ArticleScientific reports2020
Predicting binding sites from unbound versus bound protein structures.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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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.
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.
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Who cites it
18 citing papers in PubMed, 34 citations in OpenAlex.
- ViralBindPredict: empowering viral protein-ligand binding sites through deep learning and protein sequence-derived insights.GigaScience · 2026Article
- MVRBind: multi-view learning for RNA-small molecule binding site prediction.Briefings in bioinformatics · 2025Article
- Evaluation of Small-Molecule Binding Site Prediction Methods on Membrane-Embedded Protein Interfaces.Journal of chemical information and modeling · 2025Article
- Ligand-binding pockets in RNA and where to find them.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Non-hematopoietic erythropoietin splice variant is produced in the diseased human brain and confers neuroprotection.Frontiers in cellular neuroscience · 2025Article
- A review of machine learning-based methods for predicting drug-target interactions.Health information science and systems · 2024Review
- GraphBNC: Machine Learning-Aided Prediction of Interactions Between Metal Nanoclusters and Blood Proteins.Advanced materials (Deerfield Beach, Fla.) · 2024Article
- Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Integrated Molecular Modeling and Machine Learning for Drug Design.Journal of chemical theory and computation · 2023Review
- Article
- AlphaFold2 protein structure prediction: Implications for drug discovery.Current opinion in structural biology · 2023Review
- PDBspheres: a method for finding 3D similarities in local regions in proteins.NAR genomics and bioinformatics · 2022Article
- A structural biology community assessment of AlphaFold2 applications.Nature structural & molecular biology · 2022Article
- Membrane Lipids Are an Integral Part of Transmembrane Allosteric Sites in GPCRs: A Case Study of Cannabinoid CB1 Receptor Bound to a Negative Allosteric Modulator, ORG27569, and Analogs.Journal of medicinal chemistry · 2022Article
- Article
- Scoring Functions for Protein-Ligand Binding Affinity Prediction using Structure-Based Deep Learning: A Review.Frontiers in bioinformatics · 2022Article
- AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function.Journal of chemical information and modeling · 2021Article
- Benchmark Sets for Binding Hot Spot Identification in Fragment-Based Ligand Discovery.Journal of chemical information and modeling · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
We present the application of seven binding-site prediction algorithms to a meticulously curated dataset of ligand-bound and ligand-free crystal structures for 304 unique protein sequences (2528 crystal structures). We probe the influence of starting protein structures on the results of binding-site prediction, so the dataset contains a minimum of two ligand-bound and two ligand-free structures for each protein. We use this dataset in a brief survey of five geometry-based, one energy-based, and one machine-learning-based methods: Surfnet, Ghecom, LIGSITE
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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.