Robust Heterogeneous Anisotropic Elastic Network Model Precisely Reproduces the Experimental B-factors of Biomolecules

Xia, Fei; Tong, Dudu; Lu, Lanyuan

doi:10.1021/ct4002575

Cited by 21 publications

(34 citation statements)

References 84 publications

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“…The normal modes of the protein of interest are then identified with the normal modes of the corresponding network of springs. Much effort has been put into finding the values of the force constants that provide a good agreement with experimental quantities, including our previous work on a PFM based HANM . Here, we focus on the construction of the EN.…”

Section: Resultsmentioning

confidence: 95%

“…As ANMs have been extensively validated against experiments, these results gave us confidence that our HANM captures reasonably well protein dynamics. We have shown for example that for the trypsin inhibitor (PDB ID: 5PTI) and for lysozyme (PDB ID: 2LZM), the two lowest modes of our HANM represent the slow conformational changes related to bending and twisting motions . We performed a similar analysis to assess the αHANM, with α = ∞ .…”

Section: Resultsmentioning

confidence: 99%

“…Although this puts this method ahead of methods like ANM and GNM, it is not the only one to do so. For example, we have shown recently that a PFM‐based HANM is also able to fit experimental B‐factors with high accuracies . We show here, that there is however, an advantage of using αHANM over HANM, especially for protein with irregular shapes.…”

Section: Resultsmentioning

confidence: 99%

“…By combining the construction of the EN based on the alpha shape theory with the progressive fluctuation matching (PFM) method proposed before, we show that we are able to derive alpha complex based HANM models to study protein dynamics that precisely reproduce experimental B‐factors. Although the heterogeneous anisotropic network model (HANM) depends on a cutoff distance, we note that the newly developed αHANM are free of such parameters. The article is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Identifying essential pairwise interactions in elastic network model using the alpha shape theory

et al. 2014

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Elastic network models (ENM) are based on the idea that the geometry of a protein structure provides enough information for computing its fluctuations around its equilibrium conformation. This geometry is represented as an elastic network (EN) that is, a network of links between residues. A spring is associated with each of these links. The normal modes of the protein are then identified with the normal modes of the corresponding network of springs. Standard approaches for generating ENs rely on a cutoff distance. There is no consensus on how to choose this cutoff. In this work, we propose instead to filter the set of all residue pairs in a protein using the concept of alpha shapes. The main alpha shape we considered is based on the Delaunay triangulation of the Cα positions; we referred to the corresponding EN as EN(∞). We have shown that heterogeneous anisotropic network models, called αHANMs, that are based on EN(∞) reproduce experimental B-factors very well, with correlation coefficients above 0.99 and root-mean-square deviations below 0.1 Å(2) for a large set of high resolution protein structures. The construction of EN(∞) is simple to implement and may be used automatically for generating ENs for all types of ENMs.

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Section: Resultsmentioning

confidence: 95%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identifying essential pairwise interactions in elastic network model using the alpha shape theory

et al. 2014

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“…The elastic constants can also be adjusted to have the fluctuations of the atoms of the molecule computed from the equations of motions given by Equation (7) to match the atomic fluctuations captured experimentally and usually reported as B-factors. Many methods have been developed for that purpose (see for example Xia et al, 2013, 2014 and references therein). Among those methods, the one proposed by Erman (2006) is worth discussing.…”

Section: Normal Mode Analysismentioning

confidence: 99%

Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids

Hsieh

Poitevin

Delarue

et al. 2016

Front. Mol. Biosci.

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Key steps in the life cycle of a virus, such as the fusion event as the virus infects a host cell and its maturation process, relate to an intricate interplay between the structure and the dynamics of its constituent proteins, especially those that define its capsid, much akin to an envelope that protects its genomic material. We present a comprehensive, comparative analysis of such interplay for the capsids of two viruses from the flaviviridae family, Dengue (DENV) and Zika (ZIKV). We use for that purpose our own software suite, DD-NMA, which is based on normal mode analysis. We describe the elements of DD-NMA that are relevant to the analysis of large systems, such as virus capsids. In particular, we introduce our implementation of simplified elastic networks and justify their parametrization. Using DD-NMA, we illustrate the importance of packing interactions within the virus capsids on the dynamics of the E proteins of DENV and ZIKV. We identify differences between the computed atomic fluctuations of the E proteins in DENV and ZIKV and relate those differences to changes observed in their high resolution structures. We conclude with a discussion on additional analyses that are needed to fully characterize the dynamics of the two viruses.

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A new algorithm for construction of coarse-grained sites of large biomolecules

Zhang

Xia

2015

J. Comput. Chem.

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The development of coarse-grained (CG) models for large biomolecules remains a challenge in multiscale simulations, including a rigorous definition of CG representations for them. In this work, we proposed a new stepwise optimization imposed with the boundary-constraint (SOBC) algorithm to construct the CG sites of large biomolecules, based on the s cheme of essential dynamics CG. By means of SOBC, we can rigorously derive the CG representations of biomolecules with less computational cost. The SOBC is particularly efficient for the CG definition of large systems with thousands of residues. The resulted CG sites can be parameterized as a CG model using the normal mode analysis based fluctuation matching method. Through normal mode analysis, the obtained modes of CG model can accurately reflect the functionally related slow motions of biomolecules. The SOBC algorithm can be used for the construction of CG sites of large biomolecules such as F-actin and for the study of mechanical properties of biomaterials.

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Robust Heterogeneous Anisotropic Elastic Network Model Precisely Reproduces the Experimental B-factors of Biomolecules

Cited by 21 publications

References 84 publications

Identifying essential pairwise interactions in elastic network model using the alpha shape theory

Identifying essential pairwise interactions in elastic network model using the alpha shape theory

Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids

A new algorithm for construction of coarse-grained sites of large biomolecules

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