AIMC Topic: Drug Discovery

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PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery.

Journal of chemical information and modeling Apr 9, 2025
The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale desi...
Machine Learning Drug Discovery Software Quantitative Structure-Activity Relationship
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Unified Deep Learning of Molecular and Protein Language Representations with T5ProtChem.

Journal of chemical information and modeling Apr 8, 2025
Deep learning has revolutionized difficult tasks in chemistry and biology, yet existing language models often treat these domains separately, relying on concatenated architectures and independently pretrained weights. These approaches fail to fully e...
Drug Discovery Models, Molecular Computational Biology Deep Learning Proteins
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Edge-enhanced interaction graph network for protein-ligand binding affinity prediction.

PloS one Apr 8, 2025
Protein-ligand interactions are crucial in drug discovery. Accurately predicting protein-ligand binding affinity is essential for screening potential drugs. Graph neural networks have proven highly effective in modeling spatial relationships and thre...
Proteins Ligands Drug Discovery Neural Networks, Computer Protein Binding Algorithms
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Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.

Journal of microbiological methods Apr 7, 2025
Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential therapeutic targets by differentiating essential genes in pathogens and non-pathogenic genes. Since, identification of therapeutic targets and understand...
Genome, Bacterial Software Drug Discovery Bacteria Computational Biology Humans Genomics
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Virtual reality in drug design: Benefits, applications and industrial perspectives.

Current opinion in structural biology Apr 7, 2025
Virtual reality (VR) is a tool which has transformative potential in domains which involve the visualization of complex 3D data such as structure-based drug design (SBDD), where it offers new ways to visualize and manipulate complex molecular structu...
Humans COVID-19 Drug Design Drug Discovery Virtual Reality SARS-CoV-2 Molecular Docking Simulation Drug Industry Ligands COVID-19 Drug Treatment
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Machine learning approaches enable the discovery of therapeutics across domains.

Molecular therapy : the journal of the American Society of Gene Therapy Apr 3, 2025
Multi-modal datasets have grown exponentially in the last decade. This has created an enormous demand for machine learning models that can predict complex outcomes by leveraging cellular, molecular, and humoral profiles. Corresponding inference of me...
Humans Machine Learning Drug Discovery Computational Biology
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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 Discovery Deep Learning Drug Evaluation, Preclinical HT29 Cells Necroptosis Humans Molecular Docking Simulation Protein Kinase Inhibitors Receptor-Interacting Protein Serine-Threonine Kinases
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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. ...
Powder Diffraction X-Ray Diffraction Chemistry, Pharmaceutical Drug Compounding Crystallization Drug Discovery Drug Development Machine Learning Solubility Algorithms High-Throughput Screening Assays Support Vector Machine
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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...
Drug Discovery Deep Learning Humans Hydrophobic and Hydrophilic Interactions Receptors, Cytoplasmic and Nuclear Thermodynamics Protein Binding Molecular Dynamics Simulation
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