AIMC Topic: Drug Screening Assays, Antitumor

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Discovery and characterization of novel FAK inhibitors for breast cancer therapy via hybrid virtual screening, biological evaluation and molecular dynamics simulations.

Bioorganic chemistry Mar 26, 2025
Focal adhesion kinase (FAK) is a critical drug target implicated in various disease pathways, including hematological malignancies and breast cancer. Therefore, identifying FAK inhibitors with novel scaffolds could offer new opportunities for develop...
Drug Discovery Antineoplastic Agents Cell Proliferation Dose-Response Relationship, Drug Humans Female Breast Neoplasms Molecular Docking Simulation Drug Evaluation, Preclinical Protein Kinase Inhibitors Focal Adhesion Kinase 1 Focal Adhesion Protein-Tyrosine Kinases Drug Screening Assays, Antitumor Structure-Activity Relationship Molecular Structure Molecular Dynamics Simulation
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Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning.

International journal of molecular sciences Mar 10, 2025
In recent years, many approved drugs have been discovered using phenotypic screening, which elaborates the exact mechanisms of action or molecular targets of drugs. Drug susceptibility prediction is an important type of phenotypic screening. Large-sc...
Precision Medicine Neoplasms Antineoplastic Agents Deep Learning Cell Line, Tumor Humans Computational Biology Drug Screening Assays, Antitumor Drug Resistance, Neoplasm
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Cubosomes as Delivery System to Repositioning Nitrofurantoin in Breast Cancer Management.

Drug design, development and therapy Dec 19, 2024
PURPOSE: Nitrofurantoin (NITRO), a long-standing antibiotic to treat urinary tract infections, is activated by Nitro reductases. This activation mechanism has led to its exploration for repositioning applications in controlling and treating breast ca...
Particle Size Drug Delivery Systems Humans MCF-7 Cells Cell Proliferation Female Nitrofurantoin Structure-Activity Relationship Dose-Response Relationship, Drug Breast Neoplasms Drug Repositioning Cell Survival Drug Screening Assays, Antitumor
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Ultradense Electrochemical Chip and Machine Learning for High-Throughput, Accurate Anticancer Drug Screening.

ACS sensors Nov 29, 2024
Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of dr...
Drug Screening Assays, Antitumor Electrochemical Techniques Doxorubicin High-Throughput Screening Assays Machine Learning Antineoplastic Agents Cell Line, Tumor Cell Survival Humans
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Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response.

Genes Nov 12, 2024
Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. The anoikis-related prognostic signature (ANRS) was gene...
Biomarkers, Tumor Middle Aged Antineoplastic Agents Gene Expression Profiling Aged Breast Neoplasms Tumor Microenvironment Enzyme-Linked Immunosorbent Assay Treatment Outcome Databases, Genetic Predictive Value of Tests Transcriptome Real-Time Polymerase Chain Reaction Reverse Transcriptase Polymerase Chain Reaction Immunotherapy Machine Learning Prognosis Female Reproducibility of Results Imatinib Mesylate Proportional Hazards Models Anoikis Drug Screening Assays, Antitumor Gene Expression Blotting, Western
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Wee1 inhibitor optimization through deep-learning-driven decision making.

European journal of medicinal chemistry Sep 29, 2024
Deep learning has gained increasing attention in recent years, yielding promising results in hit screening and molecular optimization. Herein, we employed an efficient strategy based on multiple deep learning techniques to optimize Wee1 inhibitors, w...
Protein Kinase Inhibitors Cell Cycle Proteins Cell Line, Tumor Decision Making Cell Proliferation Humans Dose-Response Relationship, Drug Drug Screening Assays, Antitumor Antineoplastic Agents Protein-Tyrosine Kinases Structure-Activity Relationship Deep Learning Molecular Structure
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Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds.

Journal of chemical information and modeling Aug 28, 2024
Recently, various modern experimental screening pipelines and assays have been developed to find promising anticancer drug candidates. However, it is time-consuming and almost infeasible to screen an immense number of compounds for anticancer activit...
Humans Drug Evaluation, Preclinical Neural Networks, Computer Neoplasms Machine Learning Antineoplastic Agents Drug Screening Assays, Antitumor
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From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

ChemMedChem Jun 20, 2024
Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effe...
Drug Screening Assays, Antitumor Humans Structure-Activity Relationship Molecular Structure Deep Learning Protein Kinase Inhibitors Molecular Docking Simulation Vascular Endothelial Growth Factor Receptor-2 Cell Line, Tumor Drug Discovery Cell Proliferation Antineoplastic Agents Dose-Response Relationship, Drug
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Deep learning unlocks label-free viability assessment of cancer spheroids in microfluidics.

Lab on a chip Jun 11, 2024
Despite recent advances in cancer treatment, refining therapeutic agents remains a critical task for oncologists. Precise evaluation of drug effectiveness necessitates the use of 3D cell culture instead of traditional 2D monolayers. Microfluidic plat...
Humans Antineoplastic Agents Lab-On-A-Chip Devices Spheroids, Cellular Microfluidic Analytical Techniques Deep Learning Cell Line, Tumor Cell Survival Drug Screening Assays, Antitumor
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SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.

Computational biology and chemistry Mar 19, 2024
The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predi...
Drug Screening Assays, Antitumor Drug Synergism Antineoplastic Agents Cell Line, Tumor Antineoplastic Combined Chemotherapy Protocols Humans Machine Learning
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