AIMC Topic: Solvents
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Prediction Enhancement of Residue Real-Value Relative Accessible Surface Area in Transmembrane Helical Proteins by Solving the Output Preference Problem of Machine Learning-Based Predictors.
Journal of chemical information and modeling
Oct 20, 2015
The α-helical transmembrane proteins constitute 25% of the entire human proteome space and are difficult targets in high-resolution wet-lab structural studies, calling for accurate computational predictors. We present a novel sequence-based method ca...
Hydrophilic Ionic Liquids as Ingredients of Gel-Based Dermal Formulations.
AAPS PharmSciTech
Oct 1, 2015
Ionic liquids (ILs) have several properties that offer many advantages in dermal drug delivery systems. Depending on the chemical structure, ILs can be used for protection against microorganisms, to enhance skin penetration, and as a solvent. In the ...
Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.
Scientific reports
Jun 22, 2015
Direct prediction of protein structure from sequence is a challenging problem. An effective approach is to break it up into independent sub-problems. These sub-problems such as prediction of protein secondary structure can then be solved independentl...
Size Control in the Nanoprecipitation Process of Stable Iodine (¹²⁷I) Using Microchannel Reactor-Optimization by Artificial Neural Networks.
AAPS PharmSciTech
Feb 6, 2015
In this study, nanosuspension of stable iodine ((127)I) was prepared by nanoprecipitation process in microfluidic devices. Then, size of particles was optimized using artificial neural networks (ANNs) modeling. The size of prepared particles was eval...
Intelligent transformation of ultrasound-assisted novel solvent extraction plant active ingredients: Tools for machine learning and deep learning.
Food chemistry
Sep 15, 2025
Ultrasound-assisted novel solvent extraction enhances plant bioactive compound yield via cavitation, mechanical, and thermal mechanisms. However, the high designability of novel solvents, the multiple influence factors for extracting results, the com...
Extracting Residue Solvent Exposure from Covalent Labeling Data with Machine Learning: A Hybrid Approach for Protein Structure Prediction.
Journal of the American Society for Mass Spectrometry
Jun 4, 2025
Hydroxyl radical protein footprinting (HRPF) coupled with mass spectrometry yields information about residue solvent exposure and protein topology. However, data from these experiments are sparse and require computational interpretation to generate u...
Deciphering the structural complexity of esterases in Amycolatopsis eburnea: A comprehensive exploration of solvent accessibility patterns.
Computers in biology and medicine
Jun 1, 2025
Carboxylesterases (CES) are pivotal enzymes in the hydrolysis of carboxylic esters, playing fundamental roles in both biological systems and biotechnological applications. This study investigates CES from the Amycolatopsis genus, characterized by its...
Predicting the solubility of drugs in supercritical carbon dioxide using machine learning and atomic contribution.
European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
Jun 1, 2025
The pharmaceutical sector is aware of supercritical CO (SC-CO) as a possible replacement for problematic organic solvents. Using a novel artificial intelligence (AI) strategy to predict drug solubility using the SC-CO system mathematically has been d...
CrypTothML: An Integrated Mixed-Solvent Molecular Dynamics Simulation and Machine Learning Approach for Cryptic Site Prediction.
International journal of molecular sciences
May 14, 2025
Cryptic sites, which are transient binding sites that emerge through protein conformational changes upon ligand binding, are valuable targets for drug discovery, particularly for allosteric modulators. However, identifying these sites remains challen...
Prediction of the Appropriate Temperature and Pressure for Polymer Dissolution Using Machine Learning Models.
Molecular informatics
Feb 1, 2025
The widespread use of polymer solutions in the chemical industry poses a significant challenge in determining optimal dissolution conditions. Traditionally, researchers have relied on experimental methods to estimate the processing parameters needed ...
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