Evidence map›Paper›PMID 35562538›Full record

ArticleScientific reports2022

Structure-based assessment and druggability classification of protein-protein interaction sites.

Lara Alzyoud, Richard A Bryce, Mohammad Al Sorkhy, Noor Atatreh, Mohammad A Ghattas

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. In Silico Druggability Assessment ofAntibiotics (Basel, Switzerland) · 2026
    Article
  5. Review
  6. Article
  7. Computer-Aided Discovery of Drugs Against Chagas Disease.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Identification of Structurally Novel KRASJournal of medicinal chemistry · 2025
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

5 authors.

Lara AlzyoudCollege of Pharmacy, Al Ain University, 64141, Abu Dhabi, United Arab Emirates.
Richard A BryceDivision of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
Mohammad Al SorkhyDepartment of Biology, University of Toronto, Toronto, ON, Canada.
Noor AtatrehCollege of Pharmacy, Al Ain University, 64141, Abu Dhabi, United Arab Emirates.
Mohammad A GhattasCollege of Pharmacy, Al Ain University, 64141, Abu Dhabi, United Arab Emirates. mohammad.ghattas@aau.ac.ae.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The featureless interface formed by protein-protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.

Indexed as

ProteinsBinding SitesLigandsProtein BindingLigandsProteins

Identifiers

PMID35562538
PMCPMC9106675

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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.