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Aggrescan3D: Structure-Based Protein Aggregation Prediction and Solubility Design
Aggrescan3D (A3D) predicts protein aggregation propensity from 3D structure and supports rational redesign of solubility. The standalone package was described by Aleksander Kuriata, Valentin Iglesias, Mateusz Kurcinski, Salvador Ventura and Sebastian Kmiecik of the University of Warsaw and Universitat Autonoma de Barcelona, in Bioinformatics (2019). It is distributed under the MIT license.
Protein aggregation affects the stability, solubility and developability of proteins, including therapeutic candidates. Sequence-only predictors cannot see which aggregation-prone residues are actually exposed in the folded structure. A3D works from the structure, and can also account for conformational fluctuations.
The standalone package upgrades the earlier A3D web server (Zambrano et al., 2015) with customizable options, automated analysis of multiple mutations and a framework for integration with other tools.
Property | Detail |
|---|---|
Required input | Protein structure in PDB format |
Modes | Static (input structure) and dynamic (CABS-flex models) |
Optional components | FoldX (optimization, mutation, stability) and CABS-flex (flexibility) |
Solvent accessibility | freeSASA by default, naccess optional |
Outputs | Per-residue A3D scores (CSV) and a score plot |
License | MIT |
How Aggrescan3D Predicts Aggregation From Structure
Structure input: the only required input is a PDB file.
Static mode: analyzes the input structure directly.
Dynamic mode: analyzes a set of CABS-flex models that reflect flexibility, to estimate how fluctuations change aggregation.
Stability integration: aggregation propensity can be combined with FoldX stability predictions.
Automated mutations: the tool identifies the strongest aggregation-prone regions and suggests point mutations expected to raise solubility without harming stability.
Aggrescan3D Outputs and Solubility Redesign
The main output is a CSV of per-residue A3D scores with a score plot. Optional outputs include optimized PDB files, CABS-flex models and score tables, and energy-difference files. The package includes a built-in local interface with interactive plots and 3D display.
What is Tamarind Bio?
Tamarind Bio is a no-code bioinformatics platform built to give life scientists and researchers access to powerful computational tools. Many cutting-edge machine learning models are hard to deploy and use. Tamarind provides an intuitive, web-based environment that removes the complexity of high-performance computing, software dependencies and command-line interfaces.
The platform is designed for biologists, chemists and other researchers who may not have a background in programming or cloud infrastructure but want to run models on their own data. Key features include:
A user-friendly graphical interface for setting up and launching experiments
A robust API for integration into existing research pipelines
An automated system for managing and scaling computational resources
Tamarind treats information and data security as a top priority, as detailed in its Trust Center and Terms of Service.
Accelerating Discovery with Aggrescan3D on Tamarind Bio
Aggregation hotspot mapping: locate aggregation-prone residues on a structure.
Solubility engineering: use automated mutation suggestions to improve solubility.
Flexibility-aware analysis: use dynamic mode to see how conformational fluctuations affect aggregation.
Stability trade-offs: weigh aggregation against FoldX stability estimates.
How to Use Aggrescan3D on Tamarind Bio
Log in: sign in at tamarind.bio and open the Aggrescan3D tool.
Provide a structure: upload a PDB file of your protein.
Choose the mode: static or dynamic, if exposed.
Set parameters: adjust options such as the solvent accessibility method or automated mutations, if exposed.
Run the job: submit and wait for completion.
Download outputs: save the per-residue score table and plot.
Interpret and iterate: inspect high-scoring regions and test suggested mutations experimentally.
Things to Keep in Mind
A PDB structure is required, so the tool cannot run on sequence alone.
Scores can differ slightly depending on options such as the solvent accessibility method.
Dynamic mode relies on CABS-flex and stability analysis on FoldX, both optional components.
The paper describes the standalone package as built for Python 2.7.
Source: Kuriata A, Iglesias V, Kurcinski M, Ventura S, Kmiecik S. Aggrescan3D standalone package for structure-based prediction of protein aggregation properties. Bioinformatics 35(19):3834-3835 (2019). DOI 10.1093/bioinformatics/btz143. Code: https://bitbucket.org/lcbio/aggrescan3d