness stemming from the high bending rigidity of the DNA-segments. The study of these charged dendrimer systems is an important field of research in the area of soft matter due to their potential role for various interdisciplinary applications, ranging from molecular cages and carriers for drug delivery in a living organism to the development of dendrimer- and dendron-based ultra-thin films in the area of nanotechnology. These findings are essential to determine if DL-DNA is a viable candidate for the experimental realization of cluster crystals in the bulk, a novel form of solid with multiple site occupancy.

Nonproductive Binding Modes as a Prominent Feature of Aβ40 Fiber Elongation: Insights from Molecular Dynamics Simulation

The formation of amyloid fibers has been implicated in a number of neurodegenerative diseases. The growth of amyloid fibers is strongly thermodynamically favorable, but kinetic traps exist where the incoming monomer binds in an incompatible conformation that blocks further elongation. Unfortunately, this process is difficult to follow experimentally at the atomic level. It is also too complex to simulate in full detail and to date has been explored either through coarse-grained simulations, which may miss many important interactions, or full atomic simulations, in which the incoming peptide is constrained to be near the ideal fiber geometry. Here we use an alternate approach starting from a docked complex in which the monomer is from an experimental NMR structure of one of the major conformations in the unbound ensemble, a largely unstructured peptide with the central hydrophobic region in a 3₁₀ helix. A 1000 ns full atomic simulation in explicit solvent shows the formation of a metastable intermediate by sequential, concerted movements of both the fiber and the monomer. A Markov state model shows that the unfolded monomer is trapped at the end of the fiber in a set of interconverting antiparallel β-hairpin conformations. The simulation here may serve as a model for the binding of other non-β-sheet conformations to amyloid fibers.

Incremental update of electrostatic interactions in adaptively restrained particle simulations

The computation of long-range potentials is one of the demanding tasks in Molecular Dynamics. During the last decades, an inventive panoply of methods was developed to reduce the CPU time of this task. In this work, we propose a fast method dedicated to the computation of the electrostatic potential in adaptively restrained systems. We exploit the fact that, in such systems, only some particles are allowed to move at each timestep. We developed an incremental algorithm derived from a multigrid-based alternative to traditional Fourier-based methods. Our algorithm was implemented inside LAMMPS, a popular molecular dynamics simulation package. We evaluated the method on different systems. We showed that the new algorithm's computational complexity scales with the number of active particles in the simulated system, and is able to outperform the well-established Particle Particle Particle Mesh (P3M) for adaptively restrained simulations. © 2018 Wiley Periodicals, Inc.

Computer simulations of the diffusion of Na+ and Cl- ions across POPC lipid bilayer membranes

We have carried out molecular dynamics simulations using NAMD to study the diffusivity of Na and Cl ions across a POPC lipid bilayer membrane. We show that an imbalance of positively and negatively charged ions on either side of the membrane leads to the diffusion of ions and water molecules. We considered the cases of both weak and very strong charge imbalance across the membrane. The diffusion coefficients of the ions have been determined from the mean square displacements of the particles as a function of time. We find that for strong electrochemical gradients, both the Na and Cl ions diffuse rapidly through pores in the membrane with diffusion coefficients up to ten times larger than in water. Rather surprisingly, we found that although the Na ions are the first to begin the permeation process due to the lower potential barrier that they experience compared to the Cl ions, the latter complete the permeation across the barrier more quickly due to their faster diffusion rates.

Mesh-free hierarchical clustering methods for fast evaluation of electrostatic interactions of point multipoles

Electrostatic interactions involving point multipoles are being increasingly implemented to achieve higher accuracy in molecular simulations. A major drawback of multipolar electrostatics is the increased computational cost. Here we develop and compare two Cartesian tree algorithms which employ Taylor approximations and hierarchical clustering to speed up the evaluation of point multipole interactions. We present results from applying the algorithms to compute the free space Coulomb potential and forces of different sets of interacting point multipoles with different densities. The methods achieve high accuracy and speedup of more than an order of magnitude over direct sum calculations and scale well in parallel.

Selective antibody activation through protease-activated pro-antibodies that mask binding sites with inhibitory domains

Systemic injection of therapeutic antibodies may cause serious adverse effects due to on-target toxicity to the antigens expressed in normal tissues. To improve the targeting selectivity to the region of disease sites, we developed protease-activated pro-antibodies by masking the binding sites of antibodies with inhibitory domains that can be removed by proteases that are highly expressed at the disease sites. The latency-associated peptide (LAP), C2b or CBa of complement factor 2/B were linked, through a substrate peptide of matrix metalloproteinase-2 (MMP-2), to an anti-epidermal growth factor receptor (EGFR) antibody and an anti-tumor necrosis factor-α (TNF-α) antibody. Results showed that all the inhibitory domains could be removed by MMP-2 to restore the binding activities of the antibodies. LAP substantially reduced (53.8%) the binding activity of the anti-EGFR antibody on EGFR-expressing cells, whereas C2b and CBa were ineffective (21% and 9.3% reduction, respectively). Similarly, LAP also blocked 53.9% of the binding activity of the anti-TNF-α antibody. Finally, molecular dynamic simulation showed that the masking efficiency of LAP, C2b and CBa was 33.7%, 10.3% and −5.4%, respectively, over the binding sites of the antibodies. This strategy may aid in designing new protease-activated pro-antibodies that attain high therapeutic potency yet reduced systemic on-target toxicity.

The Water Permeability and Pore Entrance Structure of Aquaporin-4 Depend on Lipid Bilayer Thickness

Aquaporin-4 (AQP4), the primary water channel in glial cells of the mammalian brain, plays a critical role in water transport in the central nervous system. Previous experiments have shown that the water permeability of AQP4 depends on the cholesterol content in the lipid bilayer, but it was not clear whether changes in permeability were due to direct cholesterol-AQP4 interactions or to indirect effects caused by cholesterol-induced changes in bilayer elasticity or bilayer thickness. To determine the effects resulting only from bilayer thickness, here we use a combination of experiments and simulations to analyze AQP4 in cholesterol-free phospholipid bilayers with similar elastic properties but different hydrocarbon core thicknesses previously determined by x-ray diffraction. The channel (unit) water permeabilities of AQP4 measured by osmotic-gradient experiments were 3.5 ± 0.2 × 10(-13) cm(3)/s (mean ± SE), 3.0 ± 0.3 × 10(-13) cm(3)/s, 2.5 ± 0.2 × 10(-13) cm(3)/s, and 0.9 ± 0.1 × 10(-13) cm(3)/s in bilayers containing (C22:1)(C22:1)PC, (C20:1)(C20:1)PC, (C16:0)(C18:1)PC, and (C13:0)(C13:0)PC, respectively. Channel permeabilities obtained by molecular dynamics (MD) simulations were 3.3 ± 0.1 × 10(-13) cm(3)/s and 2.5 ± 0.1 × 10(-13) cm(3)/s in (C22:1)(C22:1)PC and (C14:0)(C14:0)PC bilayers, respectively. Both the osmotic-gradient and MD-simulation results indicated that AQP4 channel permeability decreased with decreasing bilayer hydrocarbon thickness. The MD simulations also suggested structural modifications in AQP4 in response to changes in bilayer thickness. Although the simulations showed no appreciable changes to the radius of the pore located in the hydrocarbon region of the bilayers, the simulations indicated that there were changes in both pore length and α-helix organization near the cytoplasmic vestibule of the channel. These structural changes, caused by mismatch between the hydrophobic length of AQP4 and the bilayer hydrocarbon thickness, could explain the observed differences in water permeability with changes in bilayer thickness.

Simulative and Experimental Characterization of a pH-Dependent Clamp-like DNA Triple-Helix Nanoswitch

Here we couple experimental and simulative techniques to characterize the structural/dynamical behavior of a pH-triggered switching mechanism based on the formation of a parallel DNA triple helix. Fluorescent data demonstrate the ability of this structure to reversibly switch between two states upon pH changes. Two accelerated, half microsecond, MD simulations of the system having protonated or unprotonated cytosines, mimicking the pH 5.0 and 8.0 conditions, highlight the importance of the Hoogsteen interactions in stabilizing the system, finely depicting the time-dependent disruption of the hydrogen bond network. Urea-unfolding experiments and MM/GBSA calculations converge in indicating a stabilization energy at pH 5.0, 2-fold higher than that observed at pH 8.0. These results validate the pH-controlled behavior of the designed structure and suggest that simulative approaches can be successfully coupled with experimental data to characterize responsive DNA-based nanodevices.

TopoGromacs: Automated Topology Conversion from CHARMM to GROMACS within VMD

Molecular dynamics (MD) simulation engines use a variety of different approaches for modeling molecular systems with force fields that govern their dynamics and describe their topology. These different approaches introduce incompatibilities between engines, and previously published software bridges the gaps between many popular MD packages, such as between CHARMM and AMBER or GROMACS and LAMMPS. While there are many structure building tools available that generate topologies and structures in CHARMM format, only recently have mechanisms been developed to convert their results into GROMACS input. We present an approach to convert CHARMM-formatted topology and parameters into a format suitable for simulation with GROMACS by expanding the functionality of TopoTools, a plugin integrated within the widely used molecular visualization and analysis software VMD. The conversion process was diligently tested on a comprehensive set of biological molecules in vacuo. The resulting comparison between energy terms shows that the translation performed was lossless as the energies were unchanged for identical starting configurations. By applying the conversion process to conventional benchmark systems that mimic typical modestly sized MD systems, we explore the effect of the implementation choices made in CHARMM, NAMD, and GROMACS. The newly available automatic conversion capability breaks down barriers between simulation tools and user communities and allows users to easily compare simulation programs and leverage their unique features without the tedium of constructing a topology twice.

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation method (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle-mesh Ewald method falls short.

Multiscale method for modeling binding phenomena involving large objects: application to kinesin motor domains motion along microtubules

Many biological phenomena involve the binding of proteins to a large object. Because the electrostatic forces that guide binding act over large distances, truncating the size of the system to facilitate computational modeling frequently yields inaccurate results. Our multiscale approach implements a computational focusing method that permits computation of large systems without truncating the electrostatic potential and achieves the high resolution required for modeling macromolecular interactions, all while keeping the computational time reasonable. We tested our approach on the motility of various kinesin motor domains. We found that electrostatics help guide kinesins as they walk: N-kinesins towards the plus-end, and C-kinesins towards the minus-end of microtubules. Our methodology enables computation in similar, large systems including protein binding to DNA, viruses, and membranes.