scholarly journals Optimal Coarse-Grained Site Selection in Elastic Network Models of Biomolecules

2018 ◽  
Vol 15 (1) ◽  
pp. 648-664 ◽  
Author(s):  
Patrick Diggins ◽  
Changjiang Liu ◽  
Markus Deserno ◽  
Raffaello Potestio
Keyword(s):  
Site Selection ◽  
Network Models ◽  
Coarse Grained ◽  
Elastic Network ◽  
Elastic Network Models

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 Bridging between NMA and Elastic Network Models: Preserving All-Atom Accuracy in Coarse-Grained Models

2015 ◽  
Vol 11 (10) ◽  
pp. e1004542 ◽  
Author(s):  
Hyuntae Na ◽  
Robert L. Jernigan ◽  
Guang Song
Keyword(s):  
Network Models ◽  
Coarse Grained ◽  
Elastic Network ◽  
Elastic Network Models

scholarly journals Modeling of Protein Structural Flexibility and Large-Scale Dynamics: Coarse-Grained Simulations and Elastic Network Models

2018 ◽  
Vol 19 (11) ◽  
pp. 3496 ◽  
Author(s):  
Sebastian Kmiecik ◽  
Maksim Kouza ◽  
Aleksandra Badaczewska-Dawid ◽  
Andrzej Kloczkowski ◽  
Andrzej Kolinski
Keyword(s):  
Structure Prediction ◽  
Large Scale ◽  
Dynamic Properties ◽  
Experimental Studies ◽  
Network Models ◽  
Conformational Transitions ◽  
Conformational Space ◽  
Coarse Grained ◽  
Elastic Network ◽  
Elastic Network Models

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this minireview, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions, and highly simplified structure-based elastic network models of protein flexibility. In contrast to classical all-atom molecular dynamics, the modeling strategies discussed here allow the quite accurate modeling of much larger systems and longer-time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.

scholarly journals Free energies for coarse-grained proteins by integrating multibody statistical contact potentials with entropies from elastic network models

2011 ◽  
Vol 12 (2) ◽  
pp. 137-147 ◽  
Author(s):  
Michael T. Zimmermann ◽  
Sumudu P. Leelananda ◽  
Pawel Gniewek ◽  
Yaping Feng ◽  
Robert L. Jernigan ◽  
...  
Keyword(s):  
Network Models ◽  
Coarse Grained ◽  
Free Energies ◽  
Elastic Network ◽  
Elastic Network Models

scholarly journals Coarse-Grained Protein Dynamics Studies Using Elastic Network Models

2018 ◽  
Vol 19 (12) ◽  
pp. 3899 ◽  
Author(s):  
Yuichi Togashi ◽  
Holger Flechsig
Keyword(s):  
Normal Mode Analysis ◽  
Protein Structures ◽  
Computational Cost ◽  
Network Models ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Nonlinear Phenomena ◽  
Reference Structure ◽  
Elastic Network ◽  
Elastic Network Models

Elastic networks have been used as simple models of proteins to study their slow structural dynamics. They consist of point-like particles connected by linear Hookean springs and hence are convenient for linear normal mode analysis around a given reference structure. Furthermore, dynamic simulations using these models can provide new insights. As the computational cost associated with these models is considerably lower compared to that of all-atom models, they are also convenient for comparative studies between multiple protein structures. In this review, we introduce examples of coarse-grained molecular dynamics studies using elastic network models and their derivatives, focusing on the nonlinear phenomena, and discuss their applicability to large-scale macromolecular assemblies.

scholarly journals Modeling of Protein Structural Flexibility and Large-Scale Dynamics: Coarse-grained Simulations and Elastic Network Models

2018 ◽  
Author(s):  
Sebastian Kmiecik ◽  
Maksim Kouza ◽  
Aleksandra Elzbieta Badaczewska-Dawid ◽  
Andrzej Kloczkowski ◽  
Andrzej Kolinski
Keyword(s):  
Structure Prediction ◽  
Large Scale ◽  
Dynamic Properties ◽  
Experimental Studies ◽  
Network Models ◽  
Conformational Transitions ◽  
Conformational Space ◽  
Coarse Grained ◽  
Elastic Network ◽  
Elastic Network Models

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this mini-review, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions and, on other hand, highly simplified structure-based Elastic Network Models of protein flexibility. In contrast to classical Molecular Dynamics the modeling strategies discussed here allow quite accurate modeling of much larger systems and longer time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.

Sign in / Sign up

Export Citation Format

Share Document