Evidence map›Paper›PMID 31692475›Full record

ArticleActa crystallographica. Section D, Structural biology2019

Toward the computational design of protein crystals with improved resolution.

Jeliazko R Jeliazkov, Aaron C Robinson, Bertrand García-Moreno E, James M Berger, Jeffrey J Gray

Abstract read
In one paragraph

Article in Acta crystallographica. Section D, Structural biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Redefining Protein Interfaces within Protein Single Crystals with DNA.Journal of the American Chemical Society · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jeliazko R JeliazkovProgram in Molecular Biophysics, Johns Hopkins University, Baltimore, Maryland, USA.
Aaron C RobinsonT. C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland, USA.
Bertrand García-Moreno EProgram in Molecular Biophysics, Johns Hopkins University, Baltimore, Maryland, USA.
James M BergerProgram in Molecular Biophysics, Johns Hopkins University, Baltimore, Maryland, USA.
Jeffrey J GrayProgram in Molecular Biophysics, Johns Hopkins University, Baltimore, Maryland, USA.

Funding

PROGRAM IN MOLECULAR BIOPHYSICST32GM008403 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BARRICK, DOUGLAS E. · 1990 to 2019
$13.5M
Prediction of the Structure of Therapeutic Antibodies with their AntigensR01GM078221 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI GRAY, JEFFREY J · 2006 to 2020
$4.0M
Computational Design of Crystal Lattice Interactions to Determine Recalcitrant Protein StructuresF31GM123616 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI JELIAZKOV, JELIAZKO · 2017 to 2018
$81k
National Institutes of Health, National Institute of General Medical Sciences F31-GM123616National Institutes of Health, National Institute of General Medical Sciences R01-GM078221National Institutes of Health, National Institute of General Medical Sciences T32-GM008403National Science Foundation NSF-MCB 1517378NIGMS NIH HHS F31 GM123616NIGMS NIH HHS R01 GM078221NIGMS NIH HHS T32 GM008403Office of the Provost, Johns Hopkins University Discovery Award
6 · The paper itself

Abstract

Substantial advances have been made in the computational design of protein interfaces over the last 20 years. However, the interfaces targeted by design have typically been stable and high-affinity. Here, we report the development of a generic computational design method to stabilize the weak interactions at crystallographic interfaces. Initially, we analyzed structures reported in the Protein Data Bank to determine whether crystals with more stable interfaces result in higher resolution structures. We found that for 22 variants of a single protein crystallized by a single individual, the Rosetta-calculated `crystal score' correlates with the reported diffraction resolution. We next developed and tested a computational design protocol, seeking to identify point mutations that would improve resolution in a highly stable variant of staphylococcal nuclease (SNase). Using a protocol based on fixed protein backbones, only one of the 11 initial designs crystallized, indicating modeling inaccuracies and forcing us to re-evaluate our strategy. To compensate for slight changes in the local backbone and side-chain environment, we subsequently designed on an ensemble of minimally perturbed protein backbones. Using this strategy, four of the seven designed proteins crystallized. By collecting diffraction data from multiple crystals per design and solving crystal structures, we found that the designed crystals improved the resolution modestly and in unpredictable ways, including altering the crystal space group. Post hoc, in silico analysis of the three observed space groups for SNase showed that the native space group was the lowest scoring for four of six variants (including the wild type), but that resolution did not correlate with crystal score, as it did in the preliminary results. Collectively, our results show that calculated crystal scores can correlate with reported resolution, but that the correlation is absent when the problem is inverted. This outcome suggests that more comprehensive modeling of the crystallographic state is necessary to design high-resolution protein crystals from poorly diffracting crystals.

Indexed as

Bacterial ProteinsCrystallography, X-RayDatabases, ProteinDatasets as TopicMicrococcal NucleaseModels, MolecularProtein ConformationBacterial ProteinsMicrococcal Nucleaseprotein crystallographyprotein designRosettastaphylococcal nuclease

Identifiers

PMID31692475
PMCPMC6834074

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.