AIMC Topic: Protein Kinase Inhibitors

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Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

Biochemical and biophysical research communications
Here we report the development of a machine-learning model to predict binding affinity based on the crystallographic structures of protein-ligand complexes. We used an ensemble of crystallographic structures (resolution better than 1.5 Å resolution) ...

Kinase inhibitor screening using artificial neural networks and engineered cardiac biowires.

Scientific reports
Kinase inhibitors are often used as cancer targeting agents for their ability to prevent the activation of cell growth and proliferation signals. Cardiotoxic effects have been identified for some marketed kinase inhibitors that were not detected duri...

Is Multitask Deep Learning Practical for Pharma?

Journal of chemical information and modeling
Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack ...

Imatinib Increases Serum Creatinine by Inhibiting Its Tubular Secretion in a Reversible Fashion in Chronic Myeloid Leukemia.

Clinical lymphoma, myeloma & leukemia
BACKGROUND: Monitoring renal function is important in imatinib-treated patients with chronic myeloid leukemia because serum creatinine may increase during the course of therapy. The mechanism of this increase and its reversibility on treatment cessat...

Modulatory role of garlicin in migration and invasion of intrahepatic cholangiocarcinoma via PI3K/AKT pathway.

International journal of clinical and experimental pathology
Increasing evidences have indicated the role of garlicin in inhibiting the progression of various tumors including glioma, pulmonary carcinoma and pancreatic carcinoma, via mediating cell apoptosis or cell cycle. The regulatory effect and related mol...

Binding Activity Prediction of Cyclin-Dependent Inhibitors.

Journal of chemical information and modeling
The Cyclin-Dependent Kinases (CDKs) are the core components coordinating eukaryotic cell division cycle. Generally the crystal structure of CDKs provides information on possible molecular mechanisms of ligand binding. However, reliable and robust est...

Visualization and Interpretation of Support Vector Machine Activity Predictions.

Journal of chemical information and modeling
Support vector machines (SVMs) are among the preferred machine learning algorithms for virtual compound screening and activity prediction because of their frequently observed high performance levels. However, a well-known conundrum of SVMs (and other...

Subtyping-Directed Precision Treatment Refines Traditional One-Size-Fits-All Therapy for HR+/HER2- Breast Cancer.

Cancer research
UNLABELLED: The standard approach of using one-size-fits-all endocrine therapy for hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancers has faced significant challenges because of variations in tr...

Enhancing PI3Kγ inhibitor discovery: a machine learning-based virtual screening approach integrating pharmacophores, docking, and molecular descriptors.

Molecular diversity
PI3Kγ is a lipid kinase that is expressed primarily in leukocytes and plays a significant role in tumors, inflammation, and autoimmune diseases. Consequently, considerable attention has been given to the development of pharmacological inhibitors of P...