Literature DB >> 33263324

Real-space quantum-based refinement for cryo-EM: Q|R#3.

Lum Wang1, Holger Kruse2, Oleg V Sobolev3, Nigel W Moriarty3, Mark P Waller4, Pavel V Afonine3, Malgorzata Biczysko1.   

Abstract

Electron cryo-microscopy (cryo-EM) is rapidly becoming a major competitor to X-ray crystallography, especially for large structures that are difficult or impossible to crystallize. While recent spectacular technological improvements have led to significantly higher resolution three-dimensional reconstructions, the average quality of cryo-EM maps is still at the low-resolution end of the range compared with crystallography. A long-standing challenge for atomic model refinement has been the production of stereochemically meaningful models for this resolution regime. Here, it is demonstrated that including accurate model geometry restraints derived from ab initio quantum-chemical calculations (HF-D3/6-31G) can improve the refinement of an example structure (chain A of PDB entry 3j63). The robustness of the procedure is tested for additional structures with up to 7000 atoms (PDB entry 3a5x and chain C of PDB entry 5fn5) using the less expensive semi-empirical (GFN1-xTB) model. The necessary algorithms enabling real-space quantum refinement have been implemented in the latest version of qr.refine and are described here.

Keywords:  cryo-EM; crystallography; phenix.comparama; protein; quantum refinement; real-space refinement

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Year:  2020        PMID: 33263324     DOI: 10.1107/S2059798320013194

Source DB:  PubMed          Journal:  Acta Crystallogr D Struct Biol        ISSN: 2059-7983            Impact factor:   7.652


  2 in total

1.  Macromolecular refinement of X-ray and cryoelectron microscopy structures with Phenix/OPLS3e for improved structure and ligand quality.

Authors:  Gydo C P van Zundert; Nigel W Moriarty; Oleg V Sobolev; Paul D Adams; Kenneth W Borrelli
Journal:  Structure       Date:  2021-04-05       Impact factor: 5.871

2.  Structural bases for aspartate recognition and polymerization efficiency of cyanobacterial cyanophycin synthetase.

Authors:  Takuya Miyakawa; Jian Yang; Masato Kawasaki; Naruhiko Adachi; Ayumu Fujii; Yumiko Miyauchi; Tomonari Muramatsu; Toshio Moriya; Toshiya Senda; Masaru Tanokura
Journal:  Nat Commun       Date:  2022-08-30       Impact factor: 17.694

  2 in total

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