TCB Publications - Abstract

Yuhang Wang, Mrinal Shekhar, Darren Thifault, Christopher J Williams, Ryan Mcgreevy, Jane Richardson, Abhishek Singharoy, and Emad Tajkhorshid. Constructing atomic structural models into cryo-EM densities using molecular dynamics - pros and cons. Journal of Structural Biology, 204:319-328, 2018. (PMC: PMC6394829)

WANG2018-ET Accurate structure determination from electron density maps at 3-5 $\AA$ resolution necessitates a balance between extensive global and local sampling of atomistic models, yet with stereochemical correctness of backbone and sidechain geometries. Molecular Dynamics Flexible Fitting (MDFF), particularly through a resolution-exchange scheme, ReMDFF, provides a robust way of achieving this balance for hybrid structure determination. Employing two high-resolution density maps, namely that of $\beta$-galactosidase at 3.2 $\AA$ and TRPV1 at 3.4 $\AA$, we showcase the quality of ReMDFF-generated models, comparing them against ones submitted by independent research groups for the 2015-2016 Cryo-EM Model Challenge. This comparison offers a clear evaluation of ReMDFF’s strengths and shortcomings, and those of data-guided real-space refinements in general. ReMDFF results scored highly on the various metric for judging the quality-of-fit and quality-of-model. However, some systematic discrepancies are also noted employing a Molprobity analysis, that are reproducible across multiple competition entries. A space of key refinement parameters is explored within ReMDFF to observe their impact within the final model. Choice of force field parameters and initial model seem to have the most significant impact on ReMDFF model-quality. To this end, very recently developed CHARMM36m force field parameters provide now more refined ReMDFF models than the ones originally submitted to the Cryo-EM challenge. Finally, a set of good-practices is prescribed for the community to benefit from the MDFF developments.

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