AIMC Topic: Thermodynamics

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

International journal of phytoremediation May 17, 2024
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...
Fruit Thermodynamics Rosaniline Dyes Hydrogen-Ion Concentration Biodegradation, Environmental Ulva Adsorption Kinetics Neural Networks, Computer Water Pollutants, Chemical
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ProBAN: Neural network algorithm for predicting binding affinity in protein-protein complexes.

Proteins May 9, 2024
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...
Neural Networks, Computer Algorithms Proteins Databases, Protein Binding Sites Protein Binding Computational Biology Thermodynamics Protein Interaction Mapping
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Data-driven, explainable machine learning model for predicting volatile organic compounds' standard vaporization enthalpy.

Chemosphere May 6, 2024
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...
Volatile Organic Compounds Thermodynamics Machine Learning Algorithms Volatilization Models, Chemical
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Carbon-based molecular properties efficiently predicted by deep learning-based quantum chemical simulation with large language models.

Computers in biology and medicine May 1, 2024
The prediction of thermodynamic properties of carbon-based molecules based on their geometrical conformation using fluctuation and density functional theories has achieved great success in the field of energy chemistry, while the excessive computatio...
Thermodynamics Models, Chemical Quantum Theory Deep Learning Carbon
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Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation.

International journal of biological macromolecules Apr 30, 2024
GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibi...
Chronic Disease Molecular Dynamics Simulation Ligands Molecular Docking Simulation Protein Binding Thermodynamics Pharmacophore G-Protein-Coupled Receptor Kinase 5 Protein Kinase Inhibitors Binding Sites Quantitative Structure-Activity Relationship Humans Machine Learning
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Exploring Antiviral Drugs on Monolayer Black Phosphorene: Atomistic Theory and Explainable Machine Learning-Assisted Platform.

International journal of molecular sciences Apr 30, 2024
Favipiravir (FP) and ebselen (EB) belong to a diverse class of antiviral drugs known for their significant efficacy in treating various viral infections. Utilizing molecular dynamics (MD) simulations, machine learning, and van der Waals density funct...
Density Functional Theory Machine Learning Azoles Antiviral Agents Molecular Dynamics Simulation Thermodynamics Isoindoles Organoselenium Compounds
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology.

Journal of chemical information and modeling Apr 23, 2024
In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. In recent years, two computational techniques, machin...
Machine Learning Algorithms Humans Drug Discovery Thermodynamics
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DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.

Journal of chemical information and modeling Apr 22, 2024
It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary ...
Base Sequence Nucleic Acid Conformation RNA Deep Learning Computational Biology Thermodynamics Models, Molecular
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Differentiating stable and unstable protein using convolution neural network and molecular dynamics simulations.

Computational biology and chemistry Apr 20, 2024
Protein stability is a critical aspect of molecular biology and biochemistry, hinges on an intricate balance of thermodynamic and structural factors. Determining protein stability is crucial for understanding and manipulating biological machineries, ...
Protein Stability Thermodynamics Proteins Molecular Dynamics Simulation Neural Networks, Computer Machine Learning
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Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.

Molecules (Basel, Switzerland) Apr 19, 2024
Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calcula...
Azepines Bromodomain Containing Proteins Humans Protein Binding Cell Cycle Proteins Nuclear Proteins Molecular Dynamics Simulation Binding Sites Transcription Factors Molecular Docking Simulation Triazoles Thermodynamics Deep Learning
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