Evidence map›Paper›PMID 22777874›Full record

ArticleProteins2012

Electrostatics of cysteine residues in proteins: parameterization and validation of a simple model.

Freddie R Salsbury, Leslie B Poole, Jacquelyn S Fetrow

Abstract read
In one paragraph

Article in Proteins, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

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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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
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.

Freddie R SalsburyDepartment of Physics, Wake Forest University, Winston-Salem, NC 27109, USA.
Leslie B Poole
Jacquelyn S Fetrow

Funding

Mechanistic Studies of Alkyl Hydroperoxide Reductase and Related Redox SystemsR01GM050389 · NIGMS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI POOLE, LESLIE B · 1994 to 2013
$4.8M
Proteomic Profiling of Cancer-Related Redox Signaling PathwaysR33CA126659 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI POOLE, LESLIE B · 2008 to 2010
$948k
NCI NIH HHS R33 CA126659NCI NIH HHS R33CA126659NIGMS NIH HHS R01 GM050389
6 · The paper itself

Abstract

One of the most popular and simple models for the calculation of pK(a) s from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pK(a) s. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pK(a) s; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pK(a) s. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pK(a) values (where the calculation should reproduce the pK(a) within experimental error). Both the general behavior of cysteines in proteins and the perturbed pK(a) in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pK(a) should be shifted, and validation of force field parameters for cysteine residues.

Indexed as

AnimalsCysteineDatabases, ProteinHumansModels, ChemicalMolecular Dynamics SimulationProteinsStatic ElectricityCysteineProteins

Identifiers

PMID22777874
PMCPMC3826958

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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.