AIMC Topic: Protein Conformation

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Interaction prediction in structure-based virtual screening using deep learning.

Computers in biology and medicine Sep 14, 2017
We introduce a deep learning architecture for structure-based virtual screening that generates fixed-sized fingerprints of proteins and small molecules by applying learnable atom convolution and softmax operations to each molecule separately. These f...
Protein Conformation Deep Learning Proteins Databases, Protein
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Analysis of deep learning methods for blind protein contact prediction in CASP12.

Proteins Sep 6, 2017
Here we present the results of protein contact prediction achieved in CASP12 by our RaptorX-Contact server, which is an early implementation of our deep learning method for contact prediction. On a set of 38 free-modeling target domains with a median...
Software Algorithms Deep Learning Humans Neural Networks, Computer Crystallography, X-Ray Protein Conformation Protein Folding Computational Biology Proteins Models, Molecular
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Elastic network model of learned maintained contacts to predict protein motion.

PloS one Aug 30, 2017
We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein's contact topology. Existing elastic network models assume that the contact topology r...
Motion Animals Humans Arachidonate 15-Lipoxygenase Elasticity Machine Learning Proteins Protein Conformation Models, Molecular
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In silico identification of milk antihypertensive di- and tripeptides involved in angiotensin I-converting enzyme inhibitory activity.

Nutrition research (New York, N.Y.) Jul 28, 2017
Identification of bioactive milk peptides could improve food technology through improved selection of food supplements with a focus on antihypertensive properties. We hypothesized that angiotensin I-converting enzyme (ACE) inhibitory activities of mi...
Protein Conformation Hydrogen Bonding Peptidyl-Dipeptidase A Oligopeptides Angiotensin-Converting Enzyme Inhibitors Quantitative Structure-Activity Relationship Proteolysis Binding Sites Milk Proteins Models, Molecular Peptide Fragments Dipeptides Hydrophobic and Hydrophilic Interactions Expert Systems Catalytic Domain Computational Biology Dietary Supplements Antihypertensive Agents Animals Molecular Docking Simulation Cattle Humans
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Machine-Learning-Assisted Approach for Discovering Novel Inhibitors Targeting Bromodomain-Containing Protein 4.

Journal of chemical information and modeling Jul 10, 2017
Bromodomain-containing protein 4 (BRD4) is implicated in the pathogenesis of a number of different cancers, inflammatory diseases and heart failure. Much effort has been dedicated toward discovering novel scaffold BRD4 inhibitors (BRD4is) with differ...
Humans Machine Learning Molecular Docking Simulation Molecular Targeted Therapy Protein Conformation Cell Cycle Proteins Cell Line Structure-Activity Relationship Drug Discovery Drug Evaluation, Preclinical Nuclear Proteins Transcription Factors
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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...
Molecular Dynamics Simulation Protein Conformation Protein Interaction Mapping Protein Disulfide-Isomerases Protein Interaction Domains and Motifs Machine Learning Protein Interaction Maps Oxidation-Reduction Humans
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Protein-Protein Interaction Interface Residue Pair Prediction Based on Deep Learning Architecture.

IEEE/ACM transactions on computational biology and bioinformatics May 19, 2017
MOTIVATION: Proteins usually fulfill their biological functions by interacting with other proteins. Although some methods have been developed to predict the binding sites of a monomer protein, these are not sufficient for prediction of the interactio...
Molecular Docking Simulation Deep Learning Protein Binding Computational Biology Protein Conformation Proteins Binding Sites Surface Properties
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A novel model-based on FCM-LM algorithm for prediction of protein folding rate.

Journal of bioinformatics and computational biology Apr 25, 2017
The prediction of protein folding rates is of paramount importance in describing the protein folding mechanism, which has broad applications in fields such as enzyme engineering and protein engineering. Therefore, predicting protein folding rates usi...
Protein Conformation Protein Folding Algorithms Computational Biology Proteins Humans Neural Networks, Computer
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Hidden Markov model and Chapman Kolmogrov for protein structures prediction from images.

Computational biology and chemistry Apr 13, 2017
Protein structure prediction and analysis are more significant for living organs to perfect asses the living organ functionalities. Several protein structure prediction methods use neural network (NN). However, the Hidden Markov model is more interpr...
Neural Networks, Computer Protein Conformation Algorithms Proteins Markov Chains
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Protein-Ligand Scoring with Convolutional Neural Networks.

Journal of chemical information and modeling Apr 11, 2017
Computational approaches to drug discovery can reduce the time and cost associated with experimental assays and enable the screening of novel chemotypes. Structure-based drug design methods rely on scoring functions to rank and predict binding affini...
Neural Networks, Computer Drug Evaluation, Preclinical Computational Biology User-Computer Interface Ligands Proteins Protein Conformation Models, Molecular
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