ArticleMethods (San Diego, Calif.)2022
Multi-level analysis of intrinsically disordered protein docking methods.
Article in Methods (San Diego, Calif.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Peptide-protein docking: from physics-based models to generative intelligence.Chemical communications (Cambridge, England) · 2026Review
- New Approach for Targeting Small-Molecule Candidates for Intrinsically Disordered Proteins.Methods and protocols · 2025Article
- Sequence-Based Protein-Protein Interaction Prediction and Its Applications in Drug Discovery.Cells · 2025Review
- A deep learning method for predicting interactions for intrinsically disordered regions of proteins.bioRxiv : the preprint server for biology · 2025Article
- The "DDVF" motif used by viral and bacterial proteins to hijack RSK kinases mimics a short linear motif (SLiM) found in proteins related to the RAS-ERK MAP kinase pathway.PLoS pathogens · 2025Article
- Multimeric protein interaction and complex prediction: Structure, dynamics and function.Computational and structural biotechnology journal · 2025Review
- Molecular Docking of Intrinsically Disordered Proteins: Challenges and Strategies.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Characterization of Intrinsically Disordered Proteins in Healthy and Diseased States by Nuclear Magnetic Resonance.Reviews on recent clinical trials · 2024Review
- Assessment of Protein-Protein Docking Models Using Deep Learning.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Computational prediction of disordered binding regions.Computational and structural biotechnology journal · 2023Review
- AI-Based Protein Interaction Screening and Identification (AISID).International journal of molecular sciences · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Intrinsically Disordered Proteins (IDPs) are a class of proteins in which at least some region of the protein does not possess any stable structure in solution in the physiological condition but may adopt an ordered structure upon binding to a globular receptor. These IDP-receptor complexes are thus subject to protein complex modeling in which computational techniques are applied to accurately reproduce the IDP ligand-receptor interactions. This often exists in the form of protein docking, in which the 3D structures of both the subunits are known, but the position of the ligand relative to the receptor is not. Here, we evaluate the performance of three IDP-receptor modeling tools with metrics that characterize the IDP-receptor interface at various resolutions. We show that all three methods are able to properly identify the general binding site, as identified by lower resolution metrics, but begin to struggle with higher resolution metrics that capture biophysical interactions.
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Registered trials
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.