AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Protein Aggregates

Showing 1 to 10 of 22 articles

Clear Filters

Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Molecular diversity
Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people worldwide characterized by cognitive decline and neurodegeneration. The accumulation of tau protein into paired helical filaments is one of the major ...

Label-free identification of protein aggregates using deep learning.

Nature communications
Protein misfolding and aggregation play central roles in the pathogenesis of various neurodegenerative diseases (NDDs), including Huntington's disease, which is caused by a genetic mutation in exon 1 of the Huntingtin protein (Httex1). The fluorescen...

Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning.

Nature chemical biology
Machine learning methods hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been ...

Exploring Tau Fibril-Disaggregating and Antioxidating Molecules Binding to Membrane-Bound Amyloid Oligomers Using Machine Learning-Enhanced Docking and Molecular Dynamics.

Molecules (Basel, Switzerland)
Intracellular tau fibrils are sources of neurotoxicity and oxidative stress in Alzheimer's. Current drug discovery efforts have focused on molecules with tau fibril disaggregation and antioxidation functions. However, recent studies suggest that memb...

Application of one-class classification using deep learning technique improves the classification of subvisible particles.

Journal of pharmaceutical sciences
Capturing subvisible particles using flow imaging microscopy is useful for evaluating protein aggregates that may induce immunogenicity. Automated labeling is desirable to distinguish harmless components such as silicone oil (SO) from subvisible part...

Particle formation in response to different protein formulations and containers: Insights from machine learning analysis of particle images.

Journal of pharmaceutical sciences
Subvisible particle count is a biotherapeutics stability indicator widely used by pharmaceutical industries. A variety of stresses that biotherapeutics are exposed to during development can impact particle morphology. By classifying particle morpholo...

Molecular Insights into α-Synuclein Fibrillation: A Raman Spectroscopy and Machine Learning Approach.

ACS chemical neuroscience
The aggregation of α-synuclein is crucial to the development of Lewy body diseases, including Parkinson's disease and dementia with Lewy bodies. The aggregation pathway of α-synuclein typically involves a defined sequence of nucleation, elongation, a...

Sulfonic acid functionalized β-amyloid peptide aggregation inhibitors and antioxidant agents for the treatment of Alzheimer's disease: Combining machine learning, computational, in vitro and in vivo approaches.

International journal of biological macromolecules
Alzheimer's disease (AD) is characterized as a neurodegenerative disorder that is caused by plaque formation by accumulating β-amyloid (Aβ), leading to neurocognitive function and impaired mental development. Thus, targeting Aβ represents a promising...

AggNet: Advancing protein aggregation analysis through deep learning and protein language model.

Protein science : a publication of the Protein Society
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...

Massive experimental quantification allows interpretable deep learning of protein aggregation.

Science advances
Protein aggregation is a pathological hallmark of more than 50 human diseases and a major problem for biotechnology. Methods have been proposed to predict aggregation from sequence, but these have been trained and evaluated on small and biased experi...