AIMC Topic: Molecular Structure

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Molecular property prediction: recent trends in the era of artificial intelligence.

Drug discovery today. Technologies Jul 1, 2020
Artificial intelligence (AI) has become a powerful tool in many fields, including drug discovery. Among various AI applications, molecular property prediction can have more significant immediate impact to the drug discovery process since most algorit...
Humans Artificial Intelligence Drug Discovery Molecular Structure
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Talaromydien a and talaroisocoumarin A, new metabolites from the marine-sourced fungus sp. ZZ1616.

Natural product research Jun 17, 2020
New talaromydien A and talaroisocoumarin A (), together with nine known compounds (-), were isolated from a culture of the marine-derived sp. ZZ1616 in potato dextrose broth medium. Structures of the new compounds were elucidated based on their HRE...
Molecular Structure Escherichia coli Talaromyces Candida albicans Anti-Bacterial Agents Methicillin-Resistant Staphylococcus aureus Microbial Sensitivity Tests
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Insight into potent leads for alzheimer's disease by using several artificial intelligence algorithms.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie Jun 16, 2020
Several proteins including S-nitrosoglutathione reductase (GSNOR), complement Factor D, complement 3b (C3b) and Protein Kinase R-like Endoplasmic Reticulum Kinase (PERK), have been demonstrated to be involved in pathogenesis pathways for Alzheimer's ...
Plant Extracts Humans Cognition Artificial Intelligence Signal Transduction Brain Animals Molecular Targeted Therapy Computer-Aided Design Molecular Docking Simulation Drug Design Quantitative Structure-Activity Relationship Drug Discovery Nootropic Agents Molecular Structure Molecular Dynamics Simulation Alzheimer Disease
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Learning Molecular Representations for Medicinal Chemistry.

Journal of medicinal chemistry May 15, 2020
The accurate modeling and prediction of small molecule properties and bioactivities depend on the critical choice of molecular representation. Decades of informatics-driven research have relied on expert-designed molecular descriptors to establish qu...
Cheminformatics Molecular Structure Quantitative Structure-Activity Relationship Chemistry, Pharmaceutical Deep Learning Organic Chemicals Models, Molecular
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The Synthesizability of Molecules Proposed by Generative Models.

Journal of chemical information and modeling Apr 17, 2020
The discovery of functional molecules is an expensive and time-consuming process, exemplified by the rising costs of small molecule therapeutic discovery. One class of techniques of growing interest for early stage drug discovery is molecular genera...
Neural Networks, Computer Algorithms Drug Design Drug Discovery Molecular Structure
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Neural Message Passing for NMR Chemical Shift Prediction.

Journal of chemical information and modeling Apr 13, 2020
Fast and accurate prediction of NMR spectra enables automatic structure validation and elucidation of molecules on a large scale. In this Article, we propose an improved method of learning from an NMR database to predict the chemical shifts of NMR-ac...
Databases, Factual Magnetic Resonance Imaging Molecular Structure Magnetic Resonance Spectroscopy Neural Networks, Computer
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Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.

Pharmacological research Apr 8, 2020
Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data ...
Structure-Activity Relationship Molecular Structure Analgesics Protein Interaction Maps Systems Biology Signal Transduction Systems Integration Chronic Pain Pharmacopoeias as Topic Molecular Targeted Therapy Plant Preparations Pain Threshold Humans Machine Learning Databases, Factual Animals
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Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets.

Stroke and vascular neurology Mar 29, 2020
The discovery of targeted drugs heavily relies on three-dimensional (3D) structures of target proteins. When the 3D structure of a protein target is unknown, it is very difficult to design its corresponding targeted drugs. Although the 3D structures ...
Molecular Targeted Therapy Protein Conformation Pharmaceutical Preparations Data Mining Ligands Computer-Aided Design Structure-Activity Relationship Drug Design Molecular Structure Drug Discovery Big Data Proteins Databases, Protein Humans Artificial Intelligence Animals
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PTML Model of ChEMBL Compounds Assays for Vitamin Derivatives.

ACS combinatorial science Feb 13, 2020
Determining the biological activity of vitamin derivatives is needed given that organic synthesis of analogs of vitamins is an active field of interest for medicinal chemistry, pharmaceuticals, and food additives. Accordingly, scientists from differe...
Machine Learning Databases, Factual Models, Statistical Vitamins Combinatorial Chemistry Techniques Molecular Structure Bayes Theorem
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A deep learning approach for the blind logP prediction in SAMPL6 challenge.

Journal of computer-aided molecular design Jan 30, 2020
Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed u...
Water Molecular Structure Models, Chemical Solubility Thermodynamics Octanols Machine Learning Drug Discovery Deep Learning
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