Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

Sinitskiy, Anton V.; Pande, Vijay S.

doi:10.1063/1.5005058

Cited by 5 publications

(6 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…K-Medoids clustering led to the same qualitative results as that of K-Centers clustering (data not shown). As demonstrated recently, the slowest timescale that an MSM of a biomolecule could capture is comparable by order of magnitude to the aggregate duration of all MD trajectories used to build this MSM (56). This theoretical result allows us to expect that our simulations of NMDARs can provide information on conformational transitions in these receptors on timescales of up to $15 ms for both apo and holo forms.…”

Section: Markov State Modelssupporting

confidence: 62%

Computer Simulations Predict High Structural Heterogeneity of Functional State of NMDA Receptors

Sinitskiy

Pande

2018

Biophysical Journal

Self Cite

View full text Add to dashboard Cite

N-methyl-D-aspartate receptors (NMDARs)-i.e., transmembrane proteins expressed in neurons-play a central role in the molecular mechanisms of learning and memory formation. It is unclear how the known atomic structures of NMDARs determined by x-ray crystallography and electron cryomicroscopy (18 published Protein Data Bank entries) relate to the functional states of NMDARs inferred from electrophysiological recordings (multiple closed, open, preopen, etc. states). We address this problem by using molecular dynamics simulations at atomic resolution, a method successfully applied in the past to much smaller biomolecules. Our simulations predict that several conformations of NMDARs with experimentally determined geometries, including four "nonactive" electron cryomicroscopy structures, rapidly interconvert on submicrosecond timescales and therefore may correspond to the same functional state of the receptor (specifically, one of the closed states). This conclusion is not trivial because these conformational transitions involve changes in certain interatomic distances as large as tens of Å. The simulations also predict differences in the conformational dynamics of the apo and holo (i.e., agonist and coagonist bound) forms of the receptor on the microsecond timescale. To our knowledge, five new conformations of NMDARs, with geometries joining various features from different known experimental structures, are also predicted by the model. The main limitation of this work stems from its limited sampling (30 μs of aggregate length of molecular dynamics trajectories). Though this level significantly exceeds the sampling in previous simulations of parts of NMDARs, it is still much lower than the sampling recently achieved for smaller biomolecules (up to a few milliseconds), thus precluding, in particular, the observation of transitions between different functional states of NMDARs. Despite this limitation, such computational predictions may guide further experimental studies on the structure, dynamics, and function of NMDARs, for example by suggesting optimal locations of spectroscopic probes. Overall, atomic resolution simulations provide, to our knowledge, a novel perspective on the structure and dynamics of NMDARs, complementing information obtained by experimental methods.

show abstract

Section: Markov State Modelssupporting

confidence: 62%

Computer Simulations Predict High Structural Heterogeneity of Functional State of NMDA Receptors

Sinitskiy

Pande

2018

Biophysical Journal

Self Cite

View full text Add to dashboard Cite

show abstract

“…A transition between state A and other states, accompanied by formation or vanishing of a “three-legged stool” conformation of the glycan serving as a latch between two lobes of the GluN1 LBD, was observed only once in the simulations. Respectively, we can only give a lower bound estimate on this time scale, namely that it is significantly greater than the aggregate sampling in our simulations, that is ≫100 μs (respectively, the rate constant ≪10 ms –1 ) . The transition with the slowest implicit time scale captured by MSM modeling is the transition from state C to state B (and, with a smaller weight, to state O) and vice versa, which is convenient to visualize in the tIC 4–tIC 5 plane, since these two tICs are discriminative to states B and C, respectively (Figure c).…”

Section: Resultsmentioning

confidence: 97%

Simulated Dynamics of Glycans on Ligand-Binding Domain of NMDA Receptors Reveals Strong Dynamic Coupling between Glycans and Protein Core

Sinitskiy

Pande

2017

J. Chem. Theory Comput.

Self Cite

View full text Add to dashboard Cite

N-Methyl-d-aspartate (NMDA) receptors, key neuronal receptors playing the central role in learning and memory, are heavily glycosylated in vivo. Astonishingly little is known about the structure, dynamics, and physiological relevance of glycans attached to them. We recently demonstrated that certain glycans on the ligand binding domain (LBD) of NMDA receptors (NMDARs) can serve as intramolecular potentiators, changing EC50 of NMDAR coagonists. In this work, we use molecular dynamics trajectories, in aggregate 86.5 μs long, of the glycosylated LBD of the GluN1 subunit of the NMDAR to investigate the behavior of glycans on NMDARs. Though all glycans in our simulations were structurally the same (Man5), the dynamics of glycans at different locations on NMDARs was surprisingly different. The slowest-time scale motions that we detected in various glycans in some cases corresponded to a flipping of parts of glycans relative to each other, while in other cases they reduced to a head-to-tail bending of a glycan. We predict that time scales of conformational changes in glycans on the GluN1 LBD of NMDARs range from nanoseconds to at least hundreds of microseconds. Some of the conformational changes in the glycans correlate with the physiologically important clamshell-like opening and closing of the GluN1 LBD domain. Thus, glycans are an integral part of NMDARs, and computational models of NMDARs should include glycans to faithfully represent the structure and the dynamics of these receptors.

show abstract

“…The largest implied time scale can be of the same order of magnitude of the aggregate duration of all MD trajectories used to build the MSM. 212 Obviously, the initialization points must be chosen with care, and one must ensure that no important regions of the phase space are ignored.…”

Section: Molecular Dynamics Simulation Methodologiesmentioning

confidence: 99%

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

et al. 2018

View full text Add to dashboard Cite

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA–ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

show abstract

Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

Cited by 5 publications

References 40 publications

Computer Simulations Predict High Structural Heterogeneity of Functional State of NMDA Receptors

Computer Simulations Predict High Structural Heterogeneity of Functional State of NMDA Receptors

Simulated Dynamics of Glycans on Ligand-Binding Domain of NMDA Receptors Reveals Strong Dynamic Coupling between Glycans and Protein Core

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

Contact Info

Product

Resources

About