AIMC Topic: Hydrogen Bonding

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Graphene oxide as a nanocarrier for controlled release and targeted delivery of an anticancer active agent, chlorogenic acid.

Materials science & engineering. C, Materials for biological applications Dec 5, 2016
We have synthesized graphene oxide using improved Hummer's method in order to explore the potential use of the resulting graphene oxide as a nanocarrier for an active anticancer agent, chlorogenic acid (CA). The synthesized graphene oxide and chlorog...
Graphite Chlorogenic Acid X-Ray Diffraction Drug Liberation Cell Survival HeLa Cells A549 Cells Spectrum Analysis, Raman Hydrogen-Ion Concentration Spectroscopy, Fourier Transform Infrared Nanocomposites Hep G2 Cells Oxides Microscopy, Electron, Transmission Humans Antineoplastic Agents Delayed-Action Preparations Thermogravimetry Hydrogen Bonding
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Characterizing informative sequence descriptors and predicting binding affinities of heterodimeric protein complexes.

BMC bioinformatics Dec 9, 2015
BACKGROUND: Protein-protein interactions (PPIs) are involved in various biological processes, and underlying mechanism of the interactions plays a crucial role in therapeutics and protein engineering. Most machine learning approaches have been develo...
Area Under Curve Hydrogen Bonding Dimerization Protein Structure, Tertiary Support Vector Machine Proteins Principal Component Analysis Protein Interaction Maps Protein Binding ROC Curve
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A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction.

BioMed research international Oct 4, 2015
Blood-brain barrier (BBB) is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM) is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM ...
Humans Hydrogen-Ion Concentration Permeability Models, Biological Hydrogen Bonding Biological Transport, Active Quantitative Structure-Activity Relationship Blood-Brain Barrier Algorithms Drug Design Databases, Factual Support Vector Machine
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Representing the potential-energy surface of protonated water clusters by high-dimensional neural network potentials.

Physical chemistry chemical physics : PCCP Dec 1, 2014
Investigating the properties of protons in water is essential for understanding many chemical processes in aqueous solution. While important insights can in principle be gained by accurate and well-established methods like ab initio molecular dynamic...
Hydrogen Bonding Thermodynamics Protons Water Molecular Dynamics Simulation Neural Networks, Computer
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Accurate Identification of MDMB-Type Synthetic Cannabinoids through Design of Dual Excited-State Intramolecular Proton Transfer Site Probe and Deep-Learning.

Analytical chemistry Jun 10, 2025
Synthetic cannabinoids, a novel class of highly toxic psychoactive substances with various disguised forms, have posed significant risks to public safety, and their weak reactivity presents a substantial challenge for swift and accurate analysis. In ...
Deep Learning Hydrogen Bonding Cannabinoids Protons Spectrometry, Fluorescence Fluorescent Dyes Molecular Structure
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DeepDTAF: a deep learning method to predict protein-ligand binding affinity.

Briefings in bioinformatics Sep 2, 2021
Biomolecular recognition between ligand and protein plays an essential role in drug discovery and development. However, it is extremely time and resource consuming to determine the protein-ligand binding affinity by experiments. At present, many comp...
Protein Binding Binding Sites Proteins Protein Conformation, alpha-Helical Data Accuracy Reproducibility of Results Amino Acid Sequence Models, Molecular Hydrogen Bonding Drug Discovery Ligands Software Deep Learning
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A computational method for design of connected catalytic networks in proteins.

Protein science : a publication of the Protein Society Dec 1, 2019
Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and surrounding side-chain functional groups which maximize transition-state stabilization, and then sear...
Models, Molecular Biocatalysis Hydrogen Bonding Proteins Databases, Protein Neural Networks, Computer Binding Sites
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Prediction of protein-protein interaction sites from weakly homologous template structures using meta-threading and machine learning.

Journal of molecular recognition : JMR Jan 1, 2015
The identification of protein-protein interactions is vital for understanding protein function, elucidating interaction mechanisms, and for practical applications in drug discovery. With the exponentially growing protein sequence data, fully automate...
Proteins Models, Molecular Binding Sites Hydrogen Bonding Algorithms Protein Binding Evolution, Molecular Machine Learning Software
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