AIMC Topic: Molecular Conformation

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Visualizing convolutional neural network protein-ligand scoring.

Journal of molecular graphics & modelling Jun 18, 2018
Protein-ligand scoring is an important step in a structure-based drug design pipeline. Selecting a correct binding pose and predicting the binding affinity of a protein-ligand complex enables effective virtual screening. Machine learning techniques c...
Neural Networks, Computer Algorithms Proteins Models, Molecular Ligands Molecular Conformation Deep Learning ROC Curve Protein Binding
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Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water.

Journal of chemical information and modeling May 16, 2018
Prediction of compound properties from structure via quantitative structure-activity relationship and machine-learning approaches is an important computational chemistry task in small-molecule drug research. Though many such properties are dependent ...
Thermodynamics Quantitative Structure-Activity Relationship Gases Informatics Machine Learning Drug Discovery Water Solvents Models, Molecular Molecular Conformation Pharmaceutical Preparations
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Knowledge-Based Conformer Generation Using the Cambridge Structural Database.

Journal of chemical information and modeling Feb 22, 2018
Fast generation of plausible molecular conformations is central to molecular modeling. This paper presents an approach to conformer generation that makes extensive use of the information available in the Cambridge Structural Database. By using geomet...
Algorithms Proteins Databases, Protein Models, Molecular Software Molecular Conformation Macrocyclic Compounds Hydrogen Bonding Knowledge Bases Ligands Databases, Chemical
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Physicochemical characterization and in vitro hypoglycemic activities of polysaccharides from Sargassum pallidum by microwave-assisted aqueous two-phase extraction.

International journal of biological macromolecules Dec 19, 2017
Microwave-assisted aqueous two-phase extraction (MAATPE) was applied for simultaneous extraction and separation of polysaccharides from Sargassum pallidum (SPPs). The optimal extraction parameters, physicochemical properties, and hypoglycemic activit...
Amylases Liquid-Liquid Extraction Humans alpha-Glucosidases Spectroscopy, Fourier Transform Infrared Sargassum Molecular Weight Microscopy, Atomic Force Cell Line, Tumor Models, Molecular Polysaccharides Hypoglycemic Agents Chemical Phenomena Microwaves Molecular Conformation Glycoside Hydrolase Inhibitors Monosaccharides
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De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

Proceedings of the National Academy of Sciences of the United States of America Oct 31, 2017
Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing ...
Molecular Conformation Thermodynamics Phase Transition In Situ Hybridization, Fluorescence Cell Nucleus Genome, Human Chromatin Chromosomes, Human Humans Neural Networks, Computer Animals Epigenesis, Genetic
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Study of Structure-active Relationship for Inhibitors of HIV-1 Integrase LEDGF/p75 Interaction by Machine Learning Methods.

Molecular informatics Feb 28, 2017
HIV-1 integrase (IN) is a promising target for anti-AIDS therapy, and LEDGF/p75 is proved to enhance the HIV-1 integrase strand transfer activity in vitro. Blocking the interaction between IN and LEDGF/p75 is an effective way to inhibit HIV replicati...
Molecular Conformation HIV Integrase Molecular Structure Intercellular Signaling Peptides and Proteins HIV Integrase Inhibitors Protein Binding Structure-Activity Relationship Models, Molecular Humans Reproducibility of Results ROC Curve Machine Learning Computer Simulation
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An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA.

BMC genomics Dec 22, 2016
BACKGROUND: The ability to engineer zinc finger proteins binding to a DNA sequence of choice is essential for targeted genome editing to be possible. Experimental techniques and molecular docking have been successful in predicting protein-DNA interac...
Zinc Fingers Neural Networks, Computer Models, Molecular DNA-Binding Proteins Algorithms Molecular Conformation Protein Binding Binding Sites DNA
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Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility in a Single Descriptor.

Journal of chemical information and modeling Dec 6, 2016
A new molecular descriptor, nConf, based on chemical connectivity, is presented which captures the accessible conformational space of a molecule. Currently the best available two-dimensional descriptors for quantifying the flexibility of a particular...
Crystallization Molecular Conformation Algorithms Machine Learning Drug Design Models, Molecular
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Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction.

Journal of chemical information and modeling Oct 25, 2016
Machine learning (ML) and quantum mechanical (QM) methods can be used in two-way synergy to build chemical reaction expert systems. The proposed ML approach identifies electron sources and sinks among reactants and then ranks all source-sink pairs. T...
Models, Molecular Quantum Theory Machine Learning Molecular Conformation Thermodynamics
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In Silico Calculation of Infinite Dilution Activity Coefficients of Molecular Solutes in Ionic Liquids: Critical Review of Current Methods and New Models Based on Three Machine Learning Algorithms.

Journal of chemical information and modeling Jul 20, 2016
The aim of the paper is to address all the disadvantages of currently available models for calculating infinite dilution activity coefficients (γ(∞)) of molecular solutes in ionic liquids (ILs)-a relevant property from the point of view of many appli...
Ionic Liquids Linear Models Molecular Conformation Solutions Computer Simulation Support Vector Machine Models, Molecular Neural Networks, Computer Machine Learning
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