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...
Protein Kinase Inhibitors Receptor-Interacting Protein Serine-Threonine Kinases Necroptosis Humans Drug Evaluation, Preclinical Molecular Docking Simulation Drug Discovery HT29 Cells Deep Learning
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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...
Deep Learning Pharmaceutical Preparations Humans Neural Networks, Computer Drug Discovery
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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. ...
Machine Learning Algorithms Drug Discovery Drug Development X-Ray Diffraction High-Throughput Screening Assays Chemistry, Pharmaceutical Drug Compounding Support Vector Machine Powder Diffraction Crystallization Solubility
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Integrating deep learning and molecular dynamics simulations for FXR antagonist discovery.

Molecular diversity Apr 2, 2025
Farnesoid X receptor (FXR) is a key regulator of bile acid, lipid, and glucose homeostasis, making it a promising target for treating metabolic diseases. FXR antagonists have shown therapeutic potential in cholestasis, metabolic disorders, and certai...
Humans Drug Discovery Deep Learning Hydrophobic and Hydrophilic Interactions Protein Binding Receptors, Cytoplasmic and Nuclear Molecular Dynamics Simulation Thermodynamics
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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 Graph Neural Networks Drug Discovery Proteins
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Advances in AI-based strategies and tools to facilitate natural product and drug development.

Critical reviews in biotechnology Mar 30, 2025
Natural products and their derivatives have been important for treating diseases in humans, animals, and plants. However, discovering new structures from natural sources is still challenging. In recent years, artificial intelligence (AI) has greatly ...
Humans Drug Discovery Drug Development Biological Products Neural Networks, Computer Artificial Intelligence Animals
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Deep learning in the discovery of antiviral peptides and peptidomimetics: databases and prediction tools.

Molecular diversity Mar 28, 2025
Antiviral peptides (AVPs) represent a novel and promising therapeutic alternative to conventional antiviral treatments, due to their broad-spectrum activity, high specificity, and low toxicity. The emergence of zoonotic viruses such as Zika, Ebola, a...
Antiviral Agents Peptidomimetics Humans Drug Discovery Deep Learning COVID-19 SARS-CoV-2 Databases, Factual Animals Peptides
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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 Databases, Factual Anthelmintics 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...
Humans Machine Learning Drug Discovery Pharmaceutical Preparations Administration, Intravenous Models, Biological Pharmacokinetics
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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...
Molecular Structure Molecular Dynamics Simulation Drug Evaluation, Preclinical Drug Screening Assays, Antitumor Structure-Activity Relationship Protein Kinase Inhibitors Focal Adhesion Kinase 1 Focal Adhesion Protein-Tyrosine Kinases Molecular Docking Simulation Humans Drug Discovery Female Antineoplastic Agents Breast Neoplasms Cell Proliferation Dose-Response Relationship, Drug
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