AIMC 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...
Ligands Inhibitory Concentration 50 Binding Sites Glucuronidase Receptor, IGF Type 1 Drug Discovery Antigens, CD Protein Interaction Maps Protein Binding Signal Transduction Medicine, Chinese Traditional Klotho Proteins Algorithms Thermodynamics Databases, Factual Artificial Intelligence Receptor, Insulin Molecular Docking Simulation
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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...
Forecasting Drug Discovery Deep Learning Humans
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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...
Enzyme Activation Protease Inhibitors Small Molecule Libraries Molecular Dynamics Simulation Carboxylic Ester Hydrolases Quantitative Structure-Activity Relationship Humans Machine Learning Molecular Docking Simulation Reproducibility of Results Drug Discovery ROC Curve
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Applicability Domain of Active Learning in Chemical Probe Identification: Convergence in Learning from Non-Specific Compounds and Decision Rule Clarification.

Molecules (Basel, Switzerland) Jul 26, 2019
Efficient identification of chemical probes for the manipulation and understanding of biological systems demands specificity for target proteins. Computational means to optimize candidate compound selection for experimental selectivity evaluation are...
Chemical Phenomena Databases, Chemical Quantitative Structure-Activity Relationship Reproducibility of Results Models, Theoretical Machine Learning Drug Discovery Decision Trees Algorithms Computational Biology Ligands Decision Support Techniques
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Learning-to-rank technique based on ignoring meaningless ranking orders between compounds.

Journal of molecular graphics & modelling Jul 24, 2019
Learning-to-rank, which is a machine-learning technique for information retrieval, was recently introduced to ligand-based virtual screening to reduce the costs of developing a new drug. The quality of a rank prediction model depends on experimental ...
Algorithms Humans Drug Discovery Machine Learning Models, Theoretical
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Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method.

International journal of molecular sciences Jul 22, 2019
Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immunodeficiency virus type-1 (HIV-1) and hepatitis C virus (HCV), which is common today in certain popul...
Humans Machine Learning Algorithms Hepatitis C Molecular Structure Quantitative Structure-Activity Relationship Drug Discovery HIV-1 Antiviral Agents Bayes Theorem HIV Infections Databases, Pharmaceutical Molecular Conformation Hepacivirus Protein Binding Anti-HIV Agents Polypharmacology Models, Molecular
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The Art of Virtualizing Pharma R&D.

Drug discovery today Jul 16, 2019
Drug Discovery Drug Industry Artificial Intelligence Software
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Advancing Drug Discovery via Artificial Intelligence.

Trends in pharmacological sciences Jul 15, 2019
Drug discovery and development are among the most important translational science activities that contribute to human health and wellbeing. However, the development of a new drug is a very complex, expensive, and long process which typically costs 2....
Quantitative Structure-Activity Relationship Artificial Intelligence Animals Drug Discovery Pharmaceutical Preparations Humans Translational Research, Biomedical Pharmacology
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Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery.

Chemical reviews Jul 11, 2019
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides opportunities for the discovery and development of innovative drugs. Various machine learning approaches have recently (re)emerged, some of which may be ...
Machine Learning Algorithms Drug Design Neural Networks, Computer Artificial Intelligence Drug Discovery Bayes Theorem Small Molecule Libraries
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Improved Prediction of Drug-Target Interactions Using Self-Paced Learning with Collaborative Matrix Factorization.

Journal of chemical information and modeling Jul 11, 2019
Identifying drug-target interactions (DTIs) plays an important role in the field of drug discovery, drug side-effects, and drug repositioning. However, in vivo or biochemical experimental methods for identifying new DTIs are extremely expensive and t...
Machine Learning Drug Discovery Computational Biology Drug Repositioning Drug-Related Side Effects and Adverse Reactions
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