AIMC Topic: Protein Aggregates

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Modulation of insulin aggregation by betaine and proline directly observed via real-time super-resolution microscopy.

Protein science : a publication of the Protein Society Jun 1, 2025
Protein aggregation is associated with a spectrum of neurodegenerative diseases. Although many small ligands have been found to modulate or inhibit protein aggregation, their molecular mechanisms remain unclear. One reason for this is the inherent he...
Humans Animals Insulin Kinetics Proline Protein Aggregates Betaine
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Assessing amyloid fibrils and amorphous aggregates: A review.

International journal of biological macromolecules Jun 1, 2025
Protein misfolding and aggregation play a central role in the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's. These aggregates manifest either as structured amyloid fibrils enriched in β-sheet conformations or as irregu...
Humans Animals Amyloid Protein Aggregates Protein Aggregation, Pathological
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AggNet: Advancing protein aggregation analysis through deep learning and protein language model.

Protein science : a publication of the Protein Society Feb 1, 2025
Protein aggregation is critical to various biological and pathological processes. Besides, it is also an important property in biotherapeutic development. However, experimental methods to profile protein aggregation are costly and labor-intensive, dr...
Humans Deep Learning Proteins Models, Molecular Protein Aggregates
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Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics.

mAbs Jan 1, 2022
Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this...
Humans Machine Learning Antibodies, Monoclonal Molecular Dynamics Simulation Viscosity Protein Aggregates
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Calculation of therapeutic antibody viscosity with coarse-grained models, hydrodynamic calculations and machine learning-based parameters.

mAbs Jan 1, 2021
High viscosity presents a challenge for manufacturing and drug delivery of therapeutic antibodies. The viscosity is determined by protein-protein interactions among many antibodies. Molecular simulation is a promising method to study protein-protein ...
Machine Learning Protein Binding Antibodies, Monoclonal Molecular Dynamics Simulation Motion Drug Compounding Viscosity Protein Aggregates Hydrodynamics
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Prediction of amyloid aggregation rates by machine learning and feature selection.

The Journal of chemical physics Aug 28, 2019
A novel data-based machine learning algorithm for predicting amyloid aggregation rates is reported in this paper. Based on a highly nonlinear projection from 16 intrinsic features of a protein and 4 extrinsic features of the environment to the protei...
Neural Networks, Computer Machine Learning Kinetics Amyloid Protein Aggregates
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