Evidence map›Paper›PMID 33639766›Full record

ArticleThe Journal of chemical physics2021

Microsecond dynamics in proteins by two-dimensional ESR. II. Addressing computational challenges.

Pranav Gupta, Kevin Chaudhari, Jack H Freed

Open access · greenAbstract read
In one paragraph

Article in The Journal of chemical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Pranav GuptaNational Biomedical Center for Advanced ESR Technology and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA.ORCID 0000000214120885
Kevin ChaudhariDepartment of Computer Science, Cornell University, Ithaca, New York 14853, USA.ORCID 0000000184995161
Jack H FreedNational Biomedical Center for Advanced ESR Technology and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA.ORCID 0000000342882585
Cornell University · US

Funding

TR&D 4 for ACERT, 2017-2021 funding periodP41GM103521 · NIGMS · CORNELL UNIVERSITY · PI FREED, JACK H · 2012 to 2021
$11.7M
NIGMS NIH HHS P41 GM103521
6 · The paper itself

Abstract

Two-dimensional electron-electron double resonance (2D-ELDOR) provides extensive insight into molecular motions. Recent developments permitting experiments at higher frequencies (95 GHz) provide molecular orientational resolution, enabling a clearer description of the nature of the motions. In previous work, we provided simulations for the case of domain motions within proteins that are themselves slowly tumbling in a solution. In order to perform these simulations, it was found that the standard approach of solving the relevant stochastic Liouville equation using the efficient Lanczos algorithm for this case breaks down, so algorithms were employed that rely on the Arnoldi iteration. While they lead to accurate simulations, they are very time-consuming. In this work, we focus on a variant known as the rational Arnoldi algorithm. We show that this can achieve a significant reduction in computation time. The stochastic Liouville matrix, which is of very large dimension, N, is first reduced to a much smaller dimension, m, e.g., from N ∼ O(10

Indexed as

AlgorithmsMolecular Dynamics SimulationElectron Spin Resonance SpectroscopyProteinsStochastic ProcessesTime FactorsProteins

Identifiers

PMID33639766
PMCPMC7928224
OpenAlexW3130893036

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.