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Thermodynamics

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Artificial neural networks (ANN)-genetic algorithm (GA) optimization on thermosonicated achocha juice: kinetic and thermodynamic perspectives of retained phytocompounds.

Preparative biochemistry & biotechnology
The extraction of phytocompounds from Achocha () vegetable juice using traditional methods often results in suboptimal yields and efficiency. This study aimed to enhance the extraction process through the application of thermosonication (TS). To achi...

Machine Learning Derived Collective Variables for the Study of Protein Homodimerization in Membrane.

Journal of chemical theory and computation
The accurate calculation of equilibrium constants for protein-protein association is of fundamental importance to quantitative biology and remains an outstanding challenge for computational biophysics. Traditionally, equilibrium constants have been c...

Predicting thermodynamic adhesion energies of membrane fouling in planktonic anammox MBR via backpropagation neural network model.

Bioresource technology
Predicting thermodynamic adhesion energies was a critical strategy for mitigating membrane fouling. This study utilized a backpropagation (BP) neural network model to predict the thermodynamic adhesion energies associated with membrane fouling in a p...

Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters.

Journal of chemical theory and computation
Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range potential is also an important component of the range-separated machine learning force field. This st...

Electronic and Nuclear Quantum Effects on Proton Transfer Reactions of Guanine-Thymine (G-T) Mispairs Using Combined Quantum Mechanical/Molecular Mechanical and Machine Learning Potentials.

Molecules (Basel, Switzerland)
Rare tautomeric forms of nucleobases can lead to Watson-Crick-like (WC-like) mispairs in DNA, but the process of proton transfer is fast and difficult to detect experimentally. NMR studies show evidence for the existence of short-time WC-like guanine...

Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.

Molecules (Basel, Switzerland)
CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (...

Adsorptive removal of perfluorooctanoic acid from aqueous matrices using peanut husk-derived magnetic biochar: Statistical and artificial intelligence approaches, kinetics, isotherm, and thermodynamics.

Chemosphere
Removal of perfluorooctanoic acid (PFOA) from water matrices is crucial owing to its pervasiveness and adverse ecological and human health effects. This study investigates the adsorptive removal of PFOA using magnetic biochar (MBC) derived from FeCl-...

Artificial neural network-based modeling of Malachite green adsorption onto baru fruit endocarp: insights into equilibrium, kinetic, and thermodynamic behavior.

International journal of phytoremediation
In this study, artificial neural network (ANN) tools were employed to forecast the adsorption capacity of Malachite green (MG) by baru fruit endocarp waste (B@FE) under diverse conditions, including pH, adsorbent dosage, initial dye concentration, co...

ProBAN: Neural network algorithm for predicting binding affinity in protein-protein complexes.

Proteins
Determining binding affinities in protein-protein and protein-peptide complexes is a challenging task that directly impacts the development of peptide and protein pharmaceuticals. Although several models have been proposed to predict the value of the...

Data-driven, explainable machine learning model for predicting volatile organic compounds' standard vaporization enthalpy.

Chemosphere
The accurate prediction of standard vaporization enthalpy (ΔH°) for volatile organic compounds (VOCs) is of paramount importance in environmental chemistry, industrial applications and regulatory compliance. To overcome traditional experimental metho...