scholarly journals Probing the Broad Time Scale and Heterogeneous Conformational Dynamics in the Catalytic Core of the Arf-GAP ASAP1 via Methyl Adiabatic Relaxation Dispersion

2019 ◽  
Vol 141 (30) ◽  
pp. 11881-11891 ◽  
Author(s):  
Fa-An Chao ◽  
Yifei Li ◽  
Yue Zhang ◽  
R. Andrew Byrd
Keyword(s):  
Time Scale ◽  
Conformational Dynamics ◽  
Relaxation Dispersion ◽  
Catalytic Core

scholarly journals Heteronuclear Adiabatic Relaxation Dispersion (HARD) for quantitative analysis of conformational dynamics in proteins

2012 ◽  
Vol 219 ◽  
pp. 75-82 ◽  
Author(s):  
Nathaniel J. Traaseth ◽  
Fa-An Chao ◽  
Larry R. Masterson ◽  
Silvia Mangia ◽  
Michael Garwood ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Conformational Dynamics ◽  
Relaxation Dispersion

scholarly journals Confronting pitfalls of AI-augmented molecular dynamics using statistical physics

2020 ◽  
Author(s):  
Shashank Pant ◽  
Zachary Smith ◽  
Yihang Wang ◽  
Emad Tajkhorshid ◽  
Pratyush Tiwary
Keyword(s):  
Time Scale ◽  
Conformational Dynamics ◽  
Molecular Simulations ◽  
Ground Truth ◽  
Relevant Information ◽  
Benchmark Problems ◽  
Peptide Ligand ◽  
Limited Data ◽  
Scale Separation ◽  
Time Scale Separation

AbstractArtificial intelligence (AI)-based approaches have had indubitable impact across the sciences through the ability to extract relevant information from raw data. Recently AI has also seen use for enhancing the efficiency of molecular simulations, wherein AI derived slow modes are used to accelerate the simulation in targeted ways. However, while typical fields where AI is used are characterized by a plethora of data, molecular simulations per-construction suffer from limited sampling and thus limited data. As such the use of AI in molecular simulations can suffer from a dangerous situation where the AI-optimization could get stuck in spurious regimes, leading to incorrect characterization of the reaction coordinate (RC) for the problem at hand. When such an incorrect RC is then used to perform additional simulations, one could start to deviate progressively from the ground truth. To deal with this problem of spurious AI-solutions, here we report a novel and automated algorithm using ideas from statistical mechanics. It is based on the notion that a more reliable AI-solution will be one that maximizes the time-scale separation between slow and fast processes. To learn this time-scale separation even from limited data, we use a maximum caliber-based framework. We show the applicability of this automatic protocol for 3 classic benchmark problems, namely the conformational dynamics of a model peptide, ligand-unbinding from a protein, and folding/unfolding energy landscape of the C-terminal domain of protein G. We believe our work will lead to increased and robust use of trustworthy AI in molecular simulations of complex systems.

scholarly journals Searching for Correlated Conformational Dynamics: Analysis of the NMR Relaxation Dispersions with Akaike's Information Theory and Hierarchical Clustering

2017 ◽  
Author(s):  
Evgenii L. Kovrigin
Keyword(s):  
Conformational Dynamics ◽  
Nmr Relaxation ◽  
Hierarchical Cluster ◽  
Information Criteria ◽  
Relaxation Dispersion ◽  
Spin Groups ◽  
Dispersion Data ◽  
Poorly Soluble ◽  
The Difference ◽  
Best Fit

ABSTRACT:In this manuscript, I am proposing an approach for identification of correlated exchange in proteins via analysis of the NMR relaxation dispersion data. For a set of spins experiencing exchange, every relaxation dispersion datasets is fit individually and then—globally while paired with every other dataset. The corrected Akaike’ s Information Criteria (AICc) for individual and global fits are used to evaluate the likelihood of two spins to report on the same dynamic event. Application of hierarchical cluster analysis reveals correlated spin groups using the difference in AICcs as a measure of similarity within the pairs. This approach to detection of correlated dynamics is independent of accuracy of best-fit parameters rendering it less sensitive to experimental noise. High throughput and the absence of the operator bias might make it applicable to a relatively lower quality NMR relaxation dispersion data from large and poorly soluble systems.

scholarly journals Molecular recognition of a host protein by NS1 of pandemic and seasonal influenza A viruses

2020 ◽  
Vol 117 (12) ◽  
pp. 6550-6558 ◽  
Author(s):  
Jae-Hyun Cho ◽  
Baoyu Zhao ◽  
Jie Shi ◽  
Nowlan Savage ◽  
Qingliang Shen ◽  
...  
Keyword(s):  
Molecular Recognition ◽  
Influenza A ◽  
Nonstructural Protein ◽  
Conformational Dynamics ◽  
Relaxation Dispersion ◽  
Binding Kinetics ◽  
Host Protein ◽  
Dynamics Simulation ◽  
Nonstructural Protein 1 ◽  
Strain Dependent

The 1918 influenza A virus (IAV) caused the most severe flu pandemic in recorded human history. Nonstructural protein 1 (NS1) is an important virulence factor of the 1918 IAV. NS1 antagonizes host defense mechanisms through interactions with multiple host factors. One pathway by which NS1 increases virulence is through the activation of phosphoinositide 3-kinase (PI3K) by binding to its p85β subunit. Here we present the mechanism underlying the molecular recognition of the p85β subunit by 1918 NS1. Using X-ray crystallography, we determine the structure of 1918 NS1 complexed with p85β of human PI3K. We find that the 1918 NS1 effector domain (1918 NS1ED) undergoes a conformational change to bind p85β. Using NMR relaxation dispersion and molecular dynamics simulation, we identify that free 1918 NS1EDexists in a dynamic equilibrium between p85β-binding–competent and –incompetent conformations in the submillisecond timescale. Moreover, we discover that NS1EDproteins of 1918 (H1N1) and Udorn (H3N2) strains exhibit drastically different conformational dynamics and binding kinetics to p85β. These results provide evidence of strain-dependent conformational dynamics of NS1. Using kinetic modeling based on the experimental data, we demonstrate that 1918 NS1EDcan result in the faster hijacking of p85β compared to Ud NS1ED, although the former has a lower affinity to p85β than the latter. Our results suggest that the difference in binding kinetics may impact the competition with cellular antiviral responses for the activation of PI3K. We anticipate that our findings will increase the understanding of the strain-dependent behaviors of influenza NS1 proteins.

scholarly journals Thermal fluctuations of haemoglobin from different species: adaptation to temperature via conformational dynamics

2012 ◽  
Vol 9 (76) ◽  
pp. 2845-2855 ◽  
Author(s):  
A. M. Stadler ◽  
C. J. Garvey ◽  
A. Bocahut ◽  
S. Sacquin-Mora ◽  
I. Digel ◽  
...  
Keyword(s):  
Body Temperature ◽  
Time Scale ◽  
Brownian Dynamics ◽  
Conformational Dynamics ◽  
Coarse Grained ◽  
Mean Square ◽  
Temperature Range ◽  
Dynamics Simulations ◽  
Brownian Dynamics Simulations ◽  
Average Body

Thermodynamic stability, configurational motions and internal forces of haemoglobin (Hb) of three endotherms (platypus, Ornithorhynchus anatinus ; domestic chicken, Gallus gallus domesticus and human, Homo sapiens ) and an ectotherm (salt water crocodile, Crocodylus porosus ) were investigated using circular dichroism, incoherent elastic neutron scattering and coarse-grained Brownian dynamics simulations. The experimental results from Hb solutions revealed a direct correlation between protein resilience, melting temperature and average body temperature of the different species on the 0.1 ns time scale. Molecular forces appeared to be adapted to permit conformational fluctuations with a root mean square displacement close to 1.2 Å at the corresponding average body temperature of the endotherms. Strong forces within crocodile Hb maintain the amplitudes of motion within a narrow limit over the entire temperature range in which the animal lives. In fully hydrated powder samples of human and chicken, Hb mean square displacements and effective force constants on the 1 ns time scale showed no differences over the whole temperature range from 10 to 300 K, in contrast to the solution case. A complementary result of the study, therefore, is that one hydration layer is not sufficient to activate all conformational fluctuations of Hb in the pico- to nanosecond time scale which might be relevant for biological function. Coarse-grained Brownian dynamics simulations permitted to explore residue-specific effects. They indicated that temperature sensing of human and chicken Hb occurs mainly at residues lining internal cavities in the β-subunits.

13CHD2Methyl Group Probes of Millisecond Time Scale Exchange in Proteins by1H Relaxation Dispersion: An Application to Proteasome Gating Residue Dynamics

2010 ◽  
Vol 132 (32) ◽  
pp. 10992-10995 ◽  
Author(s):  
Andrew J. Baldwin ◽  
Tomasz L. Religa ◽  
D. Flemming Hansen ◽  
Guillaume Bouvignies ◽  
Lewis E. Kay
Keyword(s):  
Time Scale ◽  
Relaxation Dispersion ◽  
Millisecond Time Scale
Sign in / Sign up

Export Citation Format

Share Document