AIMC Topic: Thermodynamics

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Toward Achieving Efficient and Accurate Ligand-Protein Unbinding with Deep Learning and Molecular Dynamics through RAVE.

Journal of chemical theory and computation Dec 24, 2018
In this work, we demonstrate how to leverage our recent iterative deep learning-all atom molecular dynamics (MD) technique "Reweighted autoencoded variational Bayes for enhanced sampling (RAVE)" (Ribeiro, Bravo, Wang, Tiwary, J. Chem. Phys. 2018, 149...
Thermodynamics Deep Learning Molecular Dynamics Simulation Ligands Protein Binding Proteins
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Combined molecular dynamics and neural network method for predicting protein antifreeze activity.

Proceedings of the National Academy of Sciences of the United States of America Dec 7, 2018
Antifreeze proteins (AFPs) are a diverse class of proteins that depress the kinetically observable freezing point of water. AFPs have been of scientific interest for decades, but the lack of an accurate model for predicting AFP activity has hindered ...
Neural Networks, Computer Temperature Animals Water Humans Crystallization Thermodynamics Freezing Antifreeze Proteins Models, Theoretical Protein Conformation Kinetics Molecular Dynamics Simulation
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iSEE: Interface structure, evolution, and energy-based machine learning predictor of binding affinity changes upon mutations.

Proteins Dec 3, 2018
Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineering and drug design. Machine learning-based methods are gaining increasing momentum in this field. Due to the limited number of experimental data, using...
Computational Biology Evolution, Molecular Proteins Machine Learning Protein Binding Tumor Suppressor Protein p53 Models, Molecular Binding, Competitive Thermodynamics Mutation Proto-Oncogene Proteins c-mdm2 Protein Domains
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Is Machine Translation a Reliable Tool for Reading German Scientific Databases and Research Articles?

Journal of chemical information and modeling Oct 25, 2018
A significant number of published databases and research papers exist in foreign languages and remain untranslated to date. Important sources of primary scientific information in German are Beilstein Handbuch der Organischen Chemie, Gmelin Handbuch d...
Chemistry Research Language Publishing Translating Physics Thermodynamics Humans Reading Artificial Intelligence Databases, Factual
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Thermodynamic integration network approach to ion transport through protein channels: Perspectives and limits.

Journal of computational chemistry Oct 11, 2018
We present a molecular dynamics simulation study of alkali metal cation transport through the double-helical and the head-to-head conformers of the gramicidin ion channel. Our approach is based on a thermodynamic integration network, which consists o...
Least-Squares Analysis Molecular Dynamics Simulation Protein Conformation Neural Networks, Computer Ion Transport Thermodynamics Ion Channels
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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...
High-Throughput Screening Assays Thermodynamics Alkanes Neural Networks, Computer Machine Learning Models, Chemical Temperature Molecular Dynamics Simulation
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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...
Pilocarpine Static Electricity Thermodynamics Irritants Rabbits Drug Liberation Spectroscopy, Fourier Transform Infrared Liposomes Particle Size Neural Networks, Computer Ophthalmic Solutions Animals Molecular Dynamics Simulation Nanoparticles
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Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges.

Journal of computer-aided molecular design Aug 16, 2018
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affin...
Molecular Docking Simulation Computer-Aided Design Protein Binding Databases, Protein Drug Design Deep Learning Thermodynamics Protein Conformation Cathepsins Protein Kinases Receptors, Cytoplasmic and Nuclear Ligands Binding Sites Crystallography, X-Ray
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A new mechanical approach to handle generalized Hopfield neural networks.

Neural networks : the official journal of the International Neural Network Society Jul 21, 2018
We propose a modification of the cost function of the Hopfield model whose salient features shine in its Taylor expansion and result in more than pairwise interactions with alternate signs, suggesting a unified framework for handling both with deep l...
Monte Carlo Method Neural Networks, Computer Thermodynamics Algorithms Models, Statistical
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miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts.

PLoS computational biology Jul 13, 2018
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to partially complementary regions within the 3'UTR of their target genes. Computational methods play an important role in target prediction and assume that the miR...
Thermodynamics Gene Targeting 3' Untranslated Regions Datasets as Topic Gene Expression Regulation Binding Sites Neural Networks, Computer Deep Learning Computer Simulation RNA, Messenger Reproducibility of Results MicroRNAs Humans
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