Coarse-Grained Models of the Proteins Backbone Conformational Dynamics

2013 ◽  
pp. 157-169
Author(s):  
Tap Ha-Duong
Keyword(s):  
Conformational Dynamics ◽  
Coarse Grained

scholarly journals Coarse-Grained Models Reveal Functional Dynamics - I. Elastic Network Models – Theories, Comparisons and Perspectives

2008 ◽  
Vol 2 ◽  
pp. BBI.S460 ◽  
Author(s):  
Lee-Wei Yang ◽  
Choon-Peng Chng
Keyword(s):  
Conformational Changes ◽  
Conformational Dynamics ◽  
Computational Cost ◽  
Network Models ◽  
Coarse Graining ◽  
Coarse Grained ◽  
Elastic Network ◽  
Elastic Network Models ◽  
Time Space ◽  
Functional Dynamics

In this review, we summarize the progress on coarse-grained elastic network models (CG-ENMs) in the past decade. Theories were formulated to allow study of conformational dynamics in time/space frames of biological interest. Several highlighted models and their underlined hypotheses are introduced in physical depth. Important ENM offshoots, motivated to reproduce experimental data as well as to address the slow-mode-encoded configurational transitions, are also introduced. With the theoretical developments, computational cost is significantly reduced due to simplified potentials and coarse-grained schemes. Accumulating wealth of data suggest that ENMs agree equally well with experiment in describing equilibrium dynamics despite their distinct potentials and levels of coarse-graining. They however do differ in the slowest motional components that are essential to address large conformational changes of functional significance. The difference stems from the dissimilar curvatures of the harmonic energy wells described for each model. We also provide our views on the predictability of ‘open to close’ (open→close) transitions of biomolecules on the basis of conformational selection theory. Lastly, we address the limitations of the ENM formalism which are partially alleviated by the complementary CG-MD approach, to be introduced in the second paper of this two-part series.

scholarly journals Expansion of Intrinsically Disordered Proteins Increases the Range of Stability of Liquid–Liquid Phase Separation

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4705
Author(s):  
Adiran Garaizar ◽  
Ignacio Sanchez-Burgos ◽  
Rosana Collepardo-Guevara ◽  
Jorge R. Espinosa
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Protein Interactions ◽  
Conformational Dynamics ◽  
Liquid Phase Separation ◽  
Phase Behaviour ◽  
Coarse Grained ◽  
Protein Protein Interactions ◽  
Intrinsically Disordered ◽  
Liquid Liquid Phase Separation

Proteins containing intrinsically disordered regions (IDRs) are ubiquitous within biomolecular condensates, which are liquid-like compartments within cells formed through liquid–liquid phase separation (LLPS). The sequence of amino acids of a protein encodes its phase behaviour, not only by establishing the patterning and chemical nature (e.g., hydrophobic, polar, charged) of the various binding sites that facilitate multivalent interactions, but also by dictating the protein conformational dynamics. Besides behaving as random coils, IDRs can exhibit a wide-range of structural behaviours, including conformational switching, where they transition between alternate conformational ensembles. Using Molecular Dynamics simulations of a minimal coarse-grained model for IDRs, we show that the role of protein conformation has a non-trivial effect in the liquid–liquid phase behaviour of IDRs. When an IDR transitions to a conformational ensemble enriched in disordered extended states, LLPS is enhanced. In contrast, IDRs that switch to ensembles that preferentially sample more compact and structured states show inhibited LLPS. This occurs because extended and disordered protein conformations facilitate LLPS-stabilising multivalent protein–protein interactions by reducing steric hindrance; thereby, such conformations maximize the molecular connectivity of the condensed liquid network. Extended protein configurations promote phase separation regardless of whether LLPS is driven by homotypic and/or heterotypic protein–protein interactions. This study sheds light on the link between the dynamic conformational plasticity of IDRs and their liquid–liquid phase behaviour.

scholarly journals Dynamical network of residue–residue contacts reveals coupled allosteric effects in recognition, catalysis, and mutation

2016 ◽  
Vol 113 (17) ◽  
pp. 4735-4740 ◽  
Author(s):  
Urmi Doshi ◽  
Michael J. Holliday ◽  
Elan Z. Eisenmesser ◽  
Donald Hamelberg
Keyword(s):  
Active Site ◽  
Substrate Binding ◽  
Conformational Dynamics ◽  
Allosteric Regulation ◽  
Coarse Grained ◽  
Centrality Measures ◽  
Multidimensional Data ◽  
Dynamical Network ◽  
Residue Contacts ◽  
Dynamical Features

Detailed understanding of how conformational dynamics orchestrates function in allosteric regulation of recognition and catalysis remains ambiguous. Here, we simulate CypA using multiple-microsecond-long atomistic molecular dynamics in explicit solvent and carry out NMR experiments. We analyze a large amount of time-dependent multidimensional data with a coarse-grained approach and map key dynamical features within individual macrostates by defining dynamics in terms of residue–residue contacts. The effects of substrate binding are observed to be largely sensed at a location over 15 Å from the active site, implying its importance in allostery. Using NMR experiments, we confirm that a dynamic cluster of residues in this distal region is directly coupled to the active site. Furthermore, the dynamical network of interresidue contacts is found to be coupled and temporally dispersed, ranging over 4 to 5 orders of magnitude. Finally, using network centrality measures we demonstrate the changes in the communication network, connectivity, and influence of CypA residues upon substrate binding, mutation, and during catalysis. We identify key residues that potentially act as a bottleneck in the communication flow through the distinct regions in CypA and, therefore, as targets for future mutational studies. Mapping these dynamical features and the coupling of dynamics to function has crucial ramifications in understanding allosteric regulation in enzymes and proteins, in general.

scholarly journals Classification of protein–protein association rates based on biophysical informatics

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kalyani Dhusia ◽  
Yinghao Wu
Keyword(s):  
Large Scale ◽  
Cross Validation ◽  
Protein Complexes ◽  
Dynamic Properties ◽  
Conformational Dynamics ◽  
Classification Model ◽  
Coarse Grained ◽  
Modeling Framework ◽  
Validation Data ◽  
Wide Range

Abstract Background Proteins form various complexes to carry out their versatile functions in cells. The dynamic properties of protein complex formation are mainly characterized by the association rates which measures how fast these complexes can be formed. It was experimentally observed that the association rates span an extremely wide range with over ten orders of magnitudes. Identification of association rates within this spectrum for specific protein complexes is therefore essential for us to understand their functional roles. Results To tackle this problem, we integrate physics-based coarse-grained simulations into a neural-network-based classification model to estimate the range of association rates for protein complexes in a large-scale benchmark set. The cross-validation results show that, when an optimal threshold was selected, we can reach the best performance with specificity, precision, sensitivity and overall accuracy all higher than 70%. The quality of our cross-validation data has also been testified by further statistical analysis. Additionally, given an independent testing set, we can successfully predict the group of association rates for eight protein complexes out of ten. Finally, the analysis of failed cases suggests the future implementation of conformational dynamics into simulation can further improve model. Conclusions In summary, this study demonstrated that a new modeling framework that combines biophysical simulations with bioinformatics approaches is able to identify protein–protein interactions with low association rates from those with higher association rates. This method thereby can serve as a useful addition to a collection of existing experimental approaches that measure biomolecular recognition.

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.

scholarly journals Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications

2019 ◽  
Vol 20 (15) ◽  
pp. 3774 ◽  
Author(s):  
Nidhi Singh ◽  
Wenjin Li
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Self Assembly ◽  
Structure Prediction ◽  
Biological Systems ◽  
Conformational Dynamics ◽  
Multiscale Simulation ◽  
Coarse Grained ◽  
Hierarchical Level ◽  
Dynamics Simulations

Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.

scholarly journals Binding Dynamics of Disordered Linker Histone H1 with a Nucleosomal Particle

2020 ◽  
Author(s):  
Hao Wu ◽  
Yamini Dalal ◽  
Garegin A. Papoian
Keyword(s):  
Regulatory Protein ◽  
Conformational Dynamics ◽  
Histone H1 ◽  
Linker Histone ◽  
Coarse Grained ◽  
Globular Domain ◽  
Linker Histone H1 ◽  
Eukaryotic Chromatin ◽  
Cancer Phenotype ◽  
Terminal Domains

AbstractLinker histone H1 is an essential regulatory protein for many critical biological processes, such as eukaryotic chromatin packaging and gene expression. Mis-regulation of H1s is commonly observed in tumor cells, where the balance between different H1 subtypes has been shown to alter the cancer phenotype. Consisting of a rigid globular domain and two highly charged terminal domains, H1 can bind to multiple sites on a nucleosomal particle to alter chromatin hierarchical condensation levels. In particular, the disordered H1 amino- and carboxyl-terminal domains (NTD/CTD) are believed to enhance this binding affinity, but their detailed dynamics and functions remain unclear. In this work, we used a coarse-grained computational model AWSEM-DNA to simulate the H1.0b-nucleosome complex, namely chromatosome. Our results demonstrate that H1 disordered domains restrict the dynamics of both globular H1 and linker DNA arms, resulting in a more compact and rigid chromatosome particle. Furthermore, we identified regions of H1 disordered domains that are tightly tethered to DNA near the entry-exit site. Overall, our study elucidates at near atomic resolution the way the disordered linker histone H1 modulates nucleosome’s structural preferences and conformational dynamics.

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