Short-time Molecular Dynamics Simulations Research Articles

Independent Nontargeted Parallel Cascade Selection Molecular Dynamics (Ino-PaCS-MD) to Enhance the Conformational Sampling of Proteins.

Biological functions are related to long-time protein dynamics (rare events) that are induced over microseconds. Such protein dynamics can be investigated using molecular dynamics (MD) simulations. However, the detection of rare events remains challenging using conventional MD (cMD) since the accessible timescales of cMD are shorter than those of the biological functions. Recently, the parallel cascade selection MD (PaCS-MD) has been proposed to detect such rare events, wherein transition paths are generated between a given reactant and product. As an extension, the nontargeted PaCS-MD (nt-PaCS-MD) has been proposed to predict the transition paths without requiring reference to any product. Thus, as a further extension, we herein propose independent nt-PaCS-MD, namely, Ino-PaCS-MD, wherein multiple walkers are launched from a set of different starting configurations. Each walker repeats a cycle of restarting short-time MD simulations from configurations with high potentials for making transitions to neighboring metastable states. To further enhance the sampling ability, Ino-PaCS-MD temporarily stops the conformational search and periodically resets the starting configurations so that they are uniformly distributed in a conformational subspace, thereby preventing a given protein from being trapped in one of the metastable states. As a demonstration, Ino-PaCS-MD successfully detects rare events of a maltose-binding protein as open-close transitions with a nanosecond-order simulation time, although a microsecond-order cMD simulation failed to detect these rare events, showing the high sampling efficiency of Ino-PaCS-MD.

Computational design of penicillin acylase variants with improved kinetic selectivity for the enzymatic synthesis of cefazolin

Enzymatic synthesis plays a pivotal role in the sustainable production of semi-synthetic β-lactam antibiotics. However, these types of green syntheses are being developed slowly because of a lack of appropriate enzymes. In the present work, a computational strategy was developed to identify variants of penicillin G acylase that can catalyze the condensation between methyl 1H-tetrazol-1-yl acetate (TZAM) and 7-amino-3-[(5-methyl-1,3,4-thiadiazol-2-yl) thiomethyl] cephalosphoranic acid (7-ZACA) to produce cefazolin in a fully aqueous medium. An initial library containing 770 sequences was generated by our computational enzyme design program PRODA, which applied a deterministic global minimization algorithm to optimize the binding between the acyl donor and the attacking nucleophile for high kinetic selectivity. The 13 top-ranked variants were subjected to experimental testing based on evaluation by multiple short-time molecular dynamics simulations. A single variant (R145αG) was experimentally confirmed to afford higher kinetic selectivity with a synthesis/hydrolysis ratio (S/H) that was increased by approximately 40% compared with the wild type, and the immobilized enzyme catalyst gave a yield of cefazolin of up to 92% with a 1.8:1 molar ratio of TZAM/7-ZACA, which to our knowledge is the lowest molar ratio of TZAM/7-ZACA to produce a yield over 90%. This study represents considerable progress toward cefazolin synthesis under practical conditions and indicates that this computational strategy could improve enzyme properties for the bio-manufacturing of non-natural molecules.

Peculiar diffusion behavior of AlCl4 intercalated in graphite from nanosecond-long molecular dynamics simulations* *Project supported by the National Key Research and Development Program of China (Grant No. 2016YFB0201202) and the National Natural Science Foundation of China (Grant Nos. 11874335 and 11774327).

The diffusion property of the intercalated species in the graphite materials is at the heart of the rate performance of graphite-based metal-ion secondary battery. Here we study the diffusion process of a AlCl4 molecule within graphite — a key component of a recently reported aluminum ion battery with excellent performance — via molecular dynamics (MD) simulations. Both ab-initio MD (AIMD) and semiempirical tight-binding MD simulations show that the diffusion process of the intercalated AlCl4 molecule becomes rather inhomogeneous, when the simulation time exceeds approximately 100 picoseconds. Specifically, during its migration in between graphene layers, the intercalated AlCl4 molecule may become stagnant occasionally, and then recovers its normal (fast) diffusion behavior after halting for a while. When this phenomenon occurs, the linear relationship of the mean squared displacement (MSD) versus the duration time is not fulfilled. We interpret this peculiar behavior as a manifestation of inadequate sampling of rare event (the stagnation of the molecule), which does not yet appear in short-time MD simulations. We further check the influence of strains present in graphite intercalated compounds (GIC) on the diffusion properties of AlCl4, and find that their presence in general slows down the diffusion of the intercalated molecule, and is detrimental to the rate performance of the GIC-based battery.

Antigenic Peptide Loading into Major Histocompatibility Complex Class I Is Driven by the Substrate N-Terminus

Major histocompatibility complex class I (MHC-I), a key element of the acquired immune system, plays essential roles in activating CD8+ T cells by recognizing intracellular antigens derived from pa...

Selection Rules for Outliers in Outlier Flooding Method Regulate Its Conformational Sampling Efficiency

The outlier flooding method (OFLOOD) has been proposed as an enhanced conformational sampling method of proteins. In OFLOOD, rarely occurring states of proteins are detected as sparse conformational distributions (outliers) with a clustering algorithm. The detected outliers are intensively resampled with short-time molecular dynamics (MD) simulations. As a set of cycles, OFLOOD repeats selections of outliers and their conformational resampling. Herein, as an essential issue to be tackled to perform OFLOOD efficiently, a selection rule for outliers should be carefully specified. Generally, many outliers are detected from distributions on conformational subspaces with the clustering. Judging from its computational costs, it is unreasonable to select all the detected outliers upon the conformational resampling. Therefore, it is important to consider which outliers should be selected from the sparse distributions when restarting their short-time MD simulations with limited computational costs. In this sense, we investigated the conformational sampling efficiency of OFLOOD by changing the selection rules for outliers. To address the conformational sampling efficiency of OFLOOD depending on its selection rules, outliers to be resampled were selected by focusing their probability occurrences (populations of outliers). As a comparison, a random selection rule for outliers was also considered. Through the present assessment, the random selection of outliers showed the most efficient conformational sampling efficiency compared to the other OFLOOD trials using the biased selection rules, indicating that a variety of outliers should be selected and resampled during the OFLOOD cycles. In conclusion, the random outlier selection rule is the best strategy to perform OFLOOD efficiently.

Simple, yet Efficient Conformational Sampling Methods for Reproducing/Predicting Biologically Rare Events of Proteins

Abstract The biological functions of proteins are strongly related to their conformational transitions. To elucidate the essential dynamics, molecular dynamics (MD) simulation has become a powerful tool. However, it might still be difficult to address the relevant conformational transitions of proteins with the conventional MD (CMD) because the accessible time scales of CMD are far from those of the biological functions. Furthermore, the essential transitions are induced as stochastic processes in the long time scales, i.e. the conformational transitions are regarded as biologically relevant rare events. To reproduce/predict the rare events, we have proposed several enhanced conformational sampling methods. Our strategy to detect the rare events is based on cycles of the following conformational resampling consisting of two steps. (1) Selections of essential initial structures. (2) Restarting of short-time MD simulations from the initial structures. The cycles of conformational resampling increase the transition probabilities, promoting the rare events. In the present article, we review the enhanced conformational sampling methods developed by us, i.e. parallel cascade selection MD (PaCS-MD), fluctuation flooding method (FFM), taboo search algorithm (TBSA), outlier flooding method (OFLOOD), structural dissimilarity sampling (SDS), and self-avoiding conformational sampling (SACS). Furthermore, we introduce representative applications using our methods for several biological systems.

Temperature-Shuffled Structural Dissimilarity Sampling Based on a Root-Mean-Square Deviation.

Structural dissimilarity sampling (SDS) has been proposed as an enhanced conformational sampling method for finding neighboring metastable states of a given reactant or generating transition pathways starting from the reactant. SDS repeats a cycle of two steps: (1) selections of initial structures based on structural dissimilarities by referring to a measure and (2) conformational resampling by restarting short-time molecular dynamics (MD) simulations from the initial structures. In the present study, the measure was defined as the root-mean-square deviation (RMSD) among the resampled snapshots to characterize their structural dissimilarities. Additionally, the temperatures in restarting the short-time MD simulations were randomly shuffled at the beginning of each cycle to further promote the conformational transitions. We call this approach temperature-shuffled SDS (TSF-SDS). As a demonstration, TSF-SDS was applied to promote the open-closed transition of T4 lysozyme (T4L) in explicit water. TSF-SDS successfully reproduced the relevant domain motion with nanosecond-order simulation time, whereas conventional SDS without shuffling of the temperatures failed to promote the transition of T4L, indicating the high conformational sampling efficiency of TSF-SDS for promoting essential conformational transitions of proteins. Furthermore, as a wide-range application, TSF-SDS efficiently identified the native state of trp-cage and a dissociation process of ubiquitin dimer in explicit water.

Structural dissimilarity sampling with dynamically self-guiding selection.

Structural dissimilarity sampling (SDS) has been proposed as an enhanced conformational sampling method for reproducing the structural transitions of a given protein. SDS consists of cycles of two steps: (1) Selections of initial structures with structural dissimilarities by referring to a measure. (2) Conformational resampling by restarting short-time molecular dynamics (MD) simulations from the initial structures. In the present study, an efficient measure is proposed as a dynamically self-guiding selection to accelerate the structural transitions from a reactant state to a product state as an extension to the original SDS. In the extended SDS, the inner product (IP) between the reactant and the snapshots generated by short-time MD simulations are evaluated and ranked according to the IPs at every cycle. Then, the snapshots with low IPs are selected as initial structures for the short-time MD simulations. This scheme enables one to choose dissimilar and distant initial structures from the reactant, and thus the initial structures dynamically head towards the product, promoting structural transitions from the reactant. To confirm the conformational sampling efficiency, the extended SDS was applied to maltodextrin binding protein (MBP), and we successfully reproduced the structural transition from the open to closed states with submicrosecond-order simulation times. However, a conventional long-time MD simulation failed to reproduce the same structural transition. We also compared the performance with that obtained by the ordinary SDS and other sampling techniques that have been developed by us to characterize the possible utility of the extended SDS for actual applications. © 2017 Wiley Periodicals, Inc.

Efficient conformational sampling of proteins based on a multi-dimensional TaBoo SeArch algorithm: An application to folding of chignolin in explicit solvent

Sampling of biologically important rare events are indispensable for understanding biological functions. As a rare event search method, we have developed TaBoo SeArch algorithm (TBSA), in which states of bio-molecules with low frequency are intensively resampled via short-time molecular dynamics simulations with reference to an inverse histogram projected on a reaction coordinate as a weight in random searches.The one-dimensional inverse histogram is extended herein to a multi-dimensional form as a function of appropriate reaction coordinates. Due to the extension with a restriction on sampled spaces, the protein-folding processes of a chignolin in explicit solvent environment are more efficiently reproduced.

Simple, yet powerful methodologies for conformational sampling of proteins.

Several biological functions, such as molecular recognition, enzyme catalysis, signal transduction, allosteric regulation, and protein folding, are strongly related to conformational transitions of proteins. These conformational transitions are generally induced as slow dynamics upon collective motions, including biologically relevant large-amplitude fluctuations of proteins. Although molecular dynamics (MD) simulation has become a powerful tool for extracting conformational transitions of proteins, it might still be difficult to reach time scales of the biological functions because the accessible time scales of MD simulations are far from biological time scales, even if straightforward conventional MD (CMD) simulations using massively parallel computers are employed. Thus, it is desirable to develop efficient methods to achieve canonical ensembles with low computational costs. From this perspective, we review several enhanced conformational sampling techniques of biomolecules developed by us. In our methods, multiple independent short-time MD simulations are employed instead of single straightforward long-time CMD simulations. Our basic strategy is as follows: (i) selection of initial seeds (initial structures) for the conformational sampling in restarting MD simulations. Here, the seeds should be selected as candidates with high potential to transit. (ii) Resampling from the selected seeds by initializing velocities in restarting short-time MD simulations. A cycle of these simple protocols might drastically promote the conformational transitions of biomolecules. (iii) Once reactive trajectories extracted from the cycles of short-time MD simulations are obtained, a free energy profile is evaluated by means of umbrella sampling (US) techniques with the weighted histogram analysis method (WHAM) as a post-processing technique. For the selection of the initial seeds, we proposed four different choices: (1) Parallel CaScade molecular dynamics (PaCS-MD), (2) Fluctuation Flooding Method (FFM), (3) Outlier FLOODing (OFLOOD) method, and (4) TaBoo SeArch (TBSA) method. We demonstrate applications of our methods to several biological systems, such as domain motions of proteins with large-amplitude fluctuations, conformational transitions upon ligand binding, and protein folding/refolding to native structures of proteins. Finally, we show the conformational sampling efficiencies of our methods compared with those by CMD simulations and other previously developed enhanced conformational sampling methods.

Friction model to describe cluster bombardment

Short time molecular dynamics simulations were performed to model C 60 and Au 3 bombardment of an amorphous water sample in the projectile energy range of 5–120 keV. A previously proposed friction model has been applied to describe the fundamental motion of a projectile during cluster bombardment of a solid. This simple analytical model uses a definition of friction on a single particle to describe the cluster movement through a medium. Although the mathematics of the friction model vary among systems, the projectile motion and energy deposition of a single particle into the sample as well as the reactive environment created is close to that of C 60 bombardment.

Sugar Folding: A Novel Structural Prediction Tool for Oligosaccharides and Polysaccharides 2.

This is the second in a set of two articles where we describe our newly developed scheme to predict conformations of complex oligosaccharides in solution. We apply our fast sugar conformation prediction tool to the case of two complex human milk oligosaccharides LNF-1 and LND-1. As described in detail in the first paper, our protocol initially delivers a set of "unique structures" corresponding to important minima on the potential-energy landscape of a complex sugar using an implicit solvent model. The nuclear Overhauser effect ranking of individual conformations provides a suitable way for comparison with available experiments. The structures obtained agree well with earlier computational predictions but are obtained at a significantly lower computational cost. Sugar conformations corresponding to stable energy minima not found by earlier molecular dynamics studies were also detected using our methodology. In order to evaluate the effects of explicit solvation and thermal fluctuations on several different predicted conformers, we also performed short-time molecular dynamics simulations in an explicit solvent.

Sputtering yields for C60 and Au3 bombardment of water ice as a function of incident kinetic energy.

The total sputtering yields for water ice due to kiloelectronvolt cluster bombardment have been measured and compared to the predictions made by the mesoscale energy deposition footprint (MEDF) model. For C60 bombardment, the experimental yield varies almost linearly from 820 water molecule equivalents at an incident kinetic energy of 10 keV to 10 100 water molecule equivalents at a kinetic energy of 120 keV. For Au3 bombardment, the experimental yield varies almost linearly from 630 water molecule equivalents at an incident energy of 10 keV and rises to 1200 water molecule equivalents at 25 keV. The MEDF model is used to calculate relative yield trends with respect to incident energy using short-time molecular dynamics simulations. The results of these calculations indicate that the model can effectively predict the yield trends observed for these two clusters in experiments, although there is a consistent overestimate of the predicted induced C60 yield. It is hypothesized that this overestimate can be explained by the absence of reactions and ionization processes in the current simulations. Despite this omission, experimental yield trends can be accurately predicted using relatively small amounts of computer time. The success of the model in predicting the yield of water from ice films using a variety of energies and projectiles suggests this approach may greatly aid in the optimization of experimental configurations.

Large-Scale Conformational Dynamics of the HIV-1 Integrase Core Domain and Its Catalytic Loop Mutants

HIV-1 integrase is one of the three essential enzymes required for viral replication and has great potential as a novel target for anti-HIV drugs. Although tremendous efforts have been devoted to understanding this protein, the conformation of the catalytic core domain around the active site, particularly the catalytic loop overhanging the active site, is still not well characterized by experimental methods due to its high degree of flexibility. Recent studies have suggested that this conformational dynamics is directly correlated with enzymatic activity, but the details of this dynamics is not known. In this study, we conducted a series of extended-time molecular dynamics simulations and locally enhanced sampling simulations of the wild-type and three loop hinge mutants to investigate the conformational dynamics of the core domain. A combined total of >480 ns of simulation data was collected which allowed us to study the conformational changes that were not possible to observe in the previously reported short-time molecular dynamics simulations. Among the main findings are a major conformational change (>20 Å) in the catalytic loop, which revealed a gatinglike dynamics, and a transient intraloop structure, which provided a rationale for the mutational effects of several residues on the loop including Q 148, P 145, and Y 143. Further, clustering analyses have identified seven major conformational states of the wild-type catalytic loop. Their implications for catalytic function and ligand interaction are discussed. The findings reported here provide a detailed view of the active site conformational dynamics and should be useful for structure-based inhibitor design for integrase.

Short time molecular dynamics simulations: Stressed polyethylene results

AbstractThe multiple signal classification method (MUSIC) for frequency estimation is used to compute the spectrum (intensity versus frequency) for stressed polyethylene in a crystal from the time‐dependent structure factor. In this article we demonstrate that MUSIC can accurately determine the frequencies for our model from very short time trajectories and can compute the frequency shifts for various stress perturbations. A preliminary study of the dynamical effects of stress on the fracture of a PE chain showed that at low stress the chain had an irregular period of the end‐to‐end distance (reaction coordinate) oscillation and at higher stress a periodic extension and contraction.

Dispersion curves from short-time molecular dynamics simulations. 1. Diatomic chain results

The multiple signal classification method (MUSIC) for frequency estimation is used to compute the frequency dispersion curves of a diatomic chain from the time-dependent structure factor. In this paper, the authors demonstrate that MUSIC can accurately determine the frequencies from very short time trajectories. MUSIC is also used to show how the frequencies can vary in time, i.e., along a trajectory. The method is ideally suited for analyzing molecular dynamics simulations of large systems.