AIMC Topic: Phosphorylation

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Mechanistic Basis for GPCR Phosphorylation-Dependent Allosteric Signaling Specificity of β-Arrestin 1 and 2.

Journal of chemical information and modeling
β-Arrestins (βarr1 and βarr2) are key transducers of G protein-coupled receptor (GPCR) signaling, orchestrating both shared and isoform-specific intracellular pathways. Phosphorylation of the receptor C-terminal tail by GPCR kinases encodes regulator...

Mapping Context-Aware Phosphosite Regulation of Protein-Protein Interactions Using Deep Learning and Pan-Cancer Proteomics.

Journal of chemical information and modeling
Phosphorylation dynamically orchestrates the protein-protein interaction (PPI) network that governs cellular signaling, and its dysregulation frequently drives malignant transformation and neurodegeneration. We present PhosPPI-SEQ, an interpretable d...

Single-Molecule SERS Detection of Phosphorylation in Serine and Tyrosine Using Deep Learning-Assisted Plasmonic Nanopore.

The journal of physical chemistry letters
Single-molecule detection of post-translational modifications (PTMs) such as phosphorylation plays a crucial role in early diagnosis of diseases and therapeutics development. Although single-molecule surface-enhanced Raman spectroscopy (SM-SERS) dete...

Insights into phosphorylation-induced influences on conformations and inhibitor binding of CDK6 through GaMD trajectory-based deep learning.

Physical chemistry chemical physics : PCCP
The phosphorylation of residue T177 produces a significant effect on the conformational dynamics of CDK6. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) are applied to explore the molecular mechanism of the ...

Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites.

Nature communications
Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, yet our limited knowledge about the regulation and function of most phosphosites hampers the extraction of meaningful biological insights. To address th...

Machine learning-based prediction reveals kinase MAP4K4 regulates neutrophil differentiation through phosphorylating apoptosis-related proteins.

PLoS computational biology
Neutrophils, an essential innate immune cell type with a short lifespan, rely on continuous replenishment from bone marrow (BM) precursors. Although it is established that neutrophils are derived from the granulocyte-macrophage progenitor (GMP), the ...

GraphPhos: Predict Protein-Phosphorylation Sites Based on Graph Neural Networks.

International journal of molecular sciences
Phosphorylation is one of the most common protein post-translational modifications. The identification of phosphorylation sites serves as the cornerstone for protein-phosphorylation-related research. This paper proposes a protein-phosphorylation site...

Screening of Aβ and phosphorylated tau status in the cerebrospinal fluid through machine learning analysis of portable electroencephalography data.

Scientific reports
Diagnosing Alzheimer's disease (AD) through pathological markers is typically costly and invasive. This study aims to find a noninvasive, cost-effective method using portable electroencephalography (EEG) to detect changes in AD-related biomarkers in ...

MMFuncPhos: A Multi-Modal Learning Framework for Identifying Functional Phosphorylation Sites and Their Regulatory Types.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Protein phosphorylation plays a crucial role in regulating a wide range of biological processes, and its dysregulation is strongly linked to various diseases. While many phosphorylation sites have been identified so far, their functionality and regul...