AIMC Topic: Molecular Dynamics Simulation

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Modern drug design: the implication of using artificial neuronal networks and multiple molecular dynamic simulations.

Journal of computer-aided molecular design Nov 13, 2017
We report the implementation of molecular modeling approaches developed as a part of the 2016 Grand Challenge 2, the blinded competition of computer aided drug design technologies held by the D3R Drug Design Data Resource ( https://drugdesigndata.org...
Molecular Docking Simulation Computer-Aided Design Drug Design Neural Networks, Computer Machine Learning Protein Conformation Humans Protein Binding Receptors, Cytoplasmic and Nuclear Molecular Dynamics Simulation Binding Sites Ligands
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Simultaneous refinement of inaccurate local regions and overall structure in the CASP12 protein model refinement experiment.

Proteins Oct 26, 2017
Advances in protein model refinement techniques are required as diverse sources of protein structure information are available from low-resolution experiments or informatics-based computations such as cryo-EM, NMR, homology models, or predicted resid...
Computational Biology Proteins Models, Molecular Machine Learning Algorithms Sequence Analysis, Protein Protein Interaction Domains and Motifs Molecular Dynamics Simulation Crystallography, X-Ray Protein Conformation Humans
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The Thermodynamic Basis of the Fuzzy Interaction of an Intrinsically Disordered Protein.

Angewandte Chemie (International ed. in English) Oct 10, 2017
Many intrinsically disordered proteins (IDP) that fold upon binding retain conformational heterogeneity in IDP-target complexes. The thermodynamics of such fuzzy interactions is poorly understood. Herein we introduce a thermodynamic framework, based ...
Protein Binding Intrinsically Disordered Proteins Thermodynamics Protein Folding Calorimetry Fuzzy Logic Kinetics Circular Dichroism Models, Molecular Molecular Dynamics Simulation Amino Acid Sequence
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TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions.

PLoS computational biology Jul 27, 2017
UNLABELLED: Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered...
Computational Biology Membrane Proteins Models, Statistical Molecular Dynamics Simulation Protein Folding Machine Learning Image Processing, Computer-Assisted Protein Binding Neural Networks, Computer
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Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase.

Scientific reports Jun 16, 2017
The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are impo...
Protein Interaction Domains and Motifs Protein Interaction Maps Oxidation-Reduction Molecular Dynamics Simulation Humans Protein Conformation Machine Learning Protein Interaction Mapping Protein Disulfide-Isomerases
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Neural Network and Nearest Neighbor Algorithms for Enhancing Sampling of Molecular Dynamics.

Journal of chemical theory and computation May 4, 2017
The free energy calculations of complex chemical and biological systems with molecular dynamics (MD) are inefficient due to multiple local minima separated by high-energy barriers. The minima can be escaped using an enhanced sampling method such as m...
Thermodynamics Neural Networks, Computer Molecular Dynamics Simulation
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Princeton_TIGRESS 2.0: High refinement consistency and net gains through support vector machines and molecular dynamics in double-blind predictions during the CASP11 experiment.

Proteins Mar 21, 2017
Protein structure refinement is the challenging problem of operating on any protein structure prediction to improve its accuracy with respect to the native structure in a blind fashion. Although many approaches have been developed and tested during t...
Double-Blind Method Internet Benchmarking Molecular Dynamics Simulation Protein Conformation Monte Carlo Method Support Vector Machine Models, Statistical Software Proteins Computational Biology
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Neural-Network-Biased Genetic Algorithms for Materials Design: Evolutionary Algorithms That Learn.

ACS combinatorial science Jan 9, 2017
Machine learning has the potential to dramatically accelerate high-throughput approaches to materials design, as demonstrated by successes in biomolecular design and hard materials design. However, in the search for new soft materials exhibiting prop...
Algorithms Humans Polymers Neural Networks, Computer Molecular Dynamics Simulation Machine Learning
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Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics.

Journal of chemical information and modeling May 20, 2016
One of the unaddressed challenges in drug discovery is that drug potency determined in vitro is not a reliable indicator of drug activity in vivo. Accumulated evidence suggests that in vivo activity is more strongly correlated with the binding/unbind...
Molecular Dynamics Simulation Protein Binding Machine Learning Protein Conformation Static Electricity Drug Discovery Computational Biology Safety Kinetics Thermodynamics Ligands
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Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles.

Journal of chemical information and modeling May 3, 2016
Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates ac...
Molecular Dynamics Simulation Drug Evaluation, Preclinical Protein Conformation Machine Learning User-Computer Interface
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