AIMC Topic: Protein Kinases

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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...
Proteins Phosphorylation Protein Kinases Machine Learning Protein Processing, Post-Translational
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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...
Humans Phosphorylation Protein Kinases Knowledge Bases
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Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BMC bioinformatics Apr 15, 2022
BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complementarily regulate signaling pathways. Even though there are > 100,000 protein kinase inhibitors, onl...
United States Food and Drug Administration Protein Kinase Inhibitors Humans Machine Learning Pharmaceutical Preparations United States Protein Kinases
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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...
Neural Networks, Computer Machine Learning Protein Kinases Algorithms Protein Kinase Inhibitors Phosphorylation Amino Acid Motifs
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Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches.

Journal of chemical information and modeling Sep 29, 2021
The protein kinase family contains many promising drug targets. Many kinase inhibitors target the ATP-binding pocket, leading to approved drugs in past decades. Scaffold hopping is an effective approach for drug design. The kinase ATP-binding pocket ...
Drug Design Deep Learning Protein Kinase Inhibitors Protein Binding Protein Kinases
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Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses.

The Plant journal : for cell and molecular biology Aug 10, 2021
Brassinosteroids (BRs) are a group of plant steroid hormones involved in regulating growth, development, and stress responses. Many components of the BR pathway have previously been identified and characterized. However, BR phenotyping experiments ar...
Brassinosteroids Arabidopsis Proteins Arabidopsis Zea mays Equipment Design Triazoles Droughts Protein Kinases Image Processing, Computer-Assisted Robotics Seedlings Phenotype Soil Machine Learning
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Prediction of kinase inhibitors binding modes with machine learning and reduced descriptor sets.

Scientific reports Jan 12, 2021
Protein kinases are receiving wide research interest, from drug perspective, due to their important roles in human body. Available kinase-inhibitor data, including crystallized structures, revealed many details about the mechanism of inhibition and b...
Models, Molecular Humans Protein Kinases Protein Kinase Inhibitors Machine Learning Support Vector Machine Protein Conformation Protein Binding
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FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms.

Cancer medicine Jan 1, 2020
Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5-FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta-analysis to identify differentially expressed ...
Humans Datasets as Topic Colorectal Neoplasms Organoplatinum Compounds Biomarkers, Tumor Machine Learning Oligonucleotide Array Sequence Analysis Gene Expression Profiling Intracellular Signaling Peptides and Proteins Prognosis Cell Cycle Proteins Neoplasm Recurrence, Local Gene Expression Regulation, Neoplastic Response Evaluation Criteria in Solid Tumors Fluorouracil Antineoplastic Combined Chemotherapy Protocols Leucovorin Protein Kinases
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Machine Learning Models for Accurate Prediction of Kinase Inhibitors with Different Binding Modes.

Journal of medicinal chemistry Aug 30, 2019
Noncovalent inhibitors of protein kinases have different modes of action. They bind to the active or inactive form of kinases, compete with ATP, stabilize inactive kinase conformations, or act through allosteric sites. Accordingly, kinase inhibitors ...
Crystallography, X-Ray Machine Learning Protein Kinase Inhibitors Protein Kinases Datasets as Topic Protein Binding Databases, Chemical
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Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation.

Journal of medicinal chemistry Aug 15, 2019
The kinome-wide virtual profiling of small molecules with high-dimensional structure-activity data is a challenging task in drug discovery. Here, we present a virtual profiling model against a panel of 391 kinases based on large-scale bioactivity dat...
Protein Kinase Inhibitors Polypharmacology Deep Learning Datasets as Topic Drug Discovery Protein Kinases Databases, Chemical
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