AIMC Topic: Molecular Dynamics Simulation

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Predicting Thermodynamic Properties of Alkanes by High-Throughput Force Field Simulation and Machine Learning.

Journal of chemical information and modeling Sep 26, 2018
Knowledge of the thermodynamic properties of molecules is essential for chemical process design and the development of new materials. Experimental measurements are often expensive and not environmentally friendly. In the past, studies using molecular...
Neural Networks, Computer Machine Learning Temperature High-Throughput Screening Assays Models, Chemical Thermodynamics Alkanes Molecular Dynamics Simulation
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Predicting improved protein conformations with a temporal deep recurrent neural network.

PloS one Sep 4, 2018
Accurate protein structure prediction from amino acid sequence is still an unsolved problem. The most reliable methods centre on template based modelling. However, the accuracy of these models entirely depends on the availability of experimentally re...
Amino Acid Sequence Neural Networks, Computer Protein Conformation Algorithms Software Protein Folding Deep Learning Molecular Dynamics Simulation Sequence Analysis, Protein
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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 Aug 23, 2018
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...
Neural Networks, Computer Animals Nanoparticles Ophthalmic Solutions Molecular Dynamics Simulation Rabbits Spectroscopy, Fourier Transform Infrared Particle Size Pilocarpine Static Electricity Thermodynamics Drug Liberation Irritants Liposomes
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Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks.

Journal of chemical theory and computation Aug 17, 2018
The ability to accurately and efficiently compute quantum-mechanical partial atomistic charges has many practical applications, such as calculations of IR spectra, analysis of chemical bonding, and classical force field parametrization. Machine learn...
Molecular Dynamics Simulation Spectrophotometry, Infrared Neural Networks, Computer Models, Chemical Methanol Proteins
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Linking of single-molecule experiments with molecular dynamics simulations by machine learning.

eLife May 3, 2018
Single-molecule experiments and molecular dynamics (MD) simulations are indispensable tools for investigating protein conformational dynamics. The former provide data, such as donor-acceptor distances, whereas the latter give atomistic information, ...
Single Molecule Imaging Protein Folding Machine Learning Carrier Proteins Fluorescence Resonance Energy Transfer Protein Conformation Molecular Dynamics Simulation
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TopP-S: Persistent homology-based multi-task deep neural networks for simultaneous predictions of partition coefficient and aqueous solubility.

Journal of computational chemistry Apr 6, 2018
Aqueous solubility and partition coefficient are important physical properties of small molecules. Accurate theoretical prediction of aqueous solubility and partition coefficient plays an important role in drug design and discovery. The prediction ac...
Water Molecular Dynamics Simulation Solubility Neural Networks, Computer Software Algorithms
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Recognition of protein allosteric states and residues: Machine learning approaches.

Journal of computational chemistry Mar 31, 2018
Allostery is a process by which proteins transmit the effect of perturbation at one site to a distal functional site upon certain perturbation. As an intrinsically global effect of protein dynamics, it is difficult to associate protein allostery with...
Proteins Molecular Dynamics Simulation Neural Networks, Computer Allosteric Site Machine Learning
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Machine Learning of Partial Charges Derived from High-Quality Quantum-Mechanical Calculations.

Journal of chemical information and modeling Mar 7, 2018
Parametrization of small organic molecules for classical molecular dynamics simulations is not trivial. The vastness of the chemical space makes approaches using building blocks challenging. The most common approach is therefore an individual paramet...
Electrons Pharmaceutical Preparations Volatilization Thermodynamics Molecular Dynamics Simulation Static Electricity Machine Learning Quantum Theory Models, Chemical
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Probing light chain mutation effects on thrombin via molecular dynamics simulations and machine learning.

Journal of biomolecular structure & dynamics Mar 2, 2018
Thrombin is a key component for chemotherapeutic and antithrombotic therapy development. As the physiologic and pathologic roles of the light chain still remain vague, here, we continue previous efforts to understand the impacts of the disease-associ...
Sodium Protein Conformation Thrombin Allosteric Regulation Hydrogen Bonding Protein Binding Humans Mutation Machine Learning Molecular Dynamics Simulation
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Simulations meet machine learning in structural biology.

Current opinion in structural biology Feb 21, 2018
Classical molecular dynamics (MD) simulations will be able to reach sampling in the second timescale within five years, producing petabytes of simulation data at current force field accuracy. Notwithstanding this, MD will still be in the regime of lo...
Models, Molecular Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Computer Simulation Machine Learning Computational Biology
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