AIMC Topic: Proteins

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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...
Databases, Protein Protein Conformation Deep Learning Proteins
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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...
Deep Learning Computational Biology Humans Software Neural Networks, Computer Crystallography, X-Ray Algorithms Proteins Protein Conformation Models, Molecular Protein Folding
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EPuL: An Enhanced Positive-Unlabeled Learning Algorithm for the Prediction of Pupylation Sites.

Molecules (Basel, Switzerland) Sep 5, 2017
Protein pupylation is a type of post-translation modification, which plays a crucial role in cellular function of bacterial organisms in prokaryotes. To have a better insight of the mechanisms underlying pupylation an initial, but important, step is ...
Protein Processing, Post-Translational Machine Learning Proteins Protein Binding Software Databases, Protein Computational Biology Algorithms
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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...
Models, Molecular Arachidonate 15-Lipoxygenase Motion Elasticity Protein Conformation Animals Proteins Humans Machine Learning
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Integration of element specific persistent homology and machine learning for protein-ligand binding affinity prediction.

International journal for numerical methods in biomedical engineering Aug 16, 2017
Protein-ligand binding is a fundamental biological process that is paramount to many other biological processes, such as signal transduction, metabolic pathways, enzyme construction, cell secretion, and gene expression. Accurate prediction of protein...
Ligands Hydrogen Bonding Proteins Databases, Protein Machine Learning Protein Binding
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Root cause investigation of deviations in protein chromatography based on mechanistic models and artificial neural networks.

Journal of chromatography. A Aug 1, 2017
In protein chromatography, process variations, such as aging of column or process errors, can result in deviations of the product and impurity levels. Consequently, the process performance described by purity, yield, or production rate may decrease. ...
Chromatography, Liquid Proteins Neural Networks, Computer Models, Theoretical
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Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening.

Journal of chemical information and modeling Jul 12, 2017
In structure-based virtual screening, compound ranking through a consensus of scores from a variety of docking programs or scoring functions, rather than ranking by scores from a single program, provides better predictive performance and reduces targ...
Drug Evaluation, Preclinical Molecular Targeted Therapy Machine Learning Molecular Docking Simulation Proteins Benchmarking User-Computer Interface
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MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.

Computational intelligence and neuroscience Jul 4, 2017
Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction...
Computational Biology Apoptosis Algorithms Gene Ontology Proteins Intracellular Space Protein Transport
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NewGOA: Predicting New GO Annotations of Proteins by Bi-Random Walks on a Hybrid Graph.

IEEE/ACM transactions on computational biology and bioinformatics Jun 15, 2017
A remaining key challenge of modern biology is annotating the functional roles of proteins. Various computational models have been proposed for this challenge. Most of them assume the annotations of annotated proteins are complete. But in fact, many ...
Humans Computational Biology Proteins Protein Interaction Maps Protein Interaction Mapping Molecular Sequence Annotation Saccharomyces cerevisiae Proteins Gene Ontology
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Machine learning based identification of protein-protein interactions using derived features of physiochemical properties and evolutionary profiles.

Artificial intelligence in medicine Jun 13, 2017
Proteins are the central constitute of a cell or biological system. Proteins execute their functions by interacting with other molecules such as RNA, DNA and other proteins. The major functionality of protein-protein interactions (PPIs) is the execut...
Protein Interaction Mapping Support Vector Machine Proteins Algorithms Computational Biology Machine Learning
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