ArticlePLoS computational biology2013
Druggable protein interaction sites are more predisposed to surface pocket formation than the rest of the protein surface.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- Rescuing the Function of Missense-Mutated Tumor SuppressorbioRxiv : the preprint server for biology · 2026Article
- Manifold-constrained nucleus-level denoising diffusion model for structure-based drug design.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Extending quantum-mechanical benchmark accuracy to biological ligand-pocket interactions.Nature communications · 2025Article
- From Concepts to Inhibitors: A Blueprint for Targeting Protein-Protein Interactions.Chemical reviews · 2025Review
- InDeepNet: a web platform for predicting functional binding sites in proteins using InDeep.Nucleic acids research · 2025Article
- Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots.Journal of chemical information and modeling · 2024Article
- Time dependent dihedral angle oscillations of the spike protein of SARS-CoV-2 reveal favored frequencies of dihedral angle rotations.Scientific reports · 2024Article
- Evolution of chemistry and selection technology for DNA-encoded library.Acta pharmaceutica Sinica. B · 2024Review
- FASTDock: A Pipeline for Allosteric Drug Discovery.Journal of chemical information and modeling · 2023Article
- Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling.Journal of chemical theory and computation · 2023Article
- Worth the weight: Sub-Pocket EXplorer (SubPEx), a weighted-ensemble method to enhance binding-pocket conformational sampling.bioRxiv : the preprint server for biology · 2023Article
- MAHOMES II: A webserver for predicting if a metal binding site is enzymatic.Protein science : a publication of the Protein Society · 2023Article
- MAHOMES II: A webserver for predicting if a metal binding site is enzymatic.bioRxiv : the preprint server for biology · 2023Article
- Detecting the PEX Like Domain of Matrix Metalloproteinase-14 (MMP-14) with Therapeutic Conjugated CNTs.Biosensors · 2022Article
- A cryptic pocket in Ebola VP35 allosterically controls RNA binding.Nature communications · 2022Article
- How does a small molecule bind at a cryptic binding site?PLoS computational biology · 2022Article
- Machine learning differentiates enzymatic and non-enzymatic metals in proteins.Nature communications · 2021Article
- Identification of a nanomolar affinity α-synuclein fibril imaging probe by ultra-high throughputChemical science · 2020Article
- Macromolecular modeling and design in Rosetta: recent methods and frameworks.Nature methods · 2020Review
- Investigating Cryptic Binding Sites by Molecular Dynamics Simulations.Accounts of chemical research · 2020Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Despite intense interest and considerable effort via high-throughput screening, there are few examples of small molecules that directly inhibit protein-protein interactions. This suggests that many protein interaction surfaces may not be intrinsically "druggable" by small molecules, and elevates in importance the few successful examples as model systems for improving our fundamental understanding of druggability. Here we describe an approach for exploring protein fluctuations enriched in conformations containing surface pockets suitable for small molecule binding. Starting from a set of seven unbound protein structures, we find that the presence of low-energy pocket-containing conformations is indeed a signature of druggable protein interaction sites and that analogous surface pockets are not formed elsewhere on the protein. We further find that ensembles of conformations generated with this biased approach structurally resemble known inhibitor-bound structures more closely than equivalent ensembles of unbiased conformations. Collectively these results suggest that "druggability" is a property encoded on a protein surface through its propensity to form pockets, and inspire a model in which the crude features of the predisposed pocket(s) restrict the range of complementary ligands; additional smaller conformational changes then respond to details of a particular ligand. We anticipate that the insights described here will prove useful in selecting protein targets for therapeutic intervention.
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