Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150624
Title: A new method for the construction of coarse-grained models of large biomolecules from low-resolution cryo-electron microscopy data
Authors: Zhang, Yuwei
Xia, Kelin
Cao, Zexing
Gräter, Frauke
Xia, Fei
Keywords: Science::Chemistry
Issue Date: 2019
Source: Zhang, Y., Xia, K., Cao, Z., Gräter, F. & Xia, F. (2019). A new method for the construction of coarse-grained models of large biomolecules from low-resolution cryo-electron microscopy data. Physical Chemistry Chemical Physics, 21(19), 9720-9727. https://dx.doi.org/10.1039/c9cp01370a
Project: M4081842
RG126/16
RG31/18
MOE2018-T2-1-033
Journal: Physical Chemistry Chemical Physics
Abstract: The rapid development of cryo-electron microscopy (cryo-EM) has led to the generation of significant low-resolution electron density data of biomolecules. However, the atomistic details of huge biomolecules usually cannot be obtained because it is very difficult to construct all-atom models for MD simulations. Thus, it is still a challenge to make use of the rich low-resolution cryo-EM data for computer simulation and functional study. In this study, we proposed a new method called Convolutional and K-means Coarse-Graining (CK-CG) for the efficient coarse-graining of large biological systems. Using the CK-CG method, we could directly map the cryo-EM data into coarse-grained (CG) beads. Furthermore, the CG beads were parameterized with an empirical harmonic potential to construct a new CG model. We subjected the CK-CG models of the fibrillar protein assemblies F-actin and collagen to external forces in pulling dynamic simulations to assess their mechanical response. The agreement between the estimated tensile stiffness between CG models and experiments demonstrates the validity of the CK-CG method. Thus, our method provides a practical strategy for the direct construction of a structural model from low-resolution data for biological function studies.
URI: https://hdl.handle.net/10356/150624
ISSN: 1463-9076
DOI: 10.1039/c9cp01370a
Rights: © 2019 The Owner Societies. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

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