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Phosphorylation

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A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction.

Genomics, proteomics & bioinformatics
Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and, as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital PTM that...

DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features.

Journal of chemical information and modeling
Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of...

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification.

Molecular & cellular proteomics : MCP
Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This ...

DeepNphos: A deep-learning architecture for prediction of N-phosphorylation sites.

Computers in biology and medicine
MOTIVATION: Phosphorylation, a prevalent post-translational modification, plays a crucial role in regulating cellular activities. This process encompasses O-phosphorylation (e.g., phosphoserine) and N-phosphorylation (e.g., phospho-lysine (pK), phosp...

DL-SPhos: Prediction of serine phosphorylation sites using transformer language model.

Computers in biology and medicine
Serine phosphorylation plays a pivotal role in the pathogenesis of various cellular processes and diseases. Roughly 81% of human diseases have links to phosphorylation, and an overwhelming 86.4% of protein phosphorylation takes place at serine residu...

PhosAF: An integrated deep learning architecture for predicting protein phosphorylation sites with AlphaFold2 predicted structures.

Analytical biochemistry
Phosphorylation is indispensable in comprehending biological processes, while biological experimental methods for identifying phosphorylation sites are tedious and arduous. With the rapid growth of biotechnology, deep learning methods have made signi...

Identifying Protein Phosphorylation Site-Disease Associations Based on Multi-Similarity Fusion and Negative Sample Selection by Convolutional Neural Network.

Interdisciplinary sciences, computational life sciences
As one of the most important post-translational modifications (PTMs), protein phosphorylation plays a key role in a variety of biological processes. Many studies have shown that protein phosphorylation is associated with various human diseases. There...

Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning.

Molecules (Basel, Switzerland)
The phosphorylation of different sites produces a significant effect on the conformational dynamics of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were combined with deep learning (DL) to explore the molecular mechanism of the ph...

PTransIPs: Identification of Phosphorylation Sites Enhanced by Protein PLM Embeddings.

IEEE journal of biomedical and health informatics
Phosphorylation is pivotal in numerous fundamental cellular processes and plays a significant role in the onset and progression of various diseases. The accurate identification of these phosphorylation sites is crucial for unraveling the molecular me...

PhosBERT: A self-supervised learning model for identifying phosphorylation sites in SARS-CoV-2-infected human cells.

Methods (San Diego, Calif.)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus, which mainly causes respiratory and enteric diseases and is responsible for the outbreak of coronavirus disease 19 (COVID-19). Numerous studies have demonstr...