Evidence map›Paper›PMID 32432124›Full record

ReviewFrontiers in molecular biosciences2020

Bioinformatics and Biosimulations as Toolbox for Peptides and Peptidomimetics Design: Where Are We?

Ilda D'Annessa, Francesco Saverio Di Leva, Anna La Teana, Ettore Novellino, Vittorio Limongelli, Daniele Di Marino

Abstract readReview
In one paragraph

Review in Frontiers in molecular biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Molecular View on theJournal of chemical information and modeling · 2023
    Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. The development of ADAM10 endocytosis inhibitors for the treatment of Alzheimer's disease.Molecular therapy : the journal of the American Society of Gene Therapy · 2022
    Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Article
  19. 1,2,3-Triazoles as Biomimetics in Peptide Science.Molecules (Basel, Switzerland) · 2021
    Review
  20. 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

6 authors.

Ilda D'AnnessaIstituto di Chimica del Riconoscimento Molecolare, CNR, Milan, Italy.
Francesco Saverio Di LevaDepartment of Pharmacy, University of Naples Federico II, Naples, Italy.
Anna La TeanaDepartment of Life and Environmental Sciences, New York-Marche Structural Biology Center (NY-MaSBiC), Polytechnic University of Marche, Ancona, Italy.
Ettore NovellinoDepartment of Pharmacy, University of Naples Federico II, Naples, Italy.
Vittorio LimongelliDepartment of Pharmacy, University of Naples Federico II, Naples, Italy.
Daniele Di MarinoDepartment of Life and Environmental Sciences, New York-Marche Structural Biology Center (NY-MaSBiC), Polytechnic University of Marche, Ancona, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peptides and peptidomimetics are strongly re-emerging as amenable candidates in the development of therapeutic strategies against a plethora of pathologies. In particular, these molecules are extremely suitable to treat diseases in which a major role is played by protein-protein interactions (PPIs). Unlike small organic compounds, peptides display both a high degree of specificity avoiding secondary off-targets effects and a relatively low degree of toxicity. Further advantages are provided by the possibility to easily conjugate peptides to functionalized nanoparticles, so improving their delivery and cellular uptake. In many cases, such molecules need to assume a specific three-dimensional conformation that resembles the bioactive one of the endogenous ligand. To this end, chemical modifications are introduced in the polypeptide chain to constrain it in a well-defined conformation, and to improve the drug-like properties. In this context, a successful strategy for peptide/peptidomimetics design and optimization is to combine different computational approaches ranging from structural bioinformatics to atomistic simulations. Here, we review the computational tools for peptide design, highlighting their main features and differences, and discuss selected protocols, among the large number of methods available, used to assess and improve the stability of the functional folding of the peptides. Finally, we introduce the simulation techniques employed to predict the binding affinity of the designed peptides for their targets.

Indexed as

binding free-energybioinformatics toolspeptides designpeptidomimeticsprotein–protein interaction

Identifiers

PMID32432124
PMCPMC7214840

What OpenQuestion holds

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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.