AIMC Topic: Phosphorylation

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LMPhosSite: A Deep Learning-Based Approach for General Protein Phosphorylation Site Prediction Using Embeddings from the Local Window Sequence and Pretrained Protein Language Model.

Journal of proteome research Jul 17, 2023
Phosphorylation is one of the most important post-translational modifications and plays a pivotal role in various cellular processes. Although there exist several computational tools to predict phosphorylation sites, existing tools have not yet harne...
Proteins Phosphorylation Amino Acid Sequence Deep Learning Protein Processing, Post-Translational
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Large-Scale Modeling of Sparse Protein Kinase Activity Data.

Journal of chemical information and modeling Jun 9, 2023
Protein kinases are a protein family that plays an important role in several complex diseases such as cancer and cardiovascular and immunological diseases. Protein kinases have conserved ATP binding sites, which when targeted can lead to similar acti...
Phosphorylation Protein Processing, Post-Translational Machine Learning Protein Kinases Proteins
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Sequence-based machine learning method for predicting the effects of phosphorylation on protein-protein interactions.

International journal of biological macromolecules Jun 6, 2023
Protein phosphorylation, catalyzed by kinases, is an important biochemical process, which plays an essential role in multiple cell signaling pathways. Meanwhile, protein-protein interactions (PPI) constitute the signaling pathways. Abnormal phosphory...
Proteins Phosphorylation Computational Biology Signal Transduction Artificial Intelligence Machine Learning
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Multiplex Identification of Post-Translational Modifications at Point-of-Care by Deep Learning-Assisted Hydrogel Sensors.

Angewandte Chemie (International ed. in English) Mar 9, 2023
Multiplex detection of protein post-translational modifications (PTMs), especially at point-of-care, is of great significance in cancer diagnosis. Herein, we report a machine learning-assisted photonic crystal hydrogel (PCH) sensor for multiplex dete...
Animals Point-of-Care Systems Proteins Phosphorylation Mammals Deep Learning Protein Processing, Post-Translational Hydrogels
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Leveraging Protein Dynamics to Identify Functional Phosphorylation Sites using Deep Learning Models.

Journal of chemical information and modeling Jul 11, 2022
Accurate prediction of post-translational modifications (PTMs) is of great significance in understanding cellular processes, by modulating protein structure and dynamics. Nowadays, with the rapid growth of protein data at different "omics" levels, ma...
Phosphorylation Acetylation Deep Learning Protein Processing, Post-Translational Proteins
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Screening membraneless organelle participants with machine-learning models that integrate multimodal features.

Proceedings of the National Academy of Sciences of the United States of America Jun 10, 2022
Protein self-assembly is one of the formation mechanisms of biomolecular condensates. However, most phase-separating systems (PS) demand multiple partners in biological conditions. In this study, we divided PS proteins into two groups according to th...
Biomolecular Condensates Machine Learning Organelles Internet Use Proteome Proteins Humans Phosphorylation
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Kinases on Double Duty: A Review of UniProtKB Annotated Bifunctionality within the Kinome.

Biomolecules May 11, 2022
Phosphorylation facilitates the regulation of all fundamental biological processes, which has triggered extensive research of protein kinases and their roles in human health and disease. In addition to their phosphotransferase activity, certain kinas...
Protein Kinases Knowledge Bases Humans Phosphorylation
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TransPhos: A Deep-Learning Model for General Phosphorylation Site Prediction Based on Transformer-Encoder Architecture.

International journal of molecular sciences Apr 12, 2022
Protein phosphorylation is one of the most critical post-translational modifications of proteins in eukaryotes, which is essential for a variety of biological processes. Plenty of attempts have been made to improve the performance of computational pr...
Neural Networks, Computer Deep Learning Protein Processing, Post-Translational Proteins Phosphorylation
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A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences.

International journal of molecular sciences Feb 3, 2022
As one of the most important post-translational modifications (PTMs), phosphorylation refers to the binding of a phosphate group with amino acid residues like Ser (S), Thr (T) and Tyr (Y) thus resulting in diverse functions at the molecular level. Ab...
Learning Curve Entropy Leukemia Amino Acid Sequence Databases as Topic Deep Learning ROC Curve Humans Neural Networks, Computer Peptides Cluster Analysis Phosphorylation Neoplasm Proteins Phosphoproteins
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A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation.

Scientific reports Jan 7, 2022
Protein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell proliferation, differentiation, and apoptosis, which shows the importance of binding mechanism research and kinase inhibitor design. In this study, a no...
Protein Kinases Algorithms Phosphorylation Protein Kinase Inhibitors Neural Networks, Computer Amino Acid Motifs Machine Learning
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