ArticleScientific reports2022
Structure-based assessment and druggability classification of protein-protein interaction sites.
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.
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Who cites it
18 citing papers in PubMed.
- Microglia-Specific Molecular Magnetic Resonance Imaging Probe Enables Noninvasive Separation of Parkinsonian Mice from Controls.bioRxiv : the preprint server for biology · 2026Article
- PL-PatchSurfer3: improved structure-based virtual screening for structure variation using 3D Zernike descriptors.Journal of cheminformatics · 2026Article
- Targeting "undruggable" cancer proteins: pharmacological challenges and emerging strategies.Translational cancer research · 2026Review
- In Silico Druggability Assessment ofAntibiotics (Basel, Switzerland) · 2026Article
- Protein structural dynamics in covalent drug design: insights from irreversible and reversible covalent inhibitors.RSC chemical biology · 2026Review
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- Computer-Aided Discovery of Drugs Against Chagas Disease.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Niraparib Demonstrates Therapeutic Potential in Multiple Sclerosis through Inhibition of IL-17A Receptor Interaction and Promotion of Remyelination.ACS chemical neuroscience · 2025Article
- Evaluating ligand docking methods for drugging protein-protein interfaces: insights from AlphaFold2 and molecular dynamics refinement.Journal of cheminformatics · 2025Article
- Structure-Based Discovery of Orthosteric Non-Peptide GLP-1R Agonists via Integrated Virtual Screening and Molecular Dynamics.International journal of molecular sciences · 2025Article
- Identification of Structurally Novel KRASJournal of medicinal chemistry · 2025Article
- Structural insights into Beclin 1 interactions with it's regulators for autophagy modulation.Computational and structural biotechnology journal · 2025Review
- Article
- Potential Inhibitors of Lumpy Skin Disease's Viral Protein (DNA Polymerase): A Combination of Bioinformatics Approaches.Animals : an open access journal from MDPI · 2024Article
- Physical-Chemical Features Selection Reveals That Differences in Dipeptide Compositions Correlate Most with Protein-Protein Interactions.bioRxiv : the preprint server for biology · 2024Article
- A computational and machine learning approach to identify GPR40-targeting agonists for neurodegenerative disease treatment.PloS one · 2024Article
- Comparative analysis of adhesion virulence protein FadA from gut-associated bacteria of colorectal cancer patients (Journal of Cancer · 2024Article
- Quantitative comparison of protein-protein interaction interface using physicochemical feature-based descriptors of surface patches.Frontiers in molecular biosciences · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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