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Photoluminescence-tunable fluorescent carbon dots-deposited silver nanoparticle for detection and killing of bacteria.

Materials science & engineering. C, Materials for biological applications 30678948
Innovative methods to detect and kill pathogenic bacteria have a pivotal role in the eradication of infectious diseases and the prevention of the growth of antibiotic-resistant bacteria. The combination of fluorescent carbon dots (FCDs) with silver n...
Animals Biocompatible Materials Carbon Catechols Cell Survival Dogs Escherichia coli Fluorescence Resonance Energy Transfer Madin Darby Canine Kidney Cells Metal Nanoparticles Microscopy, Confocal Particle Size Povidone Quantum Dots Silver Staphylococcus aureus Static Electricity Water Purification
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Comparison of response surface methodology and artificial neural network to optimize novel ophthalmic flexible nano-liposomes: Characterization, evaluation, in vivo pharmacokinetics and molecular dynamics simulation.

Colloids and surfaces. B, Biointerfaces 30173096
To improve the topical delivery of pilocarpine hydrochloride (PN) to treat glaucoma, flexible nano-liposomes containing PN (PN-FLs) were prepared, optimized and characterized. Artificial neural network (ANN) and response surface methodology (RSM) wer...
Animals Drug Liberation Irritants Liposomes Molecular Dynamics Simulation Nanoparticles Neural Networks, Computer Ophthalmic Solutions Particle Size Pilocarpine Rabbits Spectroscopy, Fourier Transform Infrared Static Electricity Thermodynamics
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Toward Building Protein Force Fields by Residue-Based Systematic Molecular Fragmentation and Neural Network.

Journal of chemical theory and computation 30550274
Accurate force fields are crucial for molecular dynamics investigation of complex biological systems. Building accurate protein force fields from quantum mechanical (QM) calculations is challenging due to the complexity of proteins and high computati...
Amino Acids Dipeptides Models, Chemical Molecular Dynamics Simulation Neural Networks, Computer Peptides Proteins Quantum Theory Static Electricity Thermodynamics
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PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges.

Journal of chemical theory and computation 31042390
In recent years, machine learning (ML) methods have become increasingly popular in computational chemistry. After being trained on appropriate ab initio reference data, these methods allow for accurately predicting the properties of chemical systems,...
Algorithms Molecular Dynamics Simulation Neural Networks, Computer Protein Conformation Proteins Quantum Theory Static Electricity Thermodynamics
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Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins.

Neural computation 31260391
A restricted Boltzmann machine (RBM) is an unsupervised machine learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relevant statistical features. RBMs were recently proposed for characterizi...
Amino Acid Sequence Computer Simulation Models, Molecular Models, Statistical Principal Component Analysis Probability Proteins Sequence Alignment Static Electricity Stochastic Processes Unsupervised Machine Learning
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Practical High-Quality Electrostatic Potential Surfaces for Drug Discovery Using a Graph-Convolutional Deep Neural Network.

Journal of medicinal chemistry 31553186
Inspecting protein and ligand electrostatic potential (ESP) surfaces in order to optimize electrostatic complementarity is a key activity in drug design. These ESP surfaces need to reflect the true electrostatic nature of the molecules, which typical...
Datasets as Topic Deep Learning Drug Discovery Factor Xa Hydrogen Bonding Ligands Organic Chemicals Protein Binding Quantum Theory Static Electricity X-Linked Inhibitor of Apoptosis Protein
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A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection.

Interdisciplinary sciences, computational life sciences 31486019
BACKGROUND: Computational prediction of inhibition efficiency (IE) for inhibitor molecules is a crucial supplementary way to design novel molecules that can efficiently inhibit corrosion onto metallic surfaces.
Algorithms Benzimidazoles Chemistry Cluster Analysis Computational Biology Conservation of Natural Resources Corrosion Hydrazines Imaging, Three-Dimensional Linear Models Machine Learning Metals Predictive Value of Tests Quantitative Structure-Activity Relationship Static Electricity Support Vector Machine
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Steroid identification via deep learning retention time predictions and two-dimensional gas chromatography-high resolution mass spectrometry.

Journal of chromatography. A 31708215
Untargeted steroid identification represents a great analytical challenge even when using sophisticated technology such as two-dimensional gas chromatography coupled to high resolution mass spectrometry (GC × GCHRMS) due to the chemical similarity of...
Deep Learning Gas Chromatography-Mass Spectrometry Least-Squares Analysis Neural Networks, Computer Static Electricity Steroids Support Vector Machine
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Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease.

Journal of chemical theory and computation 31877249
Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few clo...
Drug Resistance, Viral HIV Protease HIV Protease Inhibitors HIV-1 Humans Hydrogen Bonding Ligands Machine Learning Molecular Dynamics Simulation Monte Carlo Method Mutation Protein Binding Static Electricity
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Generalized Born radii computation using linear models and neural networks.

Bioinformatics (Oxford, England) 31693089
MOTIVATION: Implicit solvent models play an important role in describing the thermodynamics and the dynamics of biomolecular systems. Key to an efficient use of these models is the computation of generalized Born (GB) radii, which is accomplished by ...
Linear Models Neural Networks, Computer Solvents Static Electricity Thermodynamics
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