AIMC Topic: Proteins

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Structure and Protein Interaction-Based Gene Ontology Annotations Reveal Likely Functions of Uncharacterized Proteins on Human Chromosome 17.

Journal of proteome research Oct 16, 2018
Understanding the function of human proteins is essential to decipher the molecular mechanisms of human diseases and phenotypes. Of the 17 470 human protein coding genes in the neXtProt 2018-01-17 database with unequivocal protein existence evidence ...
Molecular Sequence Annotation Gene Ontology Chromosomes, Human, Pair 17 Proteins Databases, Protein Humans Proteome
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Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data.

Journal of chemical information and modeling Oct 16, 2018
Machine learning has shown enormous potential for computer-aided drug discovery. Here we show how modern convolutional neural networks (CNNs) can be applied to structure-based virtual screening. We have coupled our densely connected CNN (DenseNet) wi...
Humans Neural Networks, Computer Machine Learning Databases, Protein Ligands Molecular Docking Simulation Databases, Pharmaceutical Computer-Aided Design Drug Discovery Proteins
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Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning.

Journal of computational chemistry Oct 14, 2018
Predicting protein structure from sequence alone is challenging. Thus, the majority of methods for protein structure prediction rely on evolutionary information from multiple sequence alignments. In previous work we showed that Long Short-Term Bidire...
Deep Learning Proteins Solvents Protein Structure, Secondary
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TopScore: Using Deep Neural Networks and Large Diverse Data Sets for Accurate Protein Model Quality Assessment.

Journal of chemical theory and computation Oct 9, 2018
The value of protein models obtained with automated protein structure prediction depends primarily on their accuracy. Protein model quality assessment is thus critical to select the model that can best answer biologically relevant questions from an e...
Databases, Protein Models, Molecular Protein Conformation Neural Networks, Computer Proteins
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DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning.

Genomics, proteomics & bioinformatics Sep 27, 2018
Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are...
Nitrosation Deep Learning Software Humans Internet Amino Acids Reproducibility of Results Proteins Neural Networks, Computer Amino Acid Sequence
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Deep learning-based transcriptome data classification for drug-target interaction prediction.

BMC genomics Sep 24, 2018
BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded...
Molecular Targeted Therapy Proteins Drug Interactions Computer Simulation Drug Discovery Machine Learning Transcriptome Algorithms Models, Theoretical Humans Gene Expression Profiling Databases, Factual
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Protein function prediction from protein-protein interaction network using gene ontology based neighborhood analysis and physico-chemical features.

Journal of bioinformatics and computational biology Sep 19, 2018
Protein Function Prediction from Protein-Protein Interaction Network (PPIN) and physico-chemical features using the Gene Ontology (GO) classification are indeed very useful for assigning biological or biochemical functions to a protein. They also lea...
Proteins Databases, Protein Saccharomyces cerevisiae Protein Interaction Maps Humans Gene Ontology Computational Biology Saccharomyces cerevisiae Proteins Amino Acid Sequence
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A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites.

International journal of molecular sciences Sep 18, 2018
Protein hydroxylation is one type of post-translational modifications (PTMs) playing critical roles in human diseases. It is known that protein sequence contains many uncharacterized residues of proline and lysine. The question that needs to be answe...
Hydroxylysine Hydroxyproline Hydroxylation Neural Networks, Computer Deep Learning Proteins Models, Biological Protein Processing, Post-Translational Humans
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Detecting Proline and Non-Proline Cis Isomers in Protein Structures from Sequences Using Deep Residual Ensemble Learning.

Journal of chemical information and modeling Aug 29, 2018
It has been long established that cis conformations of amino acid residues play many biologically important roles despite their rare occurrence in protein structure. Because of this rarity, few methods have been developed for predicting cis isomers f...
Proteins Amino Acid Sequence Proline Machine Learning
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Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks.

Journal of chemical theory and computation Aug 17, 2018
The ability to accurately and efficiently compute quantum-mechanical partial atomistic charges has many practical applications, such as calculations of IR spectra, analysis of chemical bonding, and classical force field parametrization. Machine learn...
Spectrophotometry, Infrared Models, Chemical Neural Networks, Computer Methanol Proteins Molecular Dynamics Simulation
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