AIMC Topic: Drug Discovery

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Discovery and Characterization of Novel Receptor-Interacting Protein Kinase 1 Inhibitors Using Deep Learning and Virtual Screening.

ACS chemical neuroscience Apr 3, 2025
Receptor-interacting protein kinase 1 (RIPK1) serves as a critical mediator of cell necroptosis and represents a promising therapeutic target for various human neurodegenerative diseases and inflammatory diseases. Nonetheless, the RIPK1 inhibitors cu...
Drug Evaluation, Preclinical HT29 Cells Receptor-Interacting Protein Serine-Threonine Kinases Protein Kinase Inhibitors Drug Discovery Deep Learning Necroptosis Humans Molecular Docking Simulation
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Application of Deep Learning to Predict the Persistence, Bioaccumulation, and Toxicity of Pharmaceuticals.

Journal of chemical information and modeling Apr 3, 2025
This study investigates the application of a deep learning (DL) model, specifically a message-passing neural network (MPNN) implemented through Chemprop, to predict the persistence, bioaccumulation, and toxicity (PBT) characteristics of compounds, wi...
Drug Discovery Humans Deep Learning Neural Networks, Computer Pharmaceutical Preparations
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Combining High-Throughput Screening and Machine Learning to Predict the Formation of Both Binary and Ternary Amorphous Solid Dispersion Formulations for Early Drug Discovery and Development.

Pharmaceutical research Apr 3, 2025
OBJECTIVE: Amorphous solid dispersion (ASD) is widely utilized to enhance the solubility and bioavailability of water-insoluble drugs. However, conventional experimental approaches for ASD development are often resource-intensive and time-consuming. ...
Drug Development Support Vector Machine Solubility Algorithms Drug Discovery X-Ray Diffraction Chemistry, Pharmaceutical Powder Diffraction Drug Compounding Crystallization High-Throughput Screening Assays Machine Learning
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Drug-Target Affinity Prediction Based on Topological Enhanced Graph Neural Networks.

Journal of chemical information and modeling Mar 31, 2025
Graph neural networks (GNNs) have achieved remarkable success in drug-target affinity (DTA) analysis, reducing the cost of drug development. Unlike traditional one-dimensional (1D) sequence-based methods, GNNs leverage graph structures to capture ric...
Neural Networks, Computer Pharmaceutical Preparations Drug Discovery Graph Neural Networks Proteins
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Prediction and Prioritisation of Novel Anthelmintic Candidates from Public Databases Using Deep Learning and Available Bioactivity Data Sets.

International journal of molecular sciences Mar 28, 2025
The control of socioeconomically important parasitic roundworms (nematodes) of animals has become challenging or ineffective due to problems associated with widespread resistance in these worms to most classes of chemotherapeutic drugs (anthelmintics...
Haemonchus Animals Anthelmintics Databases, Factual Drug Discovery Computer Simulation Deep Learning
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Application of Machine Learning and Mechanistic Modeling to Predict Intravenous Pharmacokinetic Profiles in Humans.

Journal of medicinal chemistry Mar 27, 2025
Accurate prediction of new compounds' pharmacokinetic (PK) profile in humans is crucial for drug discovery. Traditional methods, including allometric scaling and mechanistic modeling, rely on parameters from or testing, which are labor-intensive an...
Pharmacokinetics Administration, Intravenous Models, Biological Machine Learning Drug Discovery Humans Pharmaceutical Preparations
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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...
Dose-Response Relationship, Drug Drug Screening Assays, Antitumor Structure-Activity Relationship Antineoplastic Agents Cell Proliferation Humans Female Protein Kinase Inhibitors Molecular Docking Simulation Focal Adhesion Kinase 1 Drug Discovery Focal Adhesion Protein-Tyrosine Kinases Breast Neoplasms Molecular Dynamics Simulation Molecular Structure Drug Evaluation, Preclinical
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Knowledge-Based Artificial Intelligence System for Drug Prioritization.

Journal of chemical information and modeling Mar 26, 2025
drug prioritization may be a promising and time-saving strategy to identify potential drugs, standing as a faster and more cost-effective approach than approaches. In recent years, artificial intelligence has greatly evolved the drug development pr...
Artificial Intelligence Drug Discovery Humans
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Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candidates Against MERS-CoV 3CL Protease.

International journal of molecular sciences Mar 26, 2025
In this study, we utilized machine learning techniques to identify potential inhibitors of the MERS-CoV 3CL protease. Among the models evaluated, the Random Forest (RF) algorithm exhibited the highest predictive performance, achieving an accuracy of ...
Molecular Dynamics Simulation Catalytic Domain Middle East Respiratory Syndrome Coronavirus Drug Discovery Antiviral Agents Protease Inhibitors Machine Learning Humans Coronavirus 3C Proteases Molecular Docking Simulation
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In silico discovery of novel compounds for FAK activation using virtual screening, AI-based prediction, and molecular dynamics.

Computational biology and chemistry Mar 25, 2025
Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase that plays a crucial role in cell proliferation, migration, and signal transduction. FAK is overexpressed in metastatic and advanced-stage cancers, where it is considered a key kinase in c...
Drug Discovery Molecular Structure Drug Evaluation, Preclinical Protein Kinase Inhibitors Molecular Dynamics Simulation Humans Artificial Intelligence Molecular Docking Simulation Focal Adhesion Protein-Tyrosine Kinases
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