AIMC Topic: Proteins

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GENEOnet: a breakthrough in protein binding pocket detection using group equivariant non-expansive operators.

Scientific reports
Structure-based virtual screening approaches like molecular docking rely on accurately identifying and precisely calculating binding pockets to efficiently search for potential ligands. In this paper, we introduce GENEOnet, a machine learning model d...

SARST2 high-throughput and resource-efficient protein structure alignment against massive databases.

Nature communications
The flood of protein structural Big Data is coming. With the belief that biotech researchers deserve powerful analysis engines to overcome the challenge of rapidly increasing computational demands, we are devoted to developing efficient protein struc...

A comprehensive application of FiveFold for conformation ensemble-based protein structure prediction.

Scientific reports
The emergence of artificial intelligence in protein structure prediction has significantly advanced our understanding of protein folding. Yet, challenges remain in accurately modeling intrinsically disordered proteins (IDPs) and capturing conformatio...

Scalable deep learning reconstruction for accelerated multidimensional nuclear magnetic resonance spectroscopy of proteins.

Science advances
High-dimensional nuclear magnetic resonance (NMR) spectroscopy can assist in determining protein structure, but it requires time-consuming acquisition. Deep learning enables ultrafast reconstruction but is limited to spectra of up to three dimensions...

Physics-informed deep learning for plasmonic sensing of nanoscale protein dynamics in solution.

Science advances
Quantifying nanoscale protein secondary structure in aqueous solutions is crucial for understanding protein interactions and dynamics. Deep learning models are adept at predicting protein secondary structures, but their ability to model them in aqueo...

Molecular dynamics simulations of proteins: an in-depth review of computational strategies, structural insights, and their role in medicinal chemistry and drug development.

Biological cybernetics
Molecular dynamics (MD) simulations have emerged as a powerful and extensively employed tool in biomedical research, offering insights into intricate biomolecular processes such as structural flexibility and molecular interactions, and playing a pivo...

From reactive to proactive: Continuous protein monitoring for preventive health care.

Science (New York, N.Y.)
Continuous biomarker monitoring is revolutionizing chronic disease management, with glucose monitoring for diabetes as the primary example. Given the success of this approach, a transition to continuous protein monitoring (CPM, a real-time, implantab...

Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA increase with aging in the mouse and human brain.

eLife
Recent studies have established a reciprocal causal link between aging and the activation of transposable elements, characterized in particular by a de-repression of LINE-1 retrotransposons. These LINE-1 elements represent 21% of the human genome, bu...

Language models reveal a complex sequence basis for adaptive convergent evolution of protein functions.

Proceedings of the National Academy of Sciences of the United States of America
Convergent evolution, or convergence, refers to repeated, independent emergences of the same trait in two or more lineages of species during evolution, often indicating functional adaptation to specific environmental factors. Many computational metho...

Predicting Saturation Concentrations of Phase-Separating Proteins via Thermodynamic Integration.

Journal of chemical theory and computation
Phase separation of proteins and nucleic acids into biomolecular condensates contributes to the regulation of cellular compartmentalization in membrane-less environments. A key parameter controlling the onset of biomolecular condensate formation is t...