8,137 research outputs found
Path Similarity Analysis: a Method for Quantifying Macromolecular Pathways
Diverse classes of proteins function through large-scale conformational
changes; sophisticated enhanced sampling methods have been proposed to generate
these macromolecular transition paths. As such paths are curves in a
high-dimensional space, they have been difficult to compare quantitatively, a
prerequisite to, for instance, assess the quality of different sampling
algorithms. The Path Similarity Analysis (PSA) approach alleviates these
difficulties by utilizing the full information in 3N-dimensional trajectories
in configuration space. PSA employs the Hausdorff or Fr\'echet path
metrics---adopted from computational geometry---enabling us to quantify path
(dis)similarity, while the new concept of a Hausdorff-pair map permits the
extraction of atomic-scale determinants responsible for path differences.
Combined with clustering techniques, PSA facilitates the comparison of many
paths, including collections of transition ensembles. We use the closed-to-open
transition of the enzyme adenylate kinase (AdK)---a commonly used testbed for
the assessment enhanced sampling algorithms---to examine multiple microsecond
equilibrium molecular dynamics (MD) transitions of AdK in its substrate-free
form alongside transition ensembles from the MD-based dynamic importance
sampling (DIMS-MD) and targeted MD (TMD) methods, and a geometrical targeting
algorithm (FRODA). A Hausdorff pairs analysis of these ensembles revealed, for
instance, that differences in DIMS-MD and FRODA paths were mediated by a set of
conserved salt bridges whose charge-charge interactions are fully modeled in
DIMS-MD but not in FRODA. We also demonstrate how existing trajectory analysis
methods relying on pre-defined collective variables, such as native contacts or
geometric quantities, can be used synergistically with PSA, as well as the
application of PSA to more complex systems such as membrane transporter
proteins.Comment: 9 figures, 3 tables in the main manuscript; supplementary information
includes 7 texts (S1 Text - S7 Text) and 11 figures (S1 Fig - S11 Fig) (also
available from journal site
Structural ultrafast dynamics of macromolecules: diffraction of free DNA and effect of hydration
Of special interest in molecular biology is the study of structural and conformational changes which are free of the additional effects of the environment. In the present contribution, we report on the ultrafast unfolding dynamics of a large DNA macromolecular ensemble in vacuo for a number of temperature jumps, and make a comparison with the unfolding dynamics of the DNA in aqueous solution. A number of coarse-graining approaches, such as kinetic intermediate structure (KIS) model and ensemble-averaged radial distribution functions, are used to account for the transitional dynamics of the DNA without sacrificing the structural resolution. The studied ensembles of DNA macromolecules were generated using distributed molecular dynamics (MD) simulations, and the ensemble convergence was ensured by monitoring the ensemble-averaged radial distribution functions and KIS unfolding trajectories. Because the order–disorder transition in free DNA implies unzipping, coiling, and strand-separation processes which occur consecutively or competitively depending on the initial and final temperature of the ensemble, DNA order–disorder transition in vacuo cannot be described as a two-state (un)folding process
A flexible architecture for modeling and simulation of diffusional association
Up to now, it is not possible to obtain analytical solutions for complex
molecular association processes (e.g. Molecule recognition in Signaling or
catalysis). Instead Brownian Dynamics (BD) simulations are commonly used to
estimate the rate of diffusional association, e.g. to be later used in
mesoscopic simulations. Meanwhile a portfolio of diffusional association (DA)
methods have been developed that exploit BD.
However, DA methods do not clearly distinguish between modeling, simulation,
and experiment settings. This hampers to classify and compare the existing
methods with respect to, for instance model assumptions, simulation
approximations or specific optimization strategies for steering the computation
of trajectories.
To address this deficiency we propose FADA (Flexible Architecture for
Diffusional Association) - an architecture that allows the flexible definition
of the experiment comprising a formal description of the model in SpacePi,
different simulators, as well as validation and analysis methods. Based on the
NAM (Northrup-Allison-McCammon) method, which forms the basis of many existing
DA methods, we illustrate the structure and functioning of FADA. A discussion
of future validation experiments illuminates how the FADA can be exploited in
order to estimate reaction rates and how validation techniques may be applied
to validate additional features of the model
Exploration of Reaction Pathways and Chemical Transformation Networks
For the investigation of chemical reaction networks, the identification of
all relevant intermediates and elementary reactions is mandatory. Many
algorithmic approaches exist that perform explorations efficiently and
automatedly. These approaches differ in their application range, the level of
completeness of the exploration, as well as the amount of heuristics and human
intervention required. Here, we describe and compare the different approaches
based on these criteria. Future directions leveraging the strengths of chemical
heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure
Accounting for Large Amplitude Protein Deformation during in Silico Macromolecular Docking
Rapid progress of theoretical methods and computer calculation resources has turned in silico methods into a conceivable tool to predict the 3D structure of macromolecular assemblages, starting from the structure of their separate elements. Still, some classes of complexes represent a real challenge for macromolecular docking methods. In these complexes, protein parts like loops or domains undergo large amplitude deformations upon association, thus remodeling the surface accessible to the partner protein or DNA. We discuss the problems linked with managing such rearrangements in docking methods and we review strategies that are presently being explored, as well as their limitations and success
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