ArticleBioinformatics (Oxford, England)2022
A3D database: structure-based predictions of protein aggregation for the human proteome.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Prediction of human missense variant effects from functional evidence.Nature genetics · 2026Article
- AGGRESCAN and its evolution: A two-decade perspective on protein aggregation prediction.Biophysical reviews · 2026Review
- Neurodegeneration Through the Lens of Bioinformatics Approaches: Computational Mechanisms of Protein Misfolding.International journal of molecular sciences · 2025Review
- Prediction and Evaluation of Protein Aggregation with Computational Methods.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity.Protein science : a publication of the Protein Society · 2024Review
- Exploring protein functions from structural flexibility using CABS-flex modeling.Protein science : a publication of the Protein Society · 2024Review
- A3D Model Organism Database (A3D-MODB): a database for proteome aggregation predictions in model organisms.Nucleic acids research · 2024Article
- PatchProt: hydrophobic patch prediction using protein foundation models.Bioinformatics advances · 2024Article
- A3DyDB: exploring structural aggregation propensities in the yeast proteome.Microbial cell factories · 2023Article
- AlphaFold, Artificial Intelligence (AI), and Allostery.The journal of physical chemistry. B · 2022Review
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
summaryProtein aggregation is associated with many human disorders and constitutes a major bottleneck for producing therapeutic proteins. Our knowledge of the human protein structures repertoire has dramatically increased with the recent development of the AlphaFold (AF) deep-learning method. This structural information can be used to understand better protein aggregation properties and the rational design of protein solubility. This article uses the Aggrescan3D (A3D) tool to compute the structure-based aggregation predictions for the human proteome and make the predictions available in a database form. In the A3D database, we analyze the AF-predicted human protein structures (for over 20.5 thousand unique Uniprot IDs) in terms of their aggregation properties using the A3D tool. Each entry of the A3D database provides a detailed analysis of the structure-based aggregation propensity computed with A3D. The A3D database implements simple but useful graphical tools for visualizing and interpreting protein structure datasets. It also enables testing the influence of user-selected mutations on protein solubility and stability, all integrated into a user-friendly interface. AVAILABILITY AND IMPLEMENTATION: A3D database is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/hproteome. The data underlying this article are available in the article and in its online supplementary material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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