AIMC Topic: Protein Folding

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A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence.

ACS nano Jun 26, 2019
We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural network, and then apply it to generate protein designs using artificial intelligence (AI). The soni...
Artificial Intelligence Proteins Models, Molecular Humans Sound Protein Conformation Protein Folding Mutation Amino Acid Sequence
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Prediction of zinc-binding sites using multiple sequence profiles and machine learning methods.

Molecular omics May 2, 2019
The zinc (Zn) cofactor has been proven to be involved in numerous biological mechanisms and the zinc-binding site is recognized as one of the most important post-translation modifications in proteins. Therefore, accurate knowledge of zinc ions in pro...
Machine Learning Software Protein Folding Support Vector Machine Databases, Protein Protein Conformation Zinc Binding Sites Protein Binding Amino Acid Sequence Computational Biology Algorithms Computer Simulation
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In silico minimalist approach to study 2D HP protein folding into an inhomogeneous space mimicking osmolyte effect: First trial in the search of foldameric backbones.

Bio Systems Apr 25, 2019
We have employed our bioinformatics workbench, named Evolution, a Multi-Agent System based architecture with lattice-bead-models, evolutionary-algorithms, and correlated-networks as inhomogeneous spaces, with different correlation lengths, mimicking ...
Protein Folding Models, Molecular Hydrophobic and Hydrophilic Interactions Neural Networks, Computer Computer Simulation
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End-to-End Differentiable Learning of Protein Structure.

Cell systems Apr 17, 2019
Predicting protein structure from sequence is a central challenge of biochemistry. Co-evolution methods show promise, but an explicit sequence-to-structure map remains elusive. Advances in deep learning that replace complex, human-designed pipelines ...
Machine Learning Software Sequence Analysis, Protein Evolution, Molecular Protein Folding
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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...
Molecular Dynamics Simulation Amino Acid Sequence Protein Folding Sequence Analysis, Protein Protein Conformation Algorithms Deep Learning Neural Networks, Computer Software
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Sequentially distant but structurally similar proteins exhibit fold specific patterns based on their biophysical properties.

Computational biology and chemistry May 16, 2018
The Three-dimensional structure of a protein depends on the interaction between their amino acid residues. These interactions are in turn influenced by various biophysical properties of the amino acids. There are several examples of proteins that sha...
Proteins Models, Molecular Protein Conformation Protein Folding Bayes Theorem Support Vector Machine
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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, ...
Protein Conformation Single Molecule Imaging Protein Folding Molecular Dynamics Simulation Fluorescence Resonance Energy Transfer Machine Learning Carrier Proteins
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SPIN2: Predicting sequence profiles from protein structures using deep neural networks.

Proteins Mar 25, 2018
Designing protein sequences that can fold into a given structure is a well-known inverse protein-folding problem. One important characteristic to attain for a protein design program is the ability to recover wild-type sequences given their native bac...
Protein Structure, Secondary Protein Folding Models, Molecular Amino Acid Sequence Proteins Databases, Protein Neural Networks, Computer Software
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Automated Planning Enables Complex Protocols on Liquid-Handling Robots.

ACS synthetic biology Mar 5, 2018
Robotic automation in synthetic biology is especially relevant for liquid handling to facilitate complex experiments. However, research tasks that are not highly standardized are still rarely automated in practice. Two main reasons for this are the s...
Hydrogen-Ion Concentration Osmolar Concentration Robotics Protein Folding Mutant Proteins Automation Green Fluorescent Proteins
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VAMPnets for deep learning of molecular kinetics.

Nature communications Jan 2, 2018
There is an increasing demand for computing the relevant structures, equilibria, and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations. Current methods employ transfor...
Algorithms Protein Binding Kinetics Neural Networks, Computer Protein Folding Molecular Dynamics Simulation Machine Learning Markov Chains
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