AIMC Topic: Drug Discovery

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From Target to Drug: Generative Modeling for the Multimodal Structure-Based Ligand Design.

Molecular pharmaceutics Sep 10, 2019
Chemical space is impractically large, and conventional structure-based virtual screening techniques cannot be used to simply search through the entire space to discover effective bioactive molecules. To address this shortcoming, we propose a generat...
Neural Networks, Computer Drug Design Drug Discovery Humans Molecular Conformation Quantitative Structure-Activity Relationship Small Molecule Libraries Proteins Models, Chemical Ligands
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PTPD: predicting therapeutic peptides by deep learning and word2vec.

BMC bioinformatics Sep 6, 2019
*: Background In the search for therapeutic peptides for disease treatments, many efforts have been made to identify various functional peptides from large numbers of peptide sequence databases. In this paper, we propose an effective computational mo...
Computational Biology Databases, Nucleic Acid Peptides Drug Discovery Deep Learning
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Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism.

Journal of medicinal chemistry Aug 27, 2019
Hunting for chemicals with favorable pharmacological, toxicological, and pharmacokinetic properties remains a formidable challenge for drug discovery. Deep learning provides us with powerful tools to build predictive models that are appropriate for t...
Deep Learning Proof of Concept Study Solubility Organic Chemicals Drug Discovery Models, Molecular Datasets as Topic Databases, Chemical
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Looking beyond the hype: Applied AI and machine learning in translational medicine.

EBioMedicine Aug 26, 2019
Big data problems are becoming more prevalent for laboratory scientists who look to make clinical impact. A large part of this is due to increased computing power, in parallel with new technologies for high quality data generation. Both new and old t...
Machine Learning Precision Medicine Reproducibility of Results Humans Artificial Intelligence Translational Research, Biomedical Molecular Imaging Animals Drug Discovery Genomics
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Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors.

Journal of chemical information and modeling Aug 22, 2019
The hit-to-lead and lead optimization processes usually involve the design, synthesis, and profiling of thousands of analogs prior to clinical candidate nomination. A hit finding campaign may begin with a virtual screen that explores millions of comp...
Models, Molecular Protein Kinase Inhibitors Thermodynamics Small Molecule Libraries Cyclin-Dependent Kinase 2 Machine Learning Humans Drug Design Drug Discovery
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Target-Specific Prediction of Ligand Affinity with Structure-Based Interaction Fingerprints.

Journal of chemical information and modeling Aug 19, 2019
Discovery and optimization of small molecule inhibitors as therapeutic drugs have immensely benefited from rational structure-based drug design. With recent advances in high-resolution structure determination, computational power, and machine learnin...
Drug Discovery HIV Infections Protein Binding Machine Learning Molecular Docking Simulation Drug Design HIV Protease Inhibitors HIV-1 Ligands HIV Protease Humans
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Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation.

Journal of medicinal chemistry Aug 15, 2019
The kinome-wide virtual profiling of small molecules with high-dimensional structure-activity data is a challenging task in drug discovery. Here, we present a virtual profiling model against a panel of 391 kinases based on large-scale bioactivity dat...
Deep Learning Databases, Chemical Protein Kinases Protein Kinase Inhibitors Polypharmacology Datasets as Topic Drug Discovery
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Artificial Intelligence Approach To Investigate the Longevity Drug.

The journal of physical chemistry letters Aug 14, 2019
Longevity is a very important and interesting topic, and has been demonstrated to be related to longevity. We combined network pharmacology, machine learning, deep learning, and molecular dynamics (MD) simulation to investigate potent lead drugs. Re...
Signal Transduction Medicine, Chinese Traditional Klotho Proteins Glucuronidase Receptor, IGF Type 1 Antigens, CD Drug Discovery Protein Interaction Maps Protein Binding Algorithms Artificial Intelligence Databases, Factual Thermodynamics Molecular Docking Simulation Receptor, Insulin Ligands Inhibitory Concentration 50 Binding Sites
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Deep learning in drug discovery: opportunities, challenges and future prospects.

Drug discovery today Aug 1, 2019
Artificial Intelligence (AI) is an area of computer science that simulates the structures and operating principles of the human brain. Machine learning (ML) belongs to the area of AI and endeavors to develop models from exposure to training data. Dee...
Humans Forecasting Drug Discovery Deep Learning
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Combined Ensemble Docking and Machine Learning in Identification of Therapeutic Agents with Potential Inhibitory Effect on Human CES1.

Molecules (Basel, Switzerland) Jul 29, 2019
The human carboxylesterase 1 (CES1), responsible for the biotransformation of many diverse therapeutic agents, may contribute to the occurrence of adverse drug reactions and therapeutic failure through drug interactions. The present study is designed...
Small Molecule Libraries ROC Curve Reproducibility of Results Molecular Dynamics Simulation Molecular Docking Simulation Humans Carboxylic Ester Hydrolases Quantitative Structure-Activity Relationship Drug Discovery Machine Learning Enzyme Activation Protease Inhibitors
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