@article {Shekhar687087, author = {Mrinal Shekhar and Genki Terashi and Chitrak Gupta and Gaspard Debussche and Nicholas J. Sisco and Jonathan Nguyen and James Zook and John Vant and Daipayan Sarkar and Petra Fromme and Wade D. Van Horn and Ken Dill and Daisuke Kihara and Emad Tajkhorshid and Alberto Perez and Abhishek Singharoy}, title = {CryoFold: Ab-initio structure determination from electron density maps using molecular dynamics}, elocation-id = {687087}, year = {2019}, doi = {10.1101/687087}, publisher = {Cold Spring Harbor Laboratory}, 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{\textendash}5 {\r A} 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.}, URL = {https://www.biorxiv.org/content/early/2019/07/02/687087}, eprint = {https://www.biorxiv.org/content/early/2019/07/02/687087.full.pdf}, journal = {bioRxiv} }