AIMC Topic: Solvents

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Predicting drug solubility in organic solvents mixtures: A machine-learning approach supported by high-throughput experimentation.

International journal of pharmaceutics May 18, 2024
A novel approach based on supervised machine-learning is proposed to predict the solubility of drugs and drug-like molecules in mixtures of organic solvents. Similar to quantitative structure-property relationship (QSPR) models, different solvent typ...
Least-Squares Analysis Pharmaceutical Preparations Temperature Organic Chemicals High-Throughput Screening Assays Quantitative Structure-Activity Relationship Solubility Solvents Machine Learning
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen.

Molecules (Basel, Switzerland) May 14, 2024
Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or bet...
Machine Learning Solubility Solvents Hydrogen Bonding Deep Eutectic Solvents Ibuprofen Ketoprofen Cyclooxygenase Inhibitors
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Predicting Solvatochromism of Chromophores in Proteins through QM/MM and Machine Learning.

The journal of physical chemistry. A Apr 29, 2024
Solvatochromism occurs in both homogeneous solvents and more complex biological environments, such as proteins. While in both cases the solvatochromic effects report on the surroundings of the chromophore, their interpretation in proteins becomes mor...
Molecular Dynamics Simulation Quantum Theory Machine Learning Proteins Solvents Carotenoids
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Calculation of solvation force in molecular dynamics simulation by deep-learning method.

Biophysical journal Mar 4, 2024
Electrostatic calculations are generally used in studying the thermodynamics and kinetics of biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann equation on a large grid system, a process known to be time consuming....
Molecular Dynamics Simulation Solubility Solvents Thermodynamics Deep Learning
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Building an ab initio solvated DNA model using Euclidean neural networks.

PloS one Feb 15, 2024
Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecule...
Solvents DNA Neural Networks, Computer
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Bound ion effects: Using machine learning method to study the kinesin Ncd's binding with microtubule.

Biophysical journal Dec 30, 2023
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions tha...
Animals Protein Binding Molecular Dynamics Simulation Ions Tubulin Drosophila Proteins Machine Learning Protein Multimerization Static Electricity Kinesins Solvents Microtubules
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Application of Machine Learning Algorithms to Metadynamics for the Elucidation of the Binding Modes and Free Energy Landscape of Drug/Target Interactions: a Case Study.

Chemistry (Weinheim an der Bergstrasse, Germany) Sep 28, 2023
In the context of drug discovery, computational methods were able to accelerate the challenging process of designing and optimizing a new drug candidate. Amongst the possible atomistic simulation approaches, metadynamics (metaD) has proven very power...
Algorithms Molecular Dynamics Simulation Machine Learning Thermodynamics Solvents
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Explainable Supervised Machine Learning Model To Predict Solvation Gibbs Energy.

Journal of chemical information and modeling Aug 21, 2023
Many challenges persist in developing accurate computational models for predicting solvation free energy (Δ). Despite recent developments in Machine Learning (ML) methodologies that outperformed traditional quantum mechanical models, several issues r...
Solvents Solutions Water Thermodynamics Supervised Machine Learning
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A modular strategy for distributed, embodied control of electronics-free soft robots.

Science advances Jul 7, 2023
Robots typically interact with their environments via feedback loops consisting of electronic sensors, microcontrollers, and actuators, which can be bulky and complex. Researchers have sought new strategies for achieving autonomous sensing and contro...
Feedback Robotics Solvents Elastomers
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Reduced Order Machine Learning Models for Accurate Prediction of CO Capture in Physical Solvents.

Environmental science & technology Jul 3, 2023
CO sorption in physical solvents is one of the promising approaches for carbon capture from highly concentrated CO streams at high pressures. Identifying an efficient solvent and evaluating its solubility data at different operating conditions are hi...
Machine Learning Carbon Dioxide Solvents
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