Iterative Molecular Dynamics-Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities

被引:26
|
作者
Leelananda, Sumudu P. [1 ]
Lindert, Steffen [1 ]
机构
[1] Ohio State Univ, Dept Chem & Biochem, Columbus, OH 43210 USA
关键词
NMR CHEMICAL-SHIFTS; STRUCTURE PREDICTION; CRYOELECTRON MICROSCOPY; STRUCTURE VALIDATION; DATA-BANK; RESOLUTION; MODELS; ASSEMBLIES; MOLPROBITY; RESTRAINTS;
D O I
10.1021/acs.jctc.7b00464
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Knowing atomistic details of proteins is essential not only for the understanding of protein function but also for the development of drugs. Experimental methods such as X-ray crystallography, NMR, and cryo-electron microscopy (cryo-EM) are the preferred forms of protein structure determination and have achieved great success over the most recent decades. Computational methods may be an alternative when experimental techniques fail. However, computational methods are severely limited when it comes to predicting larger macromolecule structures with little sequence similarity to known structures. The incorporation of experimental restraints in computational methods is becoming increasingly important to more reliably predict protein structure. One such experimental input used in structure prediction and refinement is cryo-EM densities. Recent advances in cryo-EM have arguably revolutionized the field of structural biology. Our previously developed cryo-EM-guided Rosetta MD protocol has shown great promise in the refinement of soluble protein structures. In this' study, we extended cryo-EM density-guided iterative Rosetta-MD to membrane proteins. We also improved the methodology in general by picking models based on a combination of their score and fit-to-density during the Rosetta model selection. By doing so, we have been able to pick models superior to those with the previous selection based on Rosetta score only and we have been able to further improve our previously refined models of soluble proteins. The method was tested with five membrane spanning protein structures. By applying density-guided Rosetta-MD iteratively we were able to refine the predicted structures of these membrane proteins to atomic resolutions. We also showed that the resolution of the density maps determines the improvement and quality of the refined models. By incorporating high-resolution density maps (similar to 4 angstrom), we were able to more significantly improve the quality of the models than when medium-resolution maps (6.9 angstrom) were used. Beginning from an average starting structure root mean square deviation (RMSD) to native of 4.66 angstrom, our protocol was able to refine the structures to bring the average refined structure RMSD to 1.66 angstrom when 4 angstrom density maps were used. The protocol also successfully refined the HIV-1 CTD guided by an experimental 5 angstrom density map.
引用
收藏
页码:5131 / 5145
页数:15
相关论文
共 50 条
  • [31] Cryo-EM structure of the ClpXP protein degradation machinery
    Gatsogiannis, Christos
    Balogh, Dora
    Merino, Felipe
    Sieber, Stephan A.
    Raunser, Stefan
    NATURE STRUCTURAL & MOLECULAR BIOLOGY, 2019, 26 (10) : 946 - +
  • [32] Predicting protein structure from cryo-EM data
    Chirigati, Fernando
    NATURE COMPUTATIONAL SCIENCE, 2021, 1 (02): : 96 - 96
  • [33] Structure and dynamics of an archetypal DNA nanoarchitecture revealed via cryo-EM and molecular dynamics simulations
    Ahmad, Katya
    Javed, Abid
    Lanphere, Conor
    Coveney, Peter V.
    Orlova, Elena V.
    Howorka, Stefan
    NATURE COMMUNICATIONS, 2023, 14 (01)
  • [34] Structure and dynamics of an archetypal DNA nanoarchitecture revealed via cryo-EM and molecular dynamics simulations
    Katya Ahmad
    Abid Javed
    Conor Lanphere
    Peter V. Coveney
    Elena V. Orlova
    Stefan Howorka
    Nature Communications, 14
  • [35] Predicting protein structure from cryo-EM data
    Fernando Chirigati
    Nature Computational Science, 2021, 1 : 96 - 96
  • [36] The Protein Fusion Strategy Facilitates the Structure Determination of Small Membrane Proteins by Cryo-EM
    Cui, Wenhao
    Niu, Yange
    Chen, Lei
    BIOCHEMISTRY, 2023, 62 (02) : 196 - 200
  • [37] Cryo-EM structure of lysenin pore elucidates membrane insertion by an aerolysin family protein
    Monika Bokori-Brown
    Thomas G. Martin
    Claire E. Naylor
    Ajit K. Basak
    Richard W. Titball
    Christos G. Savva
    Nature Communications, 7
  • [38] Cryo-EM structure of lysenin pore elucidates membrane insertion by an aerolysin family protein
    Bokori-Brown, Monika
    Martin, Thomas G.
    Naylor, Claire E.
    Basak, Ajit K.
    Titball, Richard W.
    Savva, Christos G.
    NATURE COMMUNICATIONS, 2016, 7
  • [39] Cryo-EM structure of the gasdermin A3 membrane pore
    Ruan, Jianbin
    Xia, Shiyu
    Liu, Xing
    Lieberman, Judy
    Wu, Hao
    NATURE, 2018, 557 (7703) : 62 - +
  • [40] Cryo-EM Structure of the BK Ion Channel in a Lipid Membrane
    Wang, Liguo
    Tonggu, Lige
    Zhan, Xi
    BIOPHYSICAL JOURNAL, 2016, 110 (03) : 186A - 186A