AIMC Topic: Molecular Structure

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Machine Learning Prediction of the Energy Gap of Graphene Nanoflakes Using Topological Autocorrelation Vectors.

ACS combinatorial science Sep 14, 2016
The possibility of band gap engineering in graphene opens countless new opportunities for application in nanoelectronics. In this work, the energy gaps of 622 computationally optimized graphene nanoflakes were mapped to topological autocorrelation ve...
Nanostructures Graphite Energy Transfer Machine Learning Models, Molecular Molecular Structure
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ROCS-derived features for virtual screening.

Journal of computer-aided molecular design Sep 8, 2016
Rapid overlay of chemical structures (ROCS) is a standard tool for the calculation of 3D shape and chemical ("color") similarity. ROCS uses unweighted sums to combine many aspects of similarity, yielding parameter-free models for virtual screening. I...
Drug Design Models, Molecular Machine Learning Molecular Structure Pharmaceutical Preparations Algorithms Computer-Aided Design
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Molecular graph convolutions: moving beyond fingerprints.

Journal of computer-aided molecular design Aug 24, 2016
Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structur...
Neural Networks, Computer Machine Learning Pharmaceutical Preparations Computer-Aided Design Ligands Drug Design Computer Graphics Molecular Structure
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Developing a support vector machine based QSPR model for prediction of half-life of some herbicides.

Ecotoxicology and environmental safety Mar 9, 2016
The half-life (t1/2) of 58 herbicides were modeled by quantitative structure-property relationship (QSPR) based molecular structure descriptors. After calculation and the screening of a large number of molecular descriptors, the most relevant those o...
Models, Chemical Half-Life Nonlinear Dynamics Support Vector Machine Molecular Structure Herbicides Linear Models Quantitative Structure-Activity Relationship
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Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

Regulatory toxicology and pharmacology : RTP Feb 13, 2016
Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guidelin...
Amines Data Mining Pattern Recognition, Automated Mutagens Quantitative Structure-Activity Relationship Mutagenesis Mutagenicity Tests Models, Molecular Molecular Structure Knowledge Bases Animals Risk Assessment Humans Databases, Factual Computer Simulation
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Structure-response relationship in electrospray ionization-mass spectrometry of sartans by artificial neural networks.

Journal of chromatography. A Feb 9, 2016
Quantitative structure-property relationship (QSPR) methods are based on the hypothesis that changes in the molecular structure are reflected in changes in the observed property of the molecule. Artificial neural network is a technique of data analys...
Spectrometry, Mass, Electrospray Ionization Quantitative Structure-Activity Relationship Angiotensin II Type 1 Receptor Blockers Algorithms Chromatography, Liquid Molecular Structure Neural Networks, Computer
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Network-based in silico drug efficacy screening.

Nature communications Feb 1, 2016
The increasing cost of drug development together with a significant drop in the number of new drug approvals raises the need for innovative approaches for target identification and efficacy prediction. Here, we take advantage of our increasing unders...
Drug Discovery Structure-Activity Relationship Molecular Structure Neural Networks, Computer Computer Simulation Models, Biological
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Preparation, Characterization, and Antitumor Activities of Miriplatin-Loaded Liposomes.

Journal of pharmaceutical sciences Dec 22, 2015
Because of the insolubility of miriplatin in water, miriplatin and lipiodol suspension is the sole formulation of miriplatin approved in Japan to treat hepatocellular carcinoma by transcatheter arterial chemoembolization. Until now, there have been n...
Organoplatinum Compounds Drug Storage Drug Compounding Particle Size Surface Properties Molecular Structure Cell Line, Tumor Chromatography, High Pressure Liquid Humans Apoptosis Cell Survival Antineoplastic Agents Solubility Liposomes Drug Stability
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Ligand-Based Virtual Screening in a Search for Novel Anti-HIV-1 Chemotypes.

Journal of chemical information and modeling Oct 9, 2015
In a search for new anti-HIV-1 chemotypes, we developed a multistep ligand-based virtual screening (VS) protocol combining machine learning (ML) methods with the privileged structures (PS) concept. In its learning step, the VS protocol was based on H...
Models, Molecular Molecular Structure Drug Evaluation, Preclinical Biological Assay HIV-1 Ligands Machine Learning Cells, Cultured Anti-HIV Agents Humans Inhibitory Concentration 50 HIV Integrase Inhibitors
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Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

SAR and QSAR in environmental research Sep 21, 2015
Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales t...
Computer Communication Networks Computer Simulation Computational Biology Biological Ontologies Models, Molecular Quantitative Structure-Activity Relationship Molecular Structure Vocabulary, Controlled Information Dissemination
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