Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150624
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dc.contributor.authorZhang, Yuweien_US
dc.contributor.authorXia, Kelinen_US
dc.contributor.authorCao, Zexingen_US
dc.contributor.authorGräter, Fraukeen_US
dc.contributor.authorXia, Feien_US
dc.date.accessioned2021-08-04T02:12:08Z-
dc.date.available2021-08-04T02:12:08Z-
dc.date.issued2019-
dc.identifier.citationZhang, 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/c9cp01370aen_US
dc.identifier.issn1463-9076en_US
dc.identifier.urihttps://hdl.handle.net/10356/150624-
dc.description.abstractThe 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.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.description.sponsorshipNanyang Technological Universityen_US
dc.language.isoenen_US
dc.relationM4081842en_US
dc.relationRG126/16en_US
dc.relationRG31/18en_US
dc.relationMOE2018-T2-1-033en_US
dc.relation.ispartofPhysical Chemistry Chemical Physicsen_US
dc.rights© 2019 The Owner Societies. All rights reserved.en_US
dc.subjectScience::Chemistryen_US
dc.titleA new method for the construction of coarse-grained models of large biomolecules from low-resolution cryo-electron microscopy dataen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.contributor.schoolSchool of Biological Sciencesen_US
dc.identifier.doi10.1039/c9cp01370a-
dc.identifier.pmid31025999-
dc.identifier.scopus2-s2.0-85065966141-
dc.identifier.issue19en_US
dc.identifier.volume21en_US
dc.identifier.spage9720en_US
dc.identifier.epage9727en_US
dc.subject.keywordsAmino-acid-sequenceen_US
dc.subject.keywordsForce-fielden_US
dc.description.acknowledgementThis work was supported by the National Natural Science Foundation of China (Grants No. 21773065, 21433004, 21673185 and 21873078), Nanyang Technological University Startup Grant M4081842, Singapore Ministry of Education Academic Research fund Tier 1 RG126/16 and RG31/18, Tier 2 MOE2018-T2-1-033. F. G. acknowledges support by the Klaus Tschira Foundation and by an Experiment! grant of the Volkswagen Foundation. We acknowledge the support of the NYU-ECNU Center for Computational Chemistry at NYU Shanghai. We also thank the ECNU Public Platform for Innovation(001) for providing computer time. We thank Agnieszka Obarska-Kosinska for providing the collagen all-atom model to us.en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
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