Evidence map›Paper›PMID 23589832›Full record

ReviewPhysiological reviews2013

Computational methods of studying the binding of toxins from venomous animals to biological ion channels: theory and applications.

Dan Gordon, Rong Chen, Shin-Ho Chung

Abstract readReview
In one paragraph

Review in Physiological reviews, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Review
  2. Review
  3. In Silico Conotoxin Studies: Progress and Prospects.Molecules (Basel, Switzerland) · 2024
    Review
  4. Article
  5. Article
  6. The Kv1.3 KBiologia futura · 2021
    Review
  7. Article
  8. Identification ofToxins · 2019
    Article
  9. Review
  10. Article
  11. Review
  12. Complexes of Peptide Blockers with Kv1.6 Pore Domain: Molecular Modeling and Studies with KcsA-Kv1.6 Channel.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2017
    Article
  13. Review
  14. Biobetters From an Integrated Computational/Experimental Approach.Computational and structural biotechnology journal · 2017
    Review
  15. The Origin of Coupled Chloride and Proton Transport in a ClJournal of the American Chemical Society · 2016
    Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. 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.

Dan GordonResearch School of Biology, The Australian National University, Acton, ACT 0200, Australia. dan.gordon@anu.edu.au
Rong Chen
Shin-Ho Chung

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discovery of new drugs that selectively block or modulate ion channels has great potential to provide new treatments for a host of conditions. One promising avenue revolves around modifying or mimicking certain naturally occurring ion channel modulator toxins. This strategy appears to offer the prospect of designing drugs that are both potent and specific. The use of computational modeling is crucial to this endeavor, as it has the potential to provide lower cost alternatives for exploring the effects of new compounds on ion channels. In addition, computational modeling can provide structural information and theoretical understanding that is not easily derivable from experimental results. In this review, we look at the theory and computational methods that are applicable to the study of ion channel modulators. The first section provides an introduction to various theoretical concepts, including force-fields and the statistical mechanics of binding. We then look at various computational techniques available to the researcher, including molecular dynamics, brownian dynamics, and molecular docking systems. The latter section of the review explores applications of these techniques, concentrating on pore blocker and gating modifier toxins of potassium and sodium channels. After first discussing the structural features of these channels, and their modes of block, we provide an in-depth review of past computational work that has been carried out. Finally, we discuss prospects for future developments in the field.

Indexed as

Computer SimulationAnimalsHumansIon ChannelsModels, MolecularToxins, BiologicalVenomsIon ChannelsToxins, BiologicalVenoms

Identifiers

PMID23589832
PMCPMC3768100

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.