AIMC Topic: Drug Design

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Chemical Reactivity Prediction: Current Methods and Different Application Areas.

Molecular informatics Jan 22, 2022
The ability to predict chemical reactivity of a molecule is highly desirable in drug discovery, both ex vivo (synthetic route planning, formulation, stability) and in vivo: metabolic reactions determine pharmacodynamics, pharmacokinetics and potentia...
Drug Design Drug Discovery Cheminformatics Machine Learning Algorithms
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Can Generative-Model-Based Drug Design Become a New Normal in Drug Discovery?

Journal of medicinal chemistry Dec 16, 2021
It is still rare that AI application examples with full DMTA (Design, Make, Test, Analysis) outcomes are reported. A recent study highlights that a generative model could be applied in the drug discovery process through an example in which ideas gene...
Neural Networks, Computer Artificial Intelligence Drug Discovery Deep Learning Drug Design Humans
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Systems biology and machine learning approaches identify drug targets in diabetic nephropathy.

Scientific reports Dec 6, 2021
Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic appr...
Algorithms Animals Male Humans Machine Learning Gene Regulatory Networks Mice Diabetic Nephropathies Drug Design Gene Expression Profiling Global Health Oligonucleotide Array Sequence Analysis Mice, Inbred DBA Kidney Cortex Chemistry, Pharmaceutical Microarray Analysis Kidney Medulla Epigenesis, Genetic Signal Transduction Cluster Analysis Support Vector Machine MicroRNAs Principal Component Analysis Computational Biology Linear Models Systems Biology Regression Analysis
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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...
Drug Screening Assays, Antitumor Molecular Structure Humans Anti-Inflammatory Agents Animals Protein Kinase Inhibitors Deep Learning Drug Design Mice, Inbred ICR Mice Colitis Drug Discovery Pyridazines Discoidin Domain Receptor 1 Mice, Inbred C57BL Dextran Sulfate Pyrazolones
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Deep learning approaches for de novo drug design: An overview.

Current opinion in structural biology Nov 22, 2021
De novo drug design is the process of generating novel lead compounds with desirable pharmacological and physiochemical properties. The application of deep learning (DL) in de novo drug design has become a hot topic, and many DL-based approaches have...
Deep Learning Neural Networks, Computer Drug Design
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Drug Design: Where We Are and Future Prospects.

Molecules (Basel, Switzerland) Nov 22, 2021
Medicinal chemistry is facing new challenges in approaching precision medicine. Several powerful new tools or improvements of already used tools are now available to medicinal chemists to help in the process of drug discovery, from a hit molecule to ...
Chemistry, Pharmaceutical Humans Precision Medicine Drug Design Machine Learning Drug Discovery
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Structure-Based Drug Design Using Deep Learning.

Journal of chemical information and modeling Nov 18, 2021
In recent years, deep learning-based methods have emerged as promising tools for drug design. Most of these methods are ligand-based, where an initial target-specific ligand data set is necessary to design potent molecules with optimized properties....
Deep Learning Proteins Drug Design Ligands Models, Molecular
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Don't Overweight Weights: Evaluation of Weighting Strategies for Multi-Task Bioactivity Classification Models.

Molecules (Basel, Switzerland) Nov 18, 2021
Machine learning models predicting the bioactivity of chemical compounds belong nowadays to the standard tools of cheminformaticians and computational medicinal chemists. Multi-task and federated learning are promising machine learning approaches tha...
Small Molecule Libraries Humans Drug Design Machine Learning Drug Discovery
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Active Learning for Drug Design: A Case Study on the Plasma Exposure of Orally Administered Drugs.

Journal of medicinal chemistry Nov 15, 2021
The success of artificial intelligence (AI) models has been limited by the requirement of large amounts of high-quality training data, which is just the opposite of the situation in most drug discovery pipelines. Active learning (AL) is a subfield of...
Administration, Oral Problem-Based Learning Drug Design Machine Learning Pharmaceutical Preparations
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Artificial Intelligence for Autonomous Molecular Design: A Perspective.

Molecules (Basel, Switzerland) Nov 9, 2021
Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reaso...
Drug Design Drug Discovery Automation Machine Learning
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