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CryoFold: Ab-initio structure determination from electron density maps using molecular dynamics

Mrinal Shekhar, Genki Terashi, Chitrak Gupta, Gaspard Debussche, Nicholas J. Sisco, Jonathan Nguyen, James Zook, John Vant, Daipayan Sarkar, Petra Fromme, Wade D. Van Horn, Ken Dill, Daisuke Kihara, Emad Tajkhorshid, Alberto Perez, Abhishek Singharoy
doi: https://doi.org/10.1101/687087
Mrinal Shekhar
Center for Biophysics and Quantitative Biology, Department of Biochemistry, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, 61801, USA
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Genki Terashi
Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
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Chitrak Gupta
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Center for Structural Discovery, Arizona State University, Tempe, AZ 85281, USA
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Gaspard Debussche
Department of Mathematics and Computer Sciences, Grenoble INP, 38000 Grenoble, France
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Nicholas J. Sisco
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Virginia G. Piper Center for Personalized Diagnostics, Arizona State University, Tempe, AZ 85281, USA
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Jonathan Nguyen
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Center for Structural Discovery, Arizona State University, Tempe, AZ 85281, USA
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James Zook
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Center for Structural Discovery, Arizona State University, Tempe, AZ 85281, USA
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John Vant
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Center for Structural Discovery, Arizona State University, Tempe, AZ 85281, USA
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Daipayan Sarkar
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USA
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Petra Fromme
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Center for Structural Discovery, Arizona State University, Tempe, AZ 85281, USA
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Wade D. Van Horn
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Virginia G. Piper Center for Personalized Diagnostics, Arizona State University, Tempe, AZ 85281, USA
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Ken Dill
Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, United States
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  • For correspondence: dill@laufercenter.org emad@life.illinois.edu dkihara@purdue.edu perez@chem.ufl.edu asinghar@asu.edu
Daisuke Kihara
Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USADepartment of Computer Science, Purdue University, West Lafayette, IN 47907, USA
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  • For correspondence: dill@laufercenter.org emad@life.illinois.edu dkihara@purdue.edu perez@chem.ufl.edu asinghar@asu.edu
Emad Tajkhorshid
Center for Biophysics and Quantitative Biology, Department of Biochemistry, NIH Center for Macromolecular Modeling and Bioinformatics, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, 61801, USA
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  • For correspondence: dill@laufercenter.org emad@life.illinois.edu dkihara@purdue.edu perez@chem.ufl.edu asinghar@asu.edu
Alberto Perez
Chemistry Department, University of Florida, Gainesville, Florida, 32611, USA
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  • For correspondence: dill@laufercenter.org emad@life.illinois.edu dkihara@purdue.edu perez@chem.ufl.edu asinghar@asu.edu
Abhishek Singharoy
The School of Molecular Sciences, Arizona State University, Tempe, AZ 85287, USAThe Biodesign Institute Center for Structural Discovery, Arizona State University, Tempe, AZ 85281, USA
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  • For correspondence: dill@laufercenter.org emad@life.illinois.edu dkihara@purdue.edu perez@chem.ufl.edu asinghar@asu.edu
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Abstract

Cryo-EM is a powerful method for determining biomolecular structures. But, unlike X-ray crystallography or solution-state NMR, which are data-rich, cryo-EM can be data-poor. Cryo-EM routinely gives electron density information to about 3–5 Å and the resolution often varies across the structure. So, it has been challenging to develop an automated computer algorithm that converts the experimental density maps to complete molecular structures. We address this challenge with CryoFold, a computational method that finds the chain trace from the density maps using MAINMAST, then performs molecular dynamics simulations using ReMDFF, a resolution-exchange flexible fitting protocol, accelerated by MELD, which uses low-information data to broaden the relevant conformational searching of secondary and tertiary structures. We describe four successes of structure determinations, including for membrane proteins and large molecules. CryoFold handles input data that is heterogeneous, and even sparse. The software is automated, and is available to the public via a python-based graphical user interface.

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Posted July 02, 2019.
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CryoFold: Ab-initio structure determination from electron density maps using molecular dynamics
Mrinal Shekhar, Genki Terashi, Chitrak Gupta, Gaspard Debussche, Nicholas J. Sisco, Jonathan Nguyen, James Zook, John Vant, Daipayan Sarkar, Petra Fromme, Wade D. Van Horn, Ken Dill, Daisuke Kihara, Emad Tajkhorshid, Alberto Perez, Abhishek Singharoy
bioRxiv 687087; doi: https://doi.org/10.1101/687087
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CryoFold: Ab-initio structure determination from electron density maps using molecular dynamics
Mrinal Shekhar, Genki Terashi, Chitrak Gupta, Gaspard Debussche, Nicholas J. Sisco, Jonathan Nguyen, James Zook, John Vant, Daipayan Sarkar, Petra Fromme, Wade D. Van Horn, Ken Dill, Daisuke Kihara, Emad Tajkhorshid, Alberto Perez, Abhishek Singharoy
bioRxiv 687087; doi: https://doi.org/10.1101/687087

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