AIMC Topic: Drug Screening Assays, Antitumor

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T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study.

Journal of biomolecular structure & dynamics Jan 4, 2024
Acquired resistance to EGFR is a major impediment in lung cancer treatment, highlighting the urgent need to discover novel compounds to overcome EGFR drug resistance. In this study, we utilized in silico methods and bioactivity evaluation for drug di...
Humans Machine Learning Molecular Docking Simulation Drug Discovery Antineoplastic Agents Drug Screening Assays, Antitumor Mutation Drug Resistance, Neoplasm ErbB Receptors Protein Kinase Inhibitors Cell Line, Tumor Protein Binding Cell Proliferation Apoptosis
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Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.

Pancreas Nov 24, 2023
OBJECTIVES: We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC).
Paclitaxel Drug Resistance, Neoplasm Gemcitabine Tomography Humans Deep Learning Drug Screening Assays, Antitumor Pancreatic Neoplasms Fluorouracil Carcinoma, Pancreatic Ductal
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Wet-dry-wet drug screen leads to the synthesis of TS1, a novel compound reversing lung fibrosis through inhibition of myofibroblast differentiation.

Cell death & disease Dec 17, 2021
Therapies halting the progression of fibrosis are ineffective and limited. Activated myofibroblasts are emerging as important targets in the progression of fibrotic diseases. Previously, we performed a high-throughput screen on lung fibroblasts and s...
Humans Machine Learning Lung Diseases Transfection High-Throughput Screening Assays Bleomycin Animals Myofibroblasts Drug Discovery Drug Screening Assays, Antitumor Mice Cell Differentiation Idiopathic Pulmonary Fibrosis
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A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy.

Bioorganic & medicinal chemistry Nov 27, 2021
Colorectal cancer (CRC) is the third most detected cancer and the second foremost cause of cancer deaths in the world. Intervention targeting p53 provides potential therapeutic strategies, but thus far no p53-based therapy has been successfully trans...
Dose-Response Relationship, Drug Cell Survival Drug Screening Assays, Antitumor Structure-Activity Relationship Dihydroergotoxine Molecular Structure Tumor Suppressor Protein p53 Drug Discovery Antineoplastic Agents Cell Line, Tumor Cell Proliferation Humans Machine Learning Colorectal Neoplasms Molecular Docking Simulation
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Discovery of Pyrazolo[3,4-]pyridazinone Derivatives as Selective DDR1 Inhibitors via Deep Learning Based Design, Synthesis, and Biological Evaluation.

Journal of medicinal chemistry Nov 25, 2021
Alterations of discoidin domain receptor1 (DDR1) may lead to increased production of inflammatory cytokines, making DDR1 an attractive target for inflammatory bowel disease (IBD) therapy. A scaffold-based molecular design workflow was established and...
Mice, Inbred C57BL Drug Screening Assays, Antitumor Molecular Structure Mice, Inbred ICR Drug Design Drug Discovery Deep Learning Mice Colitis Discoidin Domain Receptor 1 Pyrazolones Anti-Inflammatory Agents Protein Kinase Inhibitors Pyridazines Dextran Sulfate Humans Animals
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Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning.

International journal of molecular sciences Oct 26, 2021
The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built to predict the probability of different ...
Drug Design Antineoplastic Agents User-Computer Interface Nanoparticles Glioblastoma Humans Databases, Chemical Machine Learning Databases, Pharmaceutical Drug Carriers Drug Delivery Systems Drug Screening Assays, Antitumor Brain Neoplasms
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Synthesis, docking, machine learning and antiproliferative activity of the 6-ferrocene/heterocycle-2-aminopyrimidine and 5-ferrocene-1H-Pyrazole derivatives obtained by microwave-assisted Atwal reaction as potential anticancer agents.

Bioorganic & medicinal chemistry letters Jul 2, 2021
A simple and fast methodology under microwave irradiation for the synthesis of 2-aminopyrimidine and pyrazole derivatives using Atwal reaction is reported. After the optimization of the reaction conditions, eight 2-aminolpyrimidines containing ferroc...
Molecular Docking Simulation Antineoplastic Agents Cell Line, Tumor Cell Proliferation Structure-Activity Relationship Molecular Structure Ferrous Compounds Dose-Response Relationship, Drug Drug Screening Assays, Antitumor Humans Machine Learning Microwaves Pyrazoles Pyrimidines Metallocenes
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Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs.

Nature communications Mar 25, 2021
Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which use...
Prognosis Leukemia Neoplasms Antineoplastic Agents Proteomics Cytarabine Humans Cell Proliferation Machine Learning Hep G2 Cells Cell Line, Tumor Drug Screening Assays, Antitumor Computational Biology
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Ensemble transfer learning for the prediction of anti-cancer drug response.

Scientific reports Oct 22, 2020
Transfer learning, which transfers patterns learned on a source dataset to a related target dataset for constructing prediction models, has been shown effective in many applications. In this paper, we investigate whether transfer learning can be used...
Deep Learning Drug Development Algorithms Drug Repositioning Models, Biological Humans Precision Medicine Drug Screening Assays, Antitumor Datasets as Topic Neural Networks, Computer Neoplasms Antineoplastic Agents
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Representation of features as images with neighborhood dependencies for compatibility with convolutional neural networks.

Nature communications Sep 1, 2020
Deep learning with Convolutional Neural Networks has shown great promise in image-based classification and enhancement but is often unsuitable for predictive modeling using features without spatial correlations. We present a feature representation ap...
Gene Expression Profiling Cell Proliferation Humans Deep Learning Drug Screening Assays, Antitumor Biomarkers, Tumor Cell Line, Tumor Bayes Theorem Neoplasms Image Processing, Computer-Assisted High-Throughput Nucleotide Sequencing Datasets as Topic Oligonucleotide Array Sequence Analysis Antineoplastic Agents Drug Resistance, Neoplasm
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