AIMC Topic: Drug Design

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Deep Learning in Chemistry.

Journal of chemical information and modeling Jun 13, 2019
Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns represented in t...
Drug Design Drug Discovery Deep Learning Humans Neural Networks, Computer Chemistry Techniques, Synthetic Cheminformatics Chemical Phenomena Quantitative Structure-Activity Relationship
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Machine Learning for Molecular Modelling in Drug Design.

Biomolecules Jun 4, 2019
Machine learning (ML) has become a crucial component of early drug discovery. This researcharea has been fueled by two main factors [...].
Drug Design Models, Molecular Machine Learning
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A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs.

Molecules (Basel, Switzerland) Jun 2, 2019
G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Muc...
Drug Discovery Protein Binding Receptors, G-Protein-Coupled Machine Learning Receptor, Serotonin, 5-HT2A Molecular Docking Simulation Algorithms Quantitative Structure-Activity Relationship Molecular Dynamics Simulation Drug Design Humans Binding Sites Ligands
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Pharmacophore features for machine learning in pharmaceutical virtual screening.

Molecular diversity May 27, 2019
Methods of three-dimensional molecular alignment generally treat all pharmacophore features equally when superimposing. However, some pharmacophore features can be more important in a specific system. In this work, we derived the overlap volume of ph...
Models, Molecular Machine Learning Drug Design
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Design of Natural-Product-Inspired Multitarget Ligands by Machine Learning.

ChemMedChem May 16, 2019
A virtual screening protocol based on machine learning models was used to identify mimetics of the natural product (-)-galantamine. This fully automated approach identified eight compounds with bioactivities on at least one of the macromolecular targ...
Cholinesterase Inhibitors Galantamine Stereoisomerism Ligands Acetylcholinesterase Neuroprotective Agents Biological Products Drug Evaluation, Preclinical Alzheimer Disease Molecular Structure Molecular Docking Simulation Drug Design Cell Line, Tumor Humans Machine Learning
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The significance of artificial intelligence in drug delivery system design.

Advanced drug delivery reviews May 6, 2019
Over the last decade, increasing interest has been attracted towards the application of artificial intelligence (AI) technology for analyzing and interpreting the biological or genetic information, accelerated drug discovery, and identification of th...
Humans Drug Delivery Systems Drug Design Artificial Intelligence
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Exploiting machine learning for end-to-end drug discovery and development.

Nature materials Apr 18, 2019
A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These leverage the generally bigger datasets created from...
Drug Discovery Computational Biology Support Vector Machine Humans Drug Repositioning Algorithms Neural Networks, Computer Drug Development Technology, Pharmaceutical Computer Simulation Bayes Theorem Machine Learning Nanomedicine Drug Design
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Applications of machine learning in GPCR bioactive ligand discovery.

Current opinion in structural biology Apr 18, 2019
GPCRs constitute the largest druggable family having targets for 475 Food and Drug Administration (FDA) approved drugs. As GPCRs are of great interest to pharmaceutical industry, enormous efforts are being expended to find relevant and potent GPCR li...
Humans Receptors, G-Protein-Coupled Machine Learning Ligands Drug Design Drug Discovery
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Autonomous Molecular Design: Then and Now.

ACS applied materials & interfaces Mar 25, 2019
The success of deep machine learning in processing of large amounts of data, for example, in image or voice recognition and generation, raises the possibilities that these tools can also be applied for solving complex problems in materials science. I...
Models, Molecular Machine Learning Computer Simulation Drug Design
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Automated discovery of GPCR bioactive ligands.

Current opinion in structural biology Mar 23, 2019
While G-protein-coupled receptors (GPCRs) constitute the largest class of membrane proteins, structures and endogenous ligands of a large portion of GPCRs remain unknown. Because of the involvement of GPCRs in various signaling pathways and physiolog...
Receptors, G-Protein-Coupled Molecular Dynamics Simulation Protein Conformation Molecular Docking Simulation Humans Ligands Machine Learning Drug Design Drug Discovery
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