AIMC Topic: Molecular Structure

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Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method.

International journal of molecular sciences Jul 22, 2019
Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immunodeficiency virus type-1 (HIV-1) and hepatitis C virus (HCV), which is common today in certain popul...
Models, Molecular Molecular Structure Bayes Theorem Hepacivirus Anti-HIV Agents Antiviral Agents Protein Binding Quantitative Structure-Activity Relationship Databases, Pharmaceutical Polypharmacology Hepatitis C HIV-1 Molecular Conformation Humans Machine Learning Algorithms Drug Discovery HIV Infections
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Deep Reinforcement Learning for Multiparameter Optimization in Drug Design.

Journal of chemical information and modeling Jul 5, 2019
In medicinal chemistry programs it is key to design and make compounds that are efficacious and safe. This is a long, complex, and difficult multiparameter optimization process, often including several properties with orthogonal trends. New methods f...
Molecular Structure Neural Networks, Computer Machine Learning Drug Design Drug Discovery Models, Theoretical Models, Molecular
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Evaluating Polymer Representations via Quantifying Structure-Property Relationships.

Journal of chemical information and modeling Jul 3, 2019
Machine learning techniques are being applied in quantifying structure-property relationships for a wide variety of materials, where the properly represented materials play key roles. Although algorithms for representation learning are extensively st...
Models, Molecular Molecular Structure Polymers Machine Learning Structure-Activity Relationship
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Machine learning prediction of cyanobacterial toxin (microcystin) toxicodynamics in humans.

ALTEX Jul 2, 2019
Microcystins (MC) represent a family of cyclic peptides with approx. 250 congeners presumed harmful to human health due to their ability to inhibit ser/thr-proteinphosphatases (PPP), albeit all hazard and risk assessments (RA) are based on data of on...
Humans Molecular Structure Animal Use Alternatives Models, Biological Microcystins Phosphoprotein Phosphatases Machine Learning Computer Simulation Nuclear Proteins
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AGL-Score: Algebraic Graph Learning Score for Protein-Ligand Binding Scoring, Ranking, Docking, and Screening.

Journal of chemical information and modeling Jul 1, 2019
Although algebraic graph theory-based models have been widely applied in physical modeling and molecular studies, they are typically incompetent in the analysis and prediction of biomolecular properties, confirming the common belief that "one cannot ...
Machine Learning Computational Biology Proteins Databases, Protein Molecular Structure Algorithms Molecular Docking Simulation Drug Design
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Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Journal of chemical information and modeling Jun 28, 2019
Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most cases, showing an emerging challenge that is to accurately predict DILI in the early stage. Recently, th...
Machine Learning Algorithms Computer Simulation Molecular Structure Drug Discovery Reproducibility of Results Models, Biological Chemical and Drug Induced Liver Injury Rats Animals Gene Expression Regulation Vinblastine Rats, Sprague-Dawley Male Structure-Activity Relationship
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Machine Learning Models Combined with Virtual Screening and Molecular Docking to Predict Human Topoisomerase I Inhibitors.

Molecules (Basel, Switzerland) Jun 4, 2019
In this work, random forest (RF), support vector machine, k-nearest neighbor and C4.5 decision tree, were used to establish classification models for predicting whether an unknown molecule is an inhibitor of human topoisomerase I (Top1) protein. All ...
Quantitative Structure-Activity Relationship Topoisomerase I Inhibitors Molecular Docking Simulation ROC Curve Molecular Structure Molecular Dynamics Simulation Algorithms Computer Simulation Reproducibility of Results Humans Machine Learning
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Discrimination power of knowledge-based potential dictated by the dominant energies in native protein structures.

Amino acids May 16, 2019
Extracting a well-designed energy function is important for protein structure evaluation. Knowledge-based potential functions are one type of the energy functions which can be obtained from known protein structures. The pairwise potential between ato...
Molecular Structure Proteins Hydrophobic and Hydrophilic Interactions Amino Acids Models, Molecular Protein Conformation Amino Acid Sequence Entropy Knowledge Bases
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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...
Acetylcholinesterase Cholinesterase Inhibitors Galantamine Stereoisomerism Molecular Structure Humans Drug Evaluation, Preclinical Machine Learning Alzheimer Disease Molecular Docking Simulation Ligands Drug Design Cell Line, Tumor Neuroprotective Agents Biological Products
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Predicting drug-target interaction network using deep learning model.

Computational biology and chemistry Mar 25, 2019
BACKGROUND: Traditional methods for drug discovery are time-consuming and expensive, so efforts are being made to repurpose existing drugs. To find new ways for drug repurposing, many computational approaches have been proposed to predict drug-target...
Genes, Neoplasm Databases, Protein Breast Neoplasms Models, Chemical Protein Binding Antineoplastic Agents Protein Domains Drug Repositioning Deep Learning Computational Biology Amino Acid Sequence Molecular Structure Support Vector Machine Databases, Chemical Proteins
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