BioinformaticsBioinformaticsPeer-reviewed journal article
A3D Database: Structure-based Protein Aggregation Predictions for the Human Proteome
Aleksandra Elzbieta Badaczewska-DawidiD, Javier García‐PardoiD, Aleksander Kuriata, Jordi PujolsiD, Salvador VenturaiD, Sebastian KmiecikiD
- Citations
- 14
- FWCI
- 0.90
- Field percentile
- top 31%
Abstract
MotivationProtein aggregation is associated with highly debilitating 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. ResultsHere, we present the A3D Database, in which we analyze the AF-predicted human protein structures (for over 17 thousand non-membrane proteins) 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. We discuss case studies illustrating how the database could be used to analyze physiologically relevant proteins. Furthermore, the database enables testing the influence of user-selected mutations on protein solubility and stability, all integrated into a user-friendly interface. Availability and implementationA3D Database is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/hproteome
- organism: human
- assay: protein structure
- research focus: database / resource
- approach: deep learning
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A3D 2.0 update for the prediction and optimization of protein solubility
Jordi Pujols, Valentín Iglesias, … Salvador Ventura·Methods in molecular biologyPeer-reviewed·Jan 1, 2022
- Protocols for rational design of protein solubility and aggregation properties using Aggrescan3D standalone
Aleksander Kuriata, Aleksandra Elzbieta Badaczewska-Dawid, … Sebastian Kmiecik·Methods in molecular biologyPeer-reviewed·Jan 1, 2022
- Prediction of Aggregation Prone Regions in Proteins Using Deep Neural Networks and Their Suppression by Computational Design
Vojtěch Cima, Antonín Kunka, … Jan Martinovič·bioRxiv·Mar 6, 2024
- Non-standard proteins in the lens of AlphaFold3 - a case study of amyloids
Alicja W. Wojciechowska, Jakub Wiktor Wojciechowski, … Małgorzata Kotulska·Scientific ReportsPeer-reviewed·Sep 3, 2026
- SOLart: a structure-based method to predict protein solubility and aggregation
Qingzhen Hou, Jean Marc Kwasigroch, … Fabrizio Pucci·BioinformaticsPeer-reviewed·Oct 8, 2019
- Amylo-Pipe: an integrated web server for mechanistic and kinetic prediction of protein and peptide aggregation
Puneet Rawat, R. Prabakaran, … M. Michael Gromiha·bioRxiv·Jun 12, 2026