Molecular replacement using structure predictions from databases

Simpkin, Adam J; Thomas, Jens M. H.; Šimkovic, Felix; Keegan, Ronan; Rigden, Daniel J.

doi:10.1107/s2059798319013962

Cited by 21 publications

(29 citation statements)

References 71 publications

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“…We postulated that increasing the sensitivity of the rotation search may result in even faster run times by way of the earlytermination function. SIMBAD had previously been modified to include an additional translation step to increase the sensitivity when screening ensembles derived from metagenomic databases (Simpkin et al, 2019). A few of the cases that took longer to run were tested with this method and demonstrated significant time reductions.…”

Section: Efficiency Improvementsmentioning

confidence: 99%

Using Phaser and ensembles to improve the performance of SIMBAD

Simpkin

Šimkovic

Thomas

et al. 2020

Acta Cryst Sect D Struct Biol

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Section: Efficiency Improvementsmentioning

confidence: 99%

Using Phaser and ensembles to improve the performance of SIMBAD

Simpkin

Šimkovic

Thomas

et al. 2020

Acta Cryst Sect D Struct Biol

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“…Ever since the conception of the Protein Data Bank (PDB) 1 , 2 and Genbank, 3 , 4 open access to standardized and searchable pools of experimental data has revolutionized scientific research. Constantly growing and improving in fidelity due to collaborative effort, 5 − 8 the now hundreds of databanks 9 fuel the data-driven development of biomolecular structure determination, 10 refinement, 11 prediction, 12 and design 13 approaches as well as the development of drugs, 14 , 15 materials, 16 , 17 and more. 18 , 19 It is clear that open data enables scientific progress that is far beyond the resources of a single research group or institute.…”

Section: Introductionmentioning

confidence: 99%

Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics

Antila

Ferreira

Ollila

et al. 2021

J. Chem. Inf. Model.

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Molecular dynamics (MD) simulations are widely used to monitor time-resolved motions of biomacromolecules, although it often remains unknown how closely the conformational dynamics correspond to those occurring in real life. Here, we used a large set of open-access MD trajectories of phosphatidylcholine (PC) lipid bilayers to benchmark the conformational dynamics in several contemporary MD models (force fields) against nuclear magnetic resonance (NMR) data available in the literature: effective correlation times and spin–lattice relaxation rates. We found none of the tested MD models to fully reproduce the conformational dynamics. That said, the dynamics in CHARMM36 and Slipids are more realistic than in the Amber Lipid14, OPLS-based MacRog, and GROMOS-based Berger force fields, whose sampling of the glycerol backbone conformations is too slow. The performance of CHARMM36 persists when cholesterol is added to the bilayer, and when the hydration level is reduced. However, for conformational dynamics of the PC headgroup, both with and without cholesterol, Slipids provides the most realistic description because CHARMM36 overestimates the relative weight of ∼1 ns processes in the headgroup dynamics. We stress that not a single new simulation was run for the present work. This demonstrates the worth of open-access MD trajectory databanks for the indispensable step of any serious MD study: benchmarking the available force fields. We believe this proof of principle will inspire other novel applications of MD trajectory databanks and thus aid in developing biomolecular MD simulations into a true computational microscope—not only for lipid membranes but for all biomacromolecular systems.

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“…The use of ab initio models as MR search models has seen some success, principally with α helix-rich proteins. 9 Accurate ab initio prediction of β-rich folds has long proven to be exceptionally challenging 10 due, in part, to the high proportion of non-local interactions between β-strands. To our knowledge only one β-rich crystal structure has previously been phased using an ab initio generated search model.…”

Section: Introductionmentioning

confidence: 99%

Crystallographic molecular replacement using an in silico‐generated search model of SARS‐CoV‐2 ORF8

Flower

Hurley

2021

Protein Science

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The majority of crystal structures are determined by the method of molecular replacement (MR). The range of application of MR is limited mainly by the need for an accurate search model. In most cases, pre-existing experimentally determined structures are used as search models. In favorable cases, ab initio predicted structures have yielded search models adequate for MR. The ORF8 protein of SARS-CoV-2 represents a challenging case for MR using an ab initio prediction because ORF8 has an all β-sheet fold and few orthologs. We previously determined experimentally the structure of ORF8 using the single anomalous dispersion (SAD) phasing method, having been unable to find an MR solution to the crystallographic phase problem. Following a report of an accurate prediction of the ORF8 structure, we assessed whether the predicted model would have succeeded as an MR search model. A phase problem solution was found, and the resulting structure was refined, yielding structural parameters equivalent to the original experimental solution.

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Molecular replacement using structure predictions from databases

Abstract: Predicted ab initio protein models from online databases are a useful supplement to the PDB for molecular replacement, but usually require nontrivial processing to succeed.

Cited by 21 publications

References 71 publications

Using Phaser and ensembles to improve the performance of SIMBAD

Using Phaser and ensembles to improve the performance of SIMBAD

Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics

Crystallographic molecular replacement using an in silico‐generated search model of SARS‐CoV‐2 ORF8

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