Evidence map›Paper›PMID 28921104›Full record

ReviewBiophysical reviews2017

Development of constant-pH simulation methods in implicit solvent and applications in biomolecular systems.

Fernando Luís Barroso daSilva, Luis Gustavo Dias

Abstract readReview
In one paragraph

Review in Biophysical reviews, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
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  9. Protein pJournal of chemical theory and computation · 2022
    Article
  10. Prediction of protein pChemical science · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. The journal of physical chemistry. B · 2019
    Article
  18. Article
  19. 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

2 authors.

Fernando Luís Barroso daSilvaDepartamento de Física e Química, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Av. do café, s/no. - Universidade de São Paulo, BR-14040-903, Ribeirão Preto, SP, Brazil. flbarroso@usp.br.ORCID http://orcid.org/0000-0003-2526-2085
Luis Gustavo DiasDepartamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Av. Bandeirantes, 3900 - Universidade de São Paulo, BR-14040-901, Ribeirão Preto, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

pH is a critical parameter for biological and technological systems directly related with electrical charges. It can give rise to peculiar electrostatic phenomena, which also makes them more challenging. Due to the quantum nature of the process, involving the forming and breaking of chemical bonds, quantum methods should ideally by employed. Nevertheless, due to the very large number of ionizable sites, different macromolecular conformations, salt conditions, and all other charged species, the CPU time cost simply becomes prohibitive for computer simulations, making this a quite complex problem. Simplified methods based on Monte Carlo sampling have been devised and will be reviewed here, highlighting the updated state-of-the-art of this field, advantages, and limitations of different theoretical protocols for biomolecular systems (proteins and nucleic acids). Following a historical perspective, the discussion will be associated with the applications to protein interactions with other proteins, polyelectrolytes, and nanoparticles.

Indexed as

Electrostatics interactionsMonte Carlo simulationspH effectsProtein titrationRNA titrationTanford and Kirkwood model

Identifiers

PMID28921104
PMCPMC5662048

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.