De Novo Modeling in Cryo-EM Density Maps with Pathwalking

By Muyuan Chen, Philip Baldwin, Steven J. Ludtke, Matthew L. Baker. 2016

69 citations recorded by the source corpus.

As electron cryo-microscopy(cryo-EM) can now frequently achieve near atomic resolution, accurate interpretation of these density maps in terms of atomistic detail has become paramount in deciphering macromolecular structure and function. However, there are few software tools for modeling protein structure from cryo-EM density maps in this resolution range. Here, we present an extension of our original Pathwalking protocol, which can automatically trace a protein backbone directly from a near-atomic resolution (3 – 6 Å) density map. The original Pathwalking approach utilized a Traveling Salesman Problem solver for backbone tracing, but manual adjustment was still required during modeling. In the new version, human intervention is minimized and we provide a more robust approach for backbone modeling. This includes iterative secondary structure identification, termini detection and the ability to model multiple subunits without prior segmentation. Overall, the new Pathwalking procedure provides a more complete and robust tool for annotating protein structure function in near-atomic resolution density maps.

Subfields: Materials Chemistry, Molecular Biology, Structural Biology

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Citations in the corpus

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix (2019, methodology): “(vii) Cryo-EM model building with Pathwalker (Baker et al., 2012; Chen et al., 2016) will soon be available within Phenix.”
Integrating model simulation tools and cryo‐electron microscopy (2022, methodology): “Pathwalking 88 is a semi-automated template-free protocol to enumerate C α models from 3.5 to 6 Å resolution density maps.”
Cryo-EM targets in CASP13: overview and evaluation of results (2019, background): “However, in practice evenmodels built on such well-resolved maps are not void of structural inconsistencies or errors.(23,28) In this section, we analyzewhether CASPmodels, which are built without the knowledge of the cryo-EM density, agree with the density, and compare their goodness-of-fit with th”
Current approaches for automated model building into cryo-EM maps using Buccaneer with CCP-EM (2020, methodology): “…and the development of new model-building tools to interpret cryo-EM maps (Cowtan, 2008; Baker et al., 2012; Brown et al., 2015; Wang et al., 2015; Chen et al., 2016; Zhou et al., 2017; Terwilliger, Adams et al., 2018; Terashi & Kihara, 2018; Afonine, Poon et al., 2018; Chojnowski et al., 2018;…”