AIMC Topic: Solvents

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Improved protein relative solvent accessibility prediction using deep multi-view feature learning framework.

Analytical biochemistry Aug 31, 2021
The accurate prediction of the relative solvent accessibility of a protein is critical to understanding its 3D structure and biological function. In this study, a novel deep multi-view feature learning (DMVFL) framework that integrates three differen...
Internet Solvents Protein Structure, Secondary Proteins Databases, Protein Neural Networks, Computer Deep Learning Computational Biology Feedback
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Accurate Estimation of Solvent Accessible Surface Area for Coarse-Grained Biomolecular Structures with Deep Learning.

The journal of physical chemistry. B Aug 12, 2021
Coarse-grained (CG) models of biomolecules have been widely used in protein/ribonucleic acid (RNA) three-dimensional structure prediction, docking, drug design, and molecular simulations due to their superiority in computational efficiency. Most of t...
Proteins Algorithms RNA Deep Learning Solvents
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Optimization of diosgenin extraction from Dioscorea deltoidea tubers using response surface methodology and artificial neural network modelling.

PloS one Jul 21, 2021
INTRODUCTION: Dioscorea deltoidea var. deltoidea (Dioscoreaceae) is a valuable endangered plant of great medicinal and economic importance due to the presence of the bioactive compound diosgenin. In the present study, response surface methodology (RS...
Solvents Chemical Fractionation Neural Networks, Computer Plants, Medicinal Dioscorea Time Particle Size Endangered Species Diosgenin Plant Tubers Temperature Molecular Structure Calibration Models, Theoretical
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Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge.

Journal of computer-aided molecular design Jul 17, 2021
Accurate prediction of lipophilicity-logP-based on molecular structures is a well-established field. Predictions of logP are often used to drive forward drug discovery projects. Driven by the SAMPL7 challenge, in this manuscript we describe the steps...
Machine Learning Drug Discovery Models, Statistical Neural Networks, Computer Thermodynamics Solubility Models, Chemical Solvents Quantum Theory
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning.

International journal of molecular sciences Jul 8, 2021
Theophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and tern...
Choline Solvents Models, Chemical Solubility Theophylline Machine Learning Water
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Uncertainty Quantification and Sensitivity Analysis of Partial Charges on Macroscopic Solvent Properties in Molecular Dynamics Simulations with a Machine Learning Model.

Journal of chemical information and modeling Mar 17, 2021
The molecular dynamics (MD) simulation technique is among the most broadly used computational methods to investigate atomistic phenomena in a variety of chemical and biological systems. One of the most common (and most uncertain) parametrization step...
Solvents Static Electricity Uncertainty Machine Learning Molecular Dynamics Simulation
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Machine Learning Enables Highly Accurate Predictions of Photophysical Properties of Organic Fluorescent Materials: Emission Wavelengths and Quantum Yields.

Journal of chemical information and modeling Feb 23, 2021
The development of functional organic fluorescent materials calls for fast and accurate predictions of photophysical parameters for processes such as high-throughput virtual screening, while the task is challenged by the limitations of quantum mechan...
Fluorescent Dyes Solvents Machine Learning Density Functional Theory
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Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Networks.

Journal of chemical information and modeling Feb 5, 2021
Solvation free energy is a fundamental property that influences various chemical and biological processes, such as reaction rates, protein folding, drug binding, and bioavailability of drugs. In this work, we present a deep learning method based on g...
Thermodynamics Entropy Models, Chemical Neural Networks, Computer Solvents
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Viscosity of Ionic Liquids: Application of the Eyring's Theory and a Committee Machine Intelligent System.

Molecules (Basel, Switzerland) Dec 31, 2020
Accurate determination of the physicochemical characteristics of ionic liquids (ILs), especially viscosity, at widespread operating conditions is of a vital role for various fields. In this study, the viscosity of pure ILs is modeled using three appr...
Ionic Liquids Algorithms Solvents Temperature Support Vector Machine Artificial Intelligence Bayes Theorem Viscosity Thermodynamics
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Presence of emerging organic contaminants and solvents in schools using passive sampling.

The Science of the total environment Oct 13, 2020
In this study, we report on the applicability of passive sampling with Carbopack X adsorbent tubes followed by thermal desorption gas-chromatography-mass spectrometry (TD-GC-MS) to monitor the concentrations of emerging organic contaminants (EOCs) an...
Schools Environmental Monitoring Gas Chromatography-Mass Spectrometry Diffusion Air Pollutants Solvents
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