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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

PDFDOIPreprint
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

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