AIMC Topic: Signal Transduction

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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...
Artificial Intelligence Machine Learning Proteins Phosphorylation Computational Biology Signal Transduction
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Identification of SH2 domain-containing proteins and motifs prediction by a deep learning method.

Computers in biology and medicine May 29, 2023
The Src Homology 2 (SH2) domain plays an important role in the signal transmission mechanism in organisms. It mediates the protein-protein interactions based on the combination between phosphotyrosine and motifs in SH2 domain. In this study, we desig...
Deep Learning Proteins Binding Sites Protein Binding Signal Transduction src Homology Domains Phosphotyrosine
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EmbryoNet: using deep learning to link embryonic phenotypes to signaling pathways.

Nature methods May 8, 2023
Evolutionarily conserved signaling pathways are essential for early embryogenesis, and reducing or abolishing their activity leads to characteristic developmental defects. Classification of phenotypic defects can identify the underlying signaling mec...
Signal Transduction Algorithms Zebrafish Phenotype Animals Deep Learning Neural Networks, Computer
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Deep-Learning-Enhanced Diffusion Imaging Assay for Resolving Local-Density Effects on Membrane Receptors.

Analytical chemistry Jan 30, 2023
G-protein-coupled receptor (GPCR) density at the cell surface is thought to regulate receptor function. Spatially resolved measurements of local-density effects on GPCRs are needed but technically limited by density heterogeneity and mobility of memb...
Drug Inverse Agonism Cell Membrane Deep Learning Signal Transduction Receptors, G-Protein-Coupled Ligands
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Decoding CAR T cell phenotype using combinatorial signaling motif libraries and machine learning.

Science (New York, N.Y.) Dec 8, 2022
Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2300 synthetic costimulatory domains, built from combinations ...
Protein Domains T-Lymphocytes, Cytotoxic Signal Transduction Machine Learning Phenotype Receptors, Chimeric Antigen Peptide Library Humans
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Multi-source transfer learning with Graph Neural Network for excellent modelling the bioactivities of ligands targeting orphan G protein-coupled receptors.

Mathematical biosciences and engineering : MBE Nov 25, 2022
G protein-coupled receptors (GPCRs) have been the targets for more than 40% of the currently approved drugs. Although neural networks can effectively improve the accuracy of prediction with the biological activity, the result is undesirable in the li...
Signal Transduction Receptors, G-Protein-Coupled Ligands Neural Networks, Computer Machine Learning
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Multimodal multi-task deep neural network framework for kinase-target prediction.

Molecular diversity Nov 11, 2022
Kinase plays a significant role in various disease signaling pathways. Due to the highly conserved sequence of kinase family members, understanding the selectivity profile of kinase inhibitors remains a priority for drug discovery. Previous methods f...
Neural Networks, Computer Proteins Drug Discovery Signal Transduction
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Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins.

eLife Oct 13, 2022
A fundamental question in protein science is where allosteric hotspots - residues critical for allosteric signaling - are located, and what properties differentiate them. We carried out deep mutational scanning (DMS) of four homologous bacterial allo...
Allosteric Regulation Machine Learning Mutation Signal Transduction Molecular Dynamics Simulation Proteins
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Deep learning for de-convolution of Smad2 versus Smad3 binding sites.

BMC genomics Jul 20, 2022
BACKGROUND: The transforming growth factor beta-1 (TGF β-1) cytokine exerts both pro-tumor and anti-tumor effects in carcinogenesis. An increasing body of literature suggests that TGF β-1 signaling outcome is partially dependent on the regulatory tar...
Transforming Growth Factor beta Smad3 Protein Signal Transduction Deep Learning Binding Sites Cell Line Smad2 Protein
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Quantifying information of intracellular signaling: progress with machine learning.

Reports on progress in physics. Physical Society (Great Britain) Jul 12, 2022
Cells convey information about their extracellular environment to their core functional machineries. Studying the capacity of intracellular signaling pathways to transmit information addresses fundamental questions about living systems. Here, we revi...
Signal Transduction Machine Learning
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