Literature DB >> 28370077

Flexible fitting to cryo-EM density map using ensemble molecular dynamics simulations.

Osamu Miyashita1, Chigusa Kobayashi1, Takaharu Mori2,3, Yuji Sugita1,2,3,4, Florence Tama1,5.   

Abstract

Flexible fitting is a computational algorithm to derive a new conformational model that conforms to low-resolution experimental data by transforming a known structure. A common application is against data from cryo-electron microscopy to obtain conformational models in new functional states. The conventional flexible fitting algorithms cannot derive correct structures in some cases due to the complexity of conformational transitions. In this study, we show the importance of conformational ensemble in the refinement process by performing multiple fittings trials using a variety of different force constants. Application to simulated maps of Ca2+ ATPase and diphtheria toxin as well as experimental data of release factor 2 revealed that for these systems, multiple conformations with similar agreement with the density map exist and a large number of fitting trials are necessary to generate good models. Clustering analysis can be an effective approach to avoid over-fitting models. In addition, we show that an automatic adjustment of the biasing force constants during the fitting process, implemented as replica-exchange scheme, can improve the success rate.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  X-ray crystal structures; computational hybrid approach; cryo-EM density map; flexible fitting algorithm; replica exchange

Year:  2017        PMID: 28370077     DOI: 10.1002/jcc.24785

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  14 in total

1.  Frontiers in CryoEM Modeling.

Authors:  Giulia Palermo; Yuji Sugita; Willy Wriggers; Rommie E Amaro
Journal:  J Chem Inf Model       Date:  2019-06-13       Impact factor: 4.956

2.  Automated cryo-EM structure refinement using correlation-driven molecular dynamics.

Authors:  Maxim Igaev; Carsten Kutzner; Lars V Bock; Andrea C Vaiana; Helmut Grubmüller
Journal:  Elife       Date:  2019-03-04       Impact factor: 8.140

Review 3.  Hybrid methods for combined experimental and computational determination of protein structure.

Authors:  Justin T Seffernick; Steffen Lindert
Journal:  J Chem Phys       Date:  2020-12-28       Impact factor: 3.488

Review 4.  CryoEM-based hybrid modeling approaches for structure determination.

Authors:  C Keith Cassidy; Benjamin A Himes; Zaida Luthey-Schulten; Peijun Zhang
Journal:  Curr Opin Microbiol       Date:  2017-11-04       Impact factor: 7.934

5.  Efficient Flexible Fitting Refinement with Automatic Error Fixing for De Novo Structure Modeling from Cryo-EM Density Maps.

Authors:  Takaharu Mori; Genki Terashi; Daisuke Matsuoka; Daisuke Kihara; Yuji Sugita
Journal:  J Chem Inf Model       Date:  2021-06-18       Impact factor: 6.162

6.  Accurate flexible refinement of atomic models against medium-resolution cryo-EM maps using damped dynamics.

Authors:  Julio A Kovacs; Vitold E Galkin; Willy Wriggers
Journal:  BMC Struct Biol       Date:  2018-09-15

7.  Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.

Authors:  Sai Raghavendra Maddhuri Venkata Subramaniya; Genki Terashi; Daisuke Kihara
Journal:  Nat Methods       Date:  2019-07-29       Impact factor: 28.547

Review 8.  Tools for the cryo-EM gold rush: going from the cryo-EM map to the atomistic model.

Authors:  Doo Nam Kim; Karissa Y Sanbonmatsu
Journal:  Biosci Rep       Date:  2017-12-05       Impact factor: 3.840

9.  De novo main-chain modeling with MAINMAST in 2015/2016 EM Model Challenge.

Authors:  Genki Terashi; Daisuke Kihara
Journal:  J Struct Biol       Date:  2018-07-31       Impact factor: 2.867

10.  Searching for 3D structural models from a library of biological shapes using a few 2D experimental images.

Authors:  Sandhya P Tiwari; Florence Tama; Osamu Miyashita
Journal:  BMC Bioinformatics       Date:  2018-09-12       Impact factor: 3.169

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