ReviewProtein science : a publication of the Protein Society2024
Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity.
Review in Protein science : a publication of the Protein Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- AGGRESCAN and its evolution: A two-decade perspective on protein aggregation prediction.Biophysical reviews · 2026Review
- Engineering mammalian protein secretion: Toward the convergence of high-throughput biology and computational methods.Cell systems · 2025Review
- Neurodegeneration Through the Lens of Bioinformatics Approaches: Computational Mechanisms of Protein Misfolding.International journal of molecular sciences · 2025Review
- STAGE: A compact and versatile TnpB-based genome editing toolkit forProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Natural Design of a Stabilized Cross-β Fold: Structure of the FuA FapC from Pseudomonas Sp. UK4 Reveals a Critical Role for Stacking of Imperfect Repeats.Advanced materials (Deerfield Beach, Fla.) · 2025Article
- Improving the solubility of single domain antibodies using VH-like hallmark residues.Protein science : a publication of the Protein Society · 2025Article
- Three scenarios for amyloid transformation in the context of the funnel model.Computational and structural biotechnology journal · 2025Article
- Aggregating amyloid resources: A comprehensive review of databases on amyloid-like aggregation.Computational and structural biotechnology journal · 2024Review
- Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity.Protein science : a publication of the Protein Society · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/.
Indexed as
Identifiers
What OpenQuestion holds
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.