Dataset Information

MarkovFit: Structure Fitting for Protein Complexes in Electron Microscopy Maps Using Markov Random Field.

ABSTRACT: An increasing number of protein complex structures are determined by cryo-electron microscopy (cryo-EM). When individual protein structures have been determined and are available, an important task in structure modeling is to fit the individual structures into the density map. Here, we designed a method that fits the atomic structures of proteins in cryo-EM maps of medium to low resolutions using Markov random fields, which allows probabilistic evaluation of fitted models. The accuracy of our method, MarkovFit, performed better than existing methods on datasets of 31 simulated cryo-EM maps of resolution 10 Å , nine experimentally determined cryo-EM maps of resolution less than 4 Å , and 28 experimentally determined cryo-EM maps of resolution 6 to 20 Å .

SUBMITTER: Alnabati E

PROVIDER: S-EPMC9358042 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

MarkovFit: Structure Fitting for Protein Complexes in Electron Microscopy Maps Using Markov Random Field.

Alnabati Eman E Esquivel-Rodriguez Juan J Terashi Genki G Kihara Daisuke D

Frontiers in molecular biosciences 20220725

An increasing number of protein complex structures are determined by cryo-electron microscopy (cryo-EM). When individual protein structures have been determined and are available, an important task in structure modeling is to fit the individual structures into the density map. Here, we designed a method that fits the atomic structures of proteins in cryo-EM maps of medium to low resolutions using Markov random fields, which allows probabilistic evaluation of fitted models. The accuracy of our me ...[more]

PMID: 35959463

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Project description:X-ray crystallography and cryo-electron microscopy (cryo-EM) are complementary techniques for structure determination. Crystallography usually reveals more detailed information, while cryo-EM is an extremely useful technique for studying large-sized macromolecules. As the gap between the resolution of crystallography and cryo-EM data narrows, the cryo-EM map of a macromolecule could serve as an initial model to solve the phase problem of crystal diffraction for high-resolution structure determination. FSEARCH is a procedure to utilize the low-resolution molecular shape for crystallographic phasing. The IPCAS (Iterative Protein Crystal structure Automatic Solution) pipeline is an automatic direct-methods-aided dual-space iterative phasing and model-building procedure. When only an electron-density map is available as the starting point, IPCAS is capable of generating a completed model from the phases of the input map automatically, without the requirement of an initial model. In this study, a hybrid method integrating X-ray crystallography with cryo-EM to help with structure determination is presented. With a cryo-EM map as the starting point, the workflow of the method involves three steps. (1) Cryo-EM map replacement: FSEARCH is utilized to find the correct translation and orientation of the cryo-EM map in the crystallographic unit cell and generates the initial low-resolution map. (2) Phase extension: the phases calculated from the correctly placed cryo-EM map are extended to high-resolution X-ray data by non-crystallographic symmetry averaging with phenix.resolve. (3) Model building: IPCAS is used to generate an initial model using the phase-extended map and perform model completion by iteration. Four cases (the lowest cryo-EM map resolution being 6.9 Å) have been tested for the general applicability of the hybrid method, and almost complete models have been generated for all test cases with reasonable Rwork/Rfree. The hybrid method therefore provides an automated tool for X-ray structure determination using a cryo-EM map as the starting point.

Dataset Information

MarkovFit: Structure Fitting for Protein Complexes in Electron Microscopy Maps Using Markov Random Field.

Publications

MarkovFit: Structure Fitting for Protein Complexes in Electron Microscopy Maps Using Markov Random Field.

Similar Datasets

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