AIMC Topic: Drug Discovery

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An Ensemble Learning-Based Method for Inferring Drug-Target Interactions Combining Protein Sequences and Drug Fingerprints.

BioMed research international Apr 24, 2021
Identifying the interactions of the drug-target is central to the cognate areas including drug discovery and drug reposition. Although the high-throughput biotechnologies have made tremendous progress, the indispensable clinical trials remain to be e...
Drug Interactions Machine Learning Computational Biology Drug Discovery Amino Acid Sequence Position-Specific Scoring Matrices Support Vector Machine Databases, Protein
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Deep Learning in Virtual Screening: Recent Applications and Developments.

International journal of molecular sciences Apr 23, 2021
Drug discovery is a cost and time-intensive process that is often assisted by computational methods, such as virtual screening, to speed up and guide the design of new compounds. For many years, machine learning methods have been successfully applied...
Technology, Pharmaceutical Deep Learning Humans Computational Biology Drug Design Proteins Neural Networks, Computer Drug Discovery
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COVID-19 in the Age of Artificial Intelligence: A Comprehensive Review.

Interdisciplinary sciences, computational life sciences Apr 22, 2021
The recent COVID-19 pandemic, which broke at the end of the year 2019 in Wuhan, China, has infected more than 98.52 million people by today (January 23, 2021) with over 2.11 million deaths across the globe. To combat the growing pandemic on urgent ba...
Therapy, Computer-Assisted Drug Discovery Severity of Illness Index Diagnosis, Computer-Assisted Antiviral Agents COVID-19 Testing COVID-19 Drug Treatment Humans Biomedical Research Artificial Intelligence Computer-Aided Design COVID-19 Drug Design Decision Support Techniques Prognosis Clinical Decision-Making
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Machine learning guided aptamer refinement and discovery.

Nature communications Apr 22, 2021
Aptamers are single-stranded nucleic acid ligands that bind to target molecules with high affinity and specificity. They are typically discovered by searching large libraries for sequences with desirable binding properties. These libraries, however, ...
Machine Learning Ligands Protein Binding Gene Library Models, Chemical Computer Simulation Lipocalin-2 Drug Discovery Aptamers, Nucleotide
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Predicting drug metabolism and pharmacokinetics features of in-house compounds by a hybrid machine-learning model.

Drug metabolism and pharmacokinetics Apr 20, 2021
We constructed machine learning-based pharmacokinetic prediction models with very high performance. The models were trained on 26138 and 16613 compounds involved in metabolic stability and cytochrome P450 inhibition, respectively. Because the compoun...
Predictive Value of Tests Pharmaceutical Preparations Cytochrome P-450 Enzyme System Inactivation, Metabolic Pharmacokinetics Reproducibility of Results Humans Quantitative Structure-Activity Relationship Drug Discovery Machine Learning Metabolic Clearance Rate Computer Simulation
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AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders.

BMC bioinformatics Apr 20, 2021
BACKGROUND: Drug-target interaction (DTI) plays a vital role in drug discovery. Identifying drug-target interactions related to wet-lab experiments are costly, laborious, and time-consuming. Therefore, computational methods to predict drug-target int...
Drug Discovery Drug Development Unsupervised Machine Learning Algorithms Amino Acid Sequence
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Critical assessment of AI in drug discovery.

Expert opinion on drug discovery Apr 19, 2021
: Artificial Intelligence (AI) has become a component of our everyday lives, with applications ranging from recommendations on what to buy to the analysis of radiology images. Many of the techniques originally developed for other fields such as langu...
Machine Learning Drug Discovery Humans Artificial Intelligence
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Ligand-Receptor Interactions and Machine Learning in GCGR and GLP-1R Drug Discovery.

International journal of molecular sciences Apr 14, 2021
The large amount of data that has been collected so far for G protein-coupled receptors requires machine learning (ML) approaches to fully exploit its potential. Our previous ML model based on gradient boosting used for prediction of drug affinity an...
Machine Learning Drug Discovery Ligands Glucagon-Like Peptide-1 Receptor
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Knowledge graphs and their applications in drug discovery.

Expert opinion on drug discovery Apr 12, 2021
INTRODUCTION: Knowledge graphs have proven to be promising systems of information storage and retrieval. Due to the recent explosion of heterogeneous multimodal data sources generated in the biomedical domain, and an industry shift toward a systems b...
Humans Machine Learning Drug Repositioning COVID-19 Drug Treatment Computer Graphics Algorithms Drug Discovery Systems Biology
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Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

Molecular diversity Apr 12, 2021
Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design a...
Humans Chemistry Techniques, Synthetic Drug Design Models, Molecular Algorithms Drug Discovery Data Mining Deep Learning Artificial Intelligence Research Design Quantitative Structure-Activity Relationship Big Data Machine Learning Animals Drug Development Support Vector Machine
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