Evidence map›Paper›PMID 22474570›Full record

ArticleToxins2012

Developing a comparative docking protocol for the prediction of peptide selectivity profiles: investigation of potassium channel toxins.

Po-Chia Chen, Serdar Kuyucak

Abstract read
In one paragraph

Article in Toxins, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. 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
  7. Review
  8. Biobetters From an Integrated Computational/Experimental Approach.Computational and structural biotechnology journal · 2017
    Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. 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.

Po-Chia ChenSchool of Physics, Building A28, University of Sydney, NSW 2006, Australia. poker@physics.usyd.edu.au
Serdar Kuyucak

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the development of selective peptides against highly homologous targets, a reliable tool is sought that can predict information on both mechanisms of binding and relative affinities. These tools must first be tested on known profiles before application on novel therapeutic candidates. We therefore present a comparative docking protocol in HADDOCK using critical motifs, and use it to "predict" the various selectivity profiles of several major αKTX scorpion toxin families versus K(v)1.1, K(v)1.2 and K(v)1.3. By correlating results across toxins of similar profiles, a comprehensive set of functional residues can be identified. Reasonable models of channel-toxin interactions can be then drawn that are consistent with known affinity and mutagenesis. Without biological information on the interaction, HADDOCK reproduces mechanisms underlying the universal binding of αKTX-2 toxins, and K(v)1.3 selectivity of αKTX-3 toxins. The addition of constraints encouraging the critical lysine insertion confirms these findings, and gives analogous explanations for other families, including models of partial pore-block in αKTX-6. While qualitatively informative, the HADDOCK scoring function is not yet sufficient for accurate affinity-ranking. False minima in low-affinity complexes often resemble true binding in high-affinity complexes, despite steric/conformational penalties apparent from visual inspection. This contamination significantly complicates energetic analysis, although it is usually possible to obtain correct ranking via careful interpretation of binding-well characteristics and elimination of false positives. Aside from adaptations to the broader potassium channel family, we suggest that this strategy of comparative docking can be extended to other channels of interest with known structure, especially in cases where a critical motif exists to improve docking effectiveness.

Indexed as

Amino Acid SequenceAnimalsBinding SitesComputer SimulationConotoxinsHydrogen BondingMiceModels, MolecularMolecular Sequence DataPeptidesPotassium Channel BlockersPotassium Channels, Voltage-GatedProtein BindingProtein ConformationRatsScorpion VenomsConotoxinsPeptidesPotassium Channel BlockersPotassium Channels, Voltage-GatedScorpion Venomscomparative dockingHADDOCKKv1.1Kv1.2Kv1.3protein-protein dockingscorpion toxinsselectivityα-KTx

Identifiers

PMID22474570
PMCPMC3317111

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Registered trials

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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.