AIMC Topic: Drug Discovery

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AIEpred: An Ensemble Predictive Model of Classifier Chain to Identify Anti-Inflammatory Peptides.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Anti-inflammatory peptides (AIEs) have recently emerged as promising therapeutic agent for treatment of various inflammatory diseases, such as rheumatoid arthritis and Alzheimer's disease. Therefore, detecting the correlation between amino acid seque...
Peptides Drug Discovery Computational Biology Machine Learning Algorithms Amino Acid Sequence Sequence Analysis, Protein Models, Statistical Anti-Inflammatory Agents
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Exploring Molecular Descriptors and Fingerprints to Predict mTOR Kinase Inhibitors using Machine Learning Techniques.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Mammalian Target of Rapamycin (mTOR) is a Ser/Thr protein kinase, and its role is integral to the autophagy pathway in cancer. Targeting mTOR for therapeutic interventions in cancer through autophagy pathway is challenging due to the dual roles of au...
TOR Serine-Threonine Kinases Protein Kinase Inhibitors Computational Biology Autophagy Humans Machine Learning Neoplasms Algorithms Drug Discovery
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Artificial intelligence for microbial biotechnology: beyond the hype.

Microbial biotechnology Oct 4, 2021
It has been a landmark year for artificial intelligence (AI) and biotechnology. Perhaps the most noteworthy of these advances was Google DeepMind's AlphaFold2 algorithm which smashed records in protein structure prediction (Jumper et al., 2021, Natur...
Drug Discovery Proteins Biotechnology Artificial Intelligence Algorithms
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A decade of machine learning-based predictive models for human pharmacokinetics: Advances and challenges.

Drug discovery today Sep 27, 2021
Traditionally, in vitro and in vivo methods are useful for estimating human pharmacokinetics (PK) parameters; however, it is impractical to perform these complex and expensive experiments on a large number of compounds. The integration of publicly av...
Big Data Pharmacokinetics Machine Learning Humans Drug Discovery Artificial Intelligence Quantitative Structure-Activity Relationship
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Machine-learning methods for ligand-protein molecular docking.

Drug discovery today Sep 21, 2021
Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains use AI, including molecular simulation for drug discovery. In this review, we provide an overview of ligand-protein molecular docking and how machine learnin...
Humans Machine Learning Molecular Docking Simulation Artificial Intelligence Ligands Drug Discovery Deep Learning
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TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning.

Journal of chemical information and modeling Sep 16, 2021
One of the most challenging tasks in the drug-discovery process is the efficient identification of small molecules with desired phenotypes. In this study, we propose a novel computational method for omics-based drug design, which we call TRIOMPHE (t...
Phenotype Drug Design Transcriptome Drug Discovery Machine Learning
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Comprehensive Survey of Recent Drug Discovery Using Deep Learning.

International journal of molecular sciences Sep 15, 2021
Drug discovery based on artificial intelligence has been in the spotlight recently as it significantly reduces the time and cost required for developing novel drugs. With the advancement of deep learning (DL) technology and the growth of drug-related...
Pharmaceutical Preparations Surveys and Questionnaires Drug Development Neural Networks, Computer Drug Discovery Animals Deep Learning Humans Drug Design
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Accelerating antibiotic discovery through artificial intelligence.

Communications biology Sep 9, 2021
By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics, therapies decline in efficacy and must be replaced, distinguish...
Drug Discovery Antimicrobial Peptides Reproducibility of Results Drug Design Machine Learning Anti-Bacterial Agents Artificial Intelligence
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A machine learning framework for predicting drug-drug interactions.

Scientific reports Sep 2, 2021
Understanding drug-drug interactions is an essential step to reduce the risk of adverse drug events before clinical drug co-prescription. Existing methods, commonly integrating heterogeneous data to increase model performance, often suffer from a hig...
Signal Transduction Drug Interactions Protein Interaction Maps Computational Biology Machine Learning Drug Discovery Humans
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From computer-aided drug discovery to computer-driven drug discovery.

Drug discovery today. Technologies Aug 30, 2021
Computational chemistry and structure-based design have traditionally been viewed as a subset of tools that could aid acceleration of the drug discovery process, but were not commonly regarded as a driving force in small molecule drug discovery. In t...
Drug Design Computers Artificial Intelligence Drug Discovery Proteins Computer-Aided Design Machine Learning
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