Multiscale methods for macromolecular simulations.
Ontology highlight
ABSTRACT:
SUBMITTER: Sherwood P
PROVIDER: S-EPMC6407689 | biostudies-literature | 2008 Oct
REPOSITORIES: biostudies-literature
Publications
Multiscale methods for macromolecular simulations.
Sherwood Paul P Brooks Bernard R BR Sansom Mark S P MS
Current opinion in structural biology 20080917 5
In this article we review the key modeling tools available for simulating biomolecular systems. We consider recent developments and representative applications of mixed quantum mechanics/molecular mechanics (QM/MM), elastic network models (ENMs), coarse-grained molecular dynamics, and grid-based tools for calculating interactions between essentially rigid protein assemblies. We consider how the different length scales can be coupled, both in a sequential fashion (e.g. a coarse-grained or grid mo ...[more]
Similar Datasets
Project description:Molecular dynamics (MD) is the only technique available for obtaining dynamic protein data at atomic spatial resolution and picosecond or finer temporal resolution. In recent years, the cost of computational resources has decreased exponentially while the number of known protein structures, many of which are not characterized biochemically, has increased rapidly. These events have led to an increase in the use of MD in biological research, both to examine phenomena that cannot be resolved experimentally and to generate hypotheses that direct further experimental research. In fact, several databases of MD simulations have arisen in recent years. MD simulations, and especially MD simulation databases, contain massive amounts of data, yet interesting phenomena often occur over very short time periods and on the scale of only a few atoms. Analysis of such data must balance these fine-detail events with the global picture they create. Here, we address the multiscale nature of the problem by comparing several MD analysis methods to show their strengths and weaknesses at various scales using the wild-type and R282W mutant forms of the DNA-binding domain of protein p53. By leveraging these techniques together, we are able to pinpoint fine-detail and big picture differences between the protein's variants. Our analyses indicate that the R282W mutation of p53 destabilizes the L1 loop and loosens the H2 helix conformation, but the loosened L1 loop can be rescued by residue H115, preventing the R282W mutation from completely destabilizing the protein or abolishing activity.
| S-EPMC3406285 | biostudies-literature
Project description:Multiscale analysis provides an algorithm for the efficient simulation of macromolecular assemblies. This algorithm involves the coevolution of a quasiequilibrium probability density of atomic configurations and the Langevin dynamics of spatial coarse-grained variables denoted order parameters (OPs) characterizing nanoscale system features. In practice, implementation of the probability density involves the generation of constant OP ensembles of atomic configurations. Such ensembles are used to construct thermal forces and diffusion factors that mediate the stochastic OP dynamics. Generation of all-atom ensembles at every Langevin time step is computationally expensive. Here, multiscale computation for macromolecular systems is made more efficient by a method that self-consistently folds in ensembles of all-atom configurations constructed in an earlier step, history, of the Langevin evolution. This procedure accounts for the temporal evolution of these ensembles, accurately providing thermal forces and diffusions. It is shown that efficiency and accuracy of the OP-based simulations is increased via the integration of this historical information. Accuracy improves with the square root of the number of historical timesteps included in the calculation. As a result, CPU usage can be decreased by a factor of 3-8 without loss of accuracy. The algorithm is implemented into our existing force-field based multiscale simulation platform and demonstrated via the structural dynamics of viral capsomers.
| S-EPMC3721968 | biostudies-literature
Project description:Multiscale simulations model phenomena across natural scales using monolithic or component-based code, running on local or distributed resources. In this work, we investigate the performance of distributed multiscale computing of component-based models, guided by six multiscale applications with different characteristics and from several disciplines. Three modes of distributed multiscale computing are identified: supplementing local dependencies with large-scale resources, load distribution over multiple resources, and load balancing of small- and large-scale resources. We find that the first mode has the apparent benefit of increasing simulation speed, and the second mode can increase simulation speed if local resources are limited. Depending on resource reservation and model coupling topology, the third mode may result in a reduction of resource consumption.
| S-EPMC4084531 | biostudies-literature
Project description:Smoldyn is a software package for stochastic modelling of spatial biochemical networks and intracellular systems. It was originally developed with an accurate off-lattice particle-based model at its core. This has recently been enhanced with the addition of a computationally efficient on-lattice model, which can be run stand-alone or coupled together for multiscale simulations using both models in regions where they are most required, increasing the applicability of Smoldyn to larger molecule numbers and spatial domains. Simulations can switch between models with only small additions to their configuration file, enabling users with existing Smoldyn configuration files to run the new on-lattice model with any reaction, species or surface descriptions they might already have.Source code and binaries freely available for download at www.smoldyn.org, implemented in C/C++ and supported on Linux, Mac OSX and MS Windows.
| S-EPMC4495299 | biostudies-other
Project description:The structures of biological macromolecules would not be known to their present extent without X-ray crystallography. Most simulations of globular proteins in solution begin by surrounding the crystal structure of the monomer in a bath of water molecules, but the standard simulation employing periodic boundary conditions is already close to a crystal lattice environment. With simple protocols, the same software and molecular models can perform simulations of the crystal lattice, including all asymmetric units and solvent to fill the box. Throughout the history of molecular dynamics, studies of crystal lattices have served to investigate the quality of the underlying force fields, correlate the simulated ensembles to experimental structure factors, and extrapolate the behavior in lattices to behavior in solution. Powerful new computers are enabling molecular simulations with greater realism and statistical convergence. Meanwhile, the advent of exciting new methods in crystallography, including femtosecond free-electron lasers and image reconstruction for time-resolved crystallography on slurries of small crystals, is expanding the range of structures accessible to X-ray diffraction. We review past fusions of simulations and crystallography, then look ahead to the ways that simulations of crystal structures will enhance structural biology in the future.
| S-EPMC6818516 | biostudies-literature
Project description:The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20,000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.
| S-EPMC3695996 | biostudies-other
Project description:An approach for the automated discovery of low free energy states of macromolecular systems is presented. The method does not involve delineating the entire free energy landscape but proceeds in a sequential free energy minimizing state discovery; i.e., it first discovers one low free energy state and then automatically seeks a distinct neighboring one. These states and the associated ensembles of atomistic configurations are characterized by coarse-grained variables capturing the large-scale structure of the system. A key facet of our approach is the identification of such coarse-grained variables. Evolution of these variables is governed by Langevin dynamics driven by thermal-average forces and mediated by diffusivities, both of which are constructed by an ensemble of short molecular dynamics runs. In the present approach, the thermal-average forces are modified to account for the entropy changes following from our knowledge of the free energy basins already discovered. Such forces guide the system away from the known free energy minima, over free energy barriers, and to a new one. The theory is demonstrated for lactoferrin, known to have multiple energy-minimizing structures. The approach is validated using experimental structures and traditional molecular dynamics. The method can be generalized to enable the interpretation of nanocharacterization data (e.g., ion mobility-mass spectrometry, atomic force microscopy, chemical labeling, and nanopore measurements).
| S-EPMC3408247 | biostudies-literature
Project description:Protein functions require specific structures frequently coupled with conformational changes. The scale of the structural dynamics of proteins spans from the atomic to the molecular level. Theoretically, all-atom molecular dynamics (MD) simulation is a powerful tool to investigate protein dynamics because the MD simulation is capable of capturing conformational changes obeying the intrinsically structural features. However, to study long-timescale dynamics, efficient sampling techniques and coarse-grained (CG) approaches coupled with all-atom MD simulations, termed multiscale MD simulations, are required to overcome the timescale limitation in all-atom MD simulations. Here, we review two examples of rotary motor proteins examined using free energy landscape (FEL) analysis and CG-MD simulations. In the FEL analysis, FEL is calculated as a function of reaction coordinates, and the long-timescale dynamics corresponding to conformational changes is described as transitions on the FEL surface. Another approach is the utilization of the CG model, in which the CG parameters are tuned using the fluctuation matching methodology with all-atom MD simulations. The long-timespan dynamics is then elucidated straightforwardly by using CG-MD simulations.
| S-EPMC5899732 | biostudies-literature
Project description:The catalytic promiscuity and fidelity of cytochrome P450 enzymes are widespread in the skeletal modification of terpenoid natural products and have attracted much attention. CYP76AH1 is involved in key modification reactions in the biosynthetic pathway of tanshinone, a well-known medicinal norditerpenoid. In this work, classical molecular dynamic simulations, metadynamics, and DFT calculations were performed to investigate the protein conformational dynamics, ligand binding poses, and catalytic reaction mechanism in wide-type and mutant CYP76AH1. Our results not only reveal a plausible enzymatic mechanism for mutant CYP76AH1 leading to various products but also provide valuable guidance for rational protein engineering of the CYP76 family.
| S-EPMC8207200 | biostudies-literature
Project description:When photoactive molecules interact strongly with confined light modes in optical cavities, new hybrid light-matter states form. They are known as polaritons and correspond to coherent superpositions of excitations of the molecules and of the cavity photon. The polariton energies and thus potential energy surfaces are changed with respect to the bare molecules, such that polariton formation is considered a promising paradigm for controlling photochemical reactions. To effectively manipulate photochemistry with confined light, the molecules need to remain in the polaritonic state long enough for the reaction on the modified potential energy surface to take place. To understand what determines this lifetime, we have performed atomistic molecular dynamics simulations of room-temperature ensembles of rhodamine chromophores strongly coupled to a single confined light mode with a 15 fs lifetime. We investigated three popular experimental scenarios and followed the relaxation after optically pumping (i) the lower polariton, (ii) the upper polariton, or (iii) uncoupled molecular states. The results of the simulations suggest that the lifetimes of the optically accessible lower and upper polaritons are limited by (i) ultrafast photoemission due to the low cavity lifetime and (ii) reversible population transfer into the "dark" state manifold. Dark states are superpositions of molecular excitations but with much smaller contributions from the cavity photon, decreasing their emission rates and hence increasing their lifetimes. We find that population transfer between polaritonic modes and dark states is determined by the overlap between the polaritonic and molecular absorption spectra. Importantly, excitation can also be transferred "upward" from the lower polariton into the dark-state reservoir due to the broad absorption spectra of the chromophores, contrary to the common conception of these processes as a "one-way" relaxation from the dark states down to the lower polariton. Our results thus suggest that polaritonic chemistry relying on modified dynamics taking place within the lower polariton manifold requires cavities with sufficiently long lifetimes and, at the same time, strong light-matter coupling strengths to prevent the back-transfer of excitation into the dark states.
| S-EPMC6914212 | biostudies-literature