AIMC Topic: Drug Discovery

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Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives.

Drug discovery today Dec 1, 2021
Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for ...
Drug Discovery Big Data Models, Molecular Artificial Intelligence
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CRNNTL: Convolutional Recurrent Neural Network and Transfer Learning for QSAR Modeling in Organic Drug and Material Discovery.

Molecules (Basel, Switzerland) Nov 30, 2021
Molecular latent representations, derived from autoencoders (AEs), have been widely used for drug or material discovery over the past couple of years. In particular, a variety of machine learning methods based on latent representations have shown exc...
Models, Theoretical ROC Curve Quantitative Structure-Activity Relationship Regression Analysis Area Under Curve Isomerism Neural Networks, Computer Organic Chemicals Binding Sites Databases as Topic Drug Discovery
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A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy.

Bioorganic & medicinal chemistry Nov 27, 2021
Colorectal cancer (CRC) is the third most detected cancer and the second foremost cause of cancer deaths in the world. Intervention targeting p53 provides potential therapeutic strategies, but thus far no p53-based therapy has been successfully trans...
Tumor Suppressor Protein p53 Dihydroergotoxine Humans Machine Learning Drug Screening Assays, Antitumor Colorectal Neoplasms Structure-Activity Relationship Molecular Structure Antineoplastic Agents Dose-Response Relationship, Drug Cell Line, Tumor Cell Proliferation Cell Survival Molecular Docking Simulation Drug Discovery
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Enhancing preclinical drug discovery with artificial intelligence.

Drug discovery today Nov 25, 2021
Artificial intelligence (AI) is becoming an integral part of drug discovery. It has the potential to deliver across the drug discovery and development value chain, starting from target identification and reaching through clinical development. In this...
Machine Learning Drug Discovery Artificial Intelligence
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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 Mice, Inbred ICR Mice Mice, Inbred C57BL Pyridazines Dextran Sulfate Colitis Anti-Inflammatory Agents Protein Kinase Inhibitors Humans Animals Drug Discovery Deep Learning Drug Design Discoidin Domain Receptor 1 Pyrazolones
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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 Drug Design Machine Learning Drug Discovery Precision Medicine
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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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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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Artificial intelligence for the discovery of novel antimicrobial agents for emerging infectious diseases.

Drug discovery today Nov 5, 2021
The search for effective drugs to treat new and existing diseases is a laborious one requiring a large investment of capital, resources, and time. The coronavirus 2019 (COVID-19) pandemic has been a painful reminder of the lack of development of new ...
Animals Drug Discovery COVID-19 Drug Treatment Anti-Infective Agents SARS-CoV-2 Humans Communicable Diseases, Emerging Artificial Intelligence
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Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms.

Trends in cancer Nov 5, 2021
Plants and associated microorganisms are essential sources of natural products against human cancer diseases, partly exemplified by plant-derived anticancer drugs such as Taxol (paclitaxel). Natural products provide diverse mechanisms of action and c...
Drug Discovery Humans Biological Products Artificial Intelligence Lead Machine Learning
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