AIMC Topic: Protein Kinases

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Identification of hub necroptosis-related targets and discovery of potential natural inhibitors in ulcerative colitis based on bioinformatics and computer-aided drug design.

Journal of computer-aided molecular design Oct 24, 2025
Ulcerative colitis (UC) is a chronic inflammatory bowel disease with a complex pathogenesis and limited treatment options. Recently, necroptosis has been found to play a significant role in UC. This study aimed to investigate necroptosis-related mech...
Drug Design Drug Discovery Single-Cell Analysis Molecular Docking Simulation Computer-Aided Design Necroptosis Molecular Dynamics Simulation Protein Kinases Biological Products Colitis, Ulcerative Computational Biology Humans Machine Learning
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Affinity prediction of inhibitor-kinase based on mixture of experts enhanced by multimodal feature semantic analysis.

International journal of biological macromolecules Jul 28, 2025
Accurate identification of inhibitor-kinase binding affinity is crucial for drug discovery. However, many deep learning models often overlook high-order feature information from biological networks and face challenges related to the cold-start proble...
Protein Kinases Semantics Protein Kinase Inhibitors Deep Learning Protein Interaction Maps Humans Protein Binding Drug Discovery
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A Specialized and Enhanced Deep Generation Model for Active Molecular Design Targeting Kinases Guided by Affinity Prediction Models and Reinforcement Learning.

Journal of chemical information and modeling Apr 2, 2025
Kinases are critical regulators in numerous cellular processes, and their dysregulation is linked to various diseases, including cancer. Thus, protein kinases have emerged as major drug targets at present, with approximately a quarter to a third of g...
Models, Molecular Protein Kinases Protein Kinase Inhibitors Drug Design Deep Learning
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Docking-Informed Machine Learning for Kinome-wide Affinity Prediction.

Journal of chemical information and modeling Dec 10, 2024
Kinase inhibitors are an important class of anticancer drugs, with 80 inhibitors clinically approved and >100 in active clinical testing. Most bind competitively in the ATP-binding site, leading to challenges with selectivity for a specific kinase, r...
Protein Conformation Protein Kinase Inhibitors Binding Sites Protein Binding Protein Kinases Machine Learning Molecular Docking Simulation Humans
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The Development and Application of KinomePro-DL: A Deep Learning Based Online Small Molecule Kinome Selectivity Profiling Prediction Platform.

Journal of chemical information and modeling Sep 25, 2024
Characterizing the kinome selectivity profiles of kinase inhibitors is essential in the early stages of novel small-molecule drug discovery. This characterization is critical for interpreting potential adverse events caused by off-target polypharmaco...
Humans Small Molecule Libraries Drug Discovery Protein Kinases Deep Learning Protein Kinase Inhibitors
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Kinase Drug Discovery: Impact of Open Science and Artificial Intelligence.

Molecular pharmaceutics Sep 6, 2024
Given their central role in signal transduction, protein kinases (PKs) were first implicated in cancer development, caused by aberrant intracellular signaling events. Since then, PKs have become major targets in different therapeutic areas. The prefe...
Protein Kinases Protein Kinase Inhibitors Artificial Intelligence Drug Discovery Signal Transduction Humans
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E-pharmacophore and deep learning based high throughput virtual screening for identification of CDPK1 inhibitors of Cryptosporidium parvum.

Computational biology and chemistry Aug 13, 2024
Cryptosporidiosis, a prevalent gastrointestinal illness worldwide, is caused by the protozoan parasite Cryptosporidium parvum. Calcium-dependent protein kinase 1 (CpCDPK1), crucial for the parasite's life cycle, serves as a promising drug target due ...
Protein Kinases High-Throughput Screening Assays Protein Kinase Inhibitors Deep Learning Pharmacophore Cryptosporidium parvum Molecular Docking Simulation Molecular Structure Antiprotozoal Agents Drug Evaluation, Preclinical
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CNN-BLSTM based deep learning framework for eukaryotic kinome classification: An explainability based approach.

Computational biology and chemistry Aug 8, 2024
Classification of protein families from their sequences is an enduring task in Proteomics and related studies. Numerous deep-learning models have been moulded to tackle this challenge, but due to the black-box character, they still fall short in reli...
Algorithms Protein Kinases Deep Learning Eukaryota
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A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships.

PLoS computational biology May 20, 2024
The activities of most enzymes and drugs depend on interactions between proteins and small molecules. Accurate prediction of these interactions could greatly accelerate pharmaceutical and biotechnological research. Current machine learning models des...
Proteins Small Molecule Libraries Amino Acid Sequence Deep Learning Humans Protein Binding Protein Kinase Inhibitors Protein Kinases Machine Learning Substrate Specificity Computational Biology
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Guided Docking as a Data Generation Approach Facilitates Structure-Based Machine Learning on Kinases.

Journal of chemical information and modeling May 15, 2024
Drug discovery pipelines nowadays rely on machine learning models to explore and evaluate large chemical spaces. While including 3D structural information is considered beneficial, structural models are hindered by the availability of protein-ligand ...
Phosphotransferases Machine Learning Molecular Docking Simulation Neural Networks, Computer Ligands Protein Binding Protein Conformation Drug Discovery Protein Kinases Protein Kinase Inhibitors
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