AIMC Topic: Drug Design

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Network-Based Assessment of Adverse Drug Reaction Risk in Polypharmacy Using High-Throughput Screening Data.

International journal of molecular sciences Jan 17, 2019
The risk of adverse drug reactions increases in a polypharmacology setting. High-throughput drug screening with transcriptomics applied to human cells has shown that drugs have effects on several molecular pathways, and these affected pathways may be...
Drug Design Data Interpretation, Statistical High-Throughput Screening Assays Polypharmacy Drug-Related Side Effects and Adverse Reactions Algorithms Risk Assessment Humans Neural Networks, Computer
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Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy.

Pharmaceutical research Jan 7, 2019
PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse side effect of cancer chemotherapy that can be life debilitating and cause extreme pain. The multifactorial and poorly understood mechanisms of toxicity have impeded the i...
Machine Learning Neoplasms Drug Design Humans Neural Networks, Computer Structure-Activity Relationship Molecular Structure Peripheral Nervous System Diseases Antineoplastic Agents Incidence
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De Novo Molecule Design by Translating from Reduced Graphs to SMILES.

Journal of chemical information and modeling Dec 21, 2018
A key component of automated molecular design is the generation of compound ideas for subsequent filtering and assessment. Recently deep learning approaches have been explored as alternatives to traditional de novo molecular design techniques. Deep l...
Pharmaceutical Preparations Cheminformatics Models, Molecular Molecular Structure Drug Design Deep Learning Databases, Pharmaceutical
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Converging a Knowledge-Based Scoring Function: DrugScore.

Journal of chemical information and modeling Dec 18, 2018
We present DrugScore, a new version of the knowledge-based scoring function DrugScore, which builds upon the same formalism used to derive DrugScore but exploits a training data set of nearly 40 000 X-ray complex structures, a highly diverse and the,...
Knowledge Bases Ligands Informatics Drug Design Models, Molecular
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Deep Convolutional Neural Networks for the Prediction of Molecular Properties: Challenges and Opportunities Connected to the Data.

Journal of integrative bioinformatics Dec 5, 2018
We present a flexible deep convolutional neural network method for the analysis of arbitrary sized graph structures representing molecules. This method, which makes use of the Lipinski RDKit module, an open-source cheminformatics software, enables th...
Drug Design Pharmaceutical Preparations Databases, Pharmaceutical Machine Learning Software Humans Neural Networks, Computer
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The convergence of artificial intelligence and chemistry for improved drug discovery.

Future medicinal chemistry Nov 30, 2018
Pharmaceutical Preparations Chemistry Techniques, Synthetic Drug Design Drug Discovery Humans Artificial Intelligence Computer-Aided Design
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Advances with support vector machines for novel drug discovery.

Expert opinion on drug discovery Nov 29, 2018
Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learni...
Machine Learning Drug Design Humans Quantitative Structure-Activity Relationship Drug Discovery Support Vector Machine
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An overview of neural networks for drug discovery and the inputs used.

Expert opinion on drug discovery Nov 17, 2018
: Artificial intelligence systems based on neural networks (NNs) find rules for drug discovery according to training molecules, but first, the molecules need to be represented in certain ways. Molecular descriptors and fingerprints have been used as ...
Artificial Intelligence Drug Design Deep Learning Ligands Drug Discovery Humans Neural Networks, Computer
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Sequence-based analysis and prediction of lantibiotics: A machine learning approach.

Computational biology and chemistry Oct 9, 2018
Lantibiotics, an important group of ribosomally synthesized peptides, represent an important arsenal of novel promising antimicrobials showing high potency in fighting against the prevalence of antibiotic resistance among microbial pathogens. However...
Computer-Aided Design Drug Design Algorithms Glutamic Acid Machine Learning Anti-Bacterial Agents Bacteriocins Amino Acid Sequence Leucine
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Deep Learning in Drug Discovery and Medicine; Scratching the Surface.

Molecules (Basel, Switzerland) Sep 18, 2018
The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cure, has seen a sea change from the discerning hands of the neighborhood physician to the use of sophisticated machines to use of information gleaned f...
Drug Design Drug Discovery Drug Repositioning Deep Learning Precision Medicine Neural Networks, Computer Point-of-Care Systems Artificial Intelligence
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