AIMC Topic: Drug Discovery

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A Review on Applications of Computational Methods in Drug Screening and Design.

Molecules (Basel, Switzerland) Mar 18, 2020
Drug development is one of the most significant processes in the pharmaceutical industry. Various computational methods have dramatically reduced the time and cost of drug discovery. In this review, we firstly discussed roles of multiscale biomolecul...
Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Drug Design Drug Discovery
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Machine learning prediction of oncology drug targets based on protein and network properties.

BMC bioinformatics Mar 14, 2020
BACKGROUND: The selection and prioritization of drug targets is a central problem in drug discovery. Computational approaches can leverage the growing number of large-scale human genomics and proteomics data to make in-silico target identification, r...
Machine Learning Computer Simulation Humans Area Under Curve Protein Interaction Maps Drug Discovery Genomics Antineoplastic Agents Proteins
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HNet-DNN: Inferring New Drug-Disease Associations with Deep Neural Network Based on Heterogeneous Network Features.

Journal of chemical information and modeling Mar 13, 2020
Drug research and development is a time-consuming and high-cost task, pressing an urgent demand to identify novel indications of approved drugs, referred to as drug repositioning, which provides an economical and efficient way for drug discovery. Wit...
Computational Biology Neural Networks, Computer Drug Repositioning Drug Discovery Pharmaceutical Preparations
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Machine learning models for drug-target interactions: current knowledge and future directions.

Drug discovery today Mar 12, 2020
Predicting the binding affinity between compounds and proteins with reasonable accuracy is crucial in drug discovery. Computational prediction of binding affinity between compounds and targets greatly enhances the probability of finding lead compound...
Proteins Ligands Deep Learning Computational Biology Drug Development Drug Delivery Systems Drug Discovery Humans Machine Learning
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Machine Learning in Drug Discovery and Development Part 1: A Primer.

CPT: pharmacometrics & systems pharmacology Mar 11, 2020
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and develop...
Drug Approval History, 20th Century Algorithms Drug Discovery Drug Development Predictive Value of Tests Models, Theoretical Humans Artificial Intelligence Machine Learning
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Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?

Clinical pharmacology and therapeutics Mar 3, 2020
As the field of artificial intelligence and machine learning (AI/ML) for drug discovery is rapidly advancing, we address the question "What is the impact of recent AI/ML trends in the area of Clinical Pharmacology?" We address difficulties and AI/ML ...
Clinical Trials as Topic Humans Pharmacology, Clinical Animals Drug Discovery Artificial Intelligence
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DeepAVP: A Dual-Channel Deep Neural Network for Identifying Variable-Length Antiviral Peptides.

IEEE journal of biomedical and health informatics Feb 28, 2020
Antiviral peptides (AVPs) have been experimentally verified to block virus into host cells, which have antiviral activity with decapeptide amide. Therefore, utilization of experimentally validated antiviral peptides is a potential alternative strateg...
Antiviral Agents Computational Biology Neural Networks, Computer Drug Discovery Deep Learning Peptides
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A Deep Learning-Based Chemical System for QSAR Prediction.

IEEE journal of biomedical and health informatics Feb 28, 2020
Research on quantitative structure-activity relationships (QSAR) provides an effective approach to determine new hits and promising lead compounds during drug discovery. In the past decades, various works have gained good performance for QSAR with th...
Quantitative Structure-Activity Relationship Models, Chemical Pharmaceutical Preparations Deep Learning Drug Discovery Computational Biology
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Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Clinical pharmacology and therapeutics Feb 28, 2020
Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this s...
Drug Evaluation, Preclinical Drug-Related Side Effects and Adverse Reactions Adverse Drug Reaction Reporting Systems Animals Humans Drug Discovery Machine Learning
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Discovery of Small-Molecule Activators for Glucose-6-Phosphate Dehydrogenase (G6PD) Using Machine Learning Approaches.

International journal of molecular sciences Feb 23, 2020
Glucose-6-Phosphate Dehydrogenase (G6PD) is a ubiquitous cytoplasmic enzyme converting glucose-6-phosphate into 6-phosphogluconate in the pentose phosphate pathway (PPP). The G6PD deficiency renders the inability to regenerate glutathione due to lack...
Humans Machine Learning Animals Oxidative Stress Oxidation-Reduction Glucosephosphate Dehydrogenase Deficiency Molecular Docking Simulation Drug Discovery Glucosephosphate Dehydrogenase Glutathione NADP Drug Evaluation, Preclinical X-Ray Diffraction Pentose Phosphate Pathway Catalytic Domain Protein Interaction Domains and Motifs
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