AIMC Topic: Protein Structure, Tertiary

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APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction.

Computational biology and chemistry Sep 5, 2015
Tertiary protein structure prediction is one of the most challenging problems in structural bioinformatics. Despite the advances in algorithm development and computational strategies, predicting the folded structure of a protein only from its amino a...
Algorithms Computational Biology Proteins Knowledge Bases Protein Conformation Protein Structure, Tertiary
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SPECTRUS: A Dimensionality Reduction Approach for Identifying Dynamical Domains in Protein Complexes from Limited Structural Datasets.

Structure (London, England : 1993) Jul 9, 2015
Identifying dynamical, quasi-rigid domains in proteins provides a powerful means for characterizing functionally oriented structural changes via a parsimonious set of degrees of freedom. In fact, the relative displacements of few dynamical domains us...
Software Escherichia coli Models, Molecular Internet Adenylate Kinase Tobacco mosaic satellite virus Capsid Multifactor Dimensionality Reduction Ion Channels Thermodynamics Protein Structure, Tertiary
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Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.

Cell reports Jul 2, 2015
Alternative splicing acts on transcripts from almost all human multi-exon genes. Notwithstanding its ubiquity, fundamental ramifications of splicing on protein expression remain unresolved. The number and identity of spliced transcripts that form sta...
Protein Structure, Tertiary Exons Alternative Splicing Supervised Machine Learning Protein Isoforms Humans ROC Curve Proteins Area Under Curve
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All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences.

Proceedings of the National Academy of Sciences of the United States of America Apr 9, 2015
Transmembrane β-barrels (TMBs) carry out major functions in substrate transport and protein biogenesis but experimental determination of their 3D structure is challenging. Encouraged by successful de novo 3D structure prediction of globular and α-hel...
Protein Structure, Tertiary Sequence Analysis, Protein Escherichia coli Proteins Protein Structure, Secondary Artificial Intelligence Receptors, Cell Surface Escherichia coli Models, Molecular
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Prediction of cancer proteins by integrating protein interaction, domain frequency, and domain interaction data using machine learning algorithms.

BioMed research international Mar 17, 2015
Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of...
Databases, Protein Neoplasm Proteins Protein Structure, Tertiary Sequence Analysis, Protein Humans Algorithms Machine Learning Animals Neoplasms
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Using support vector machines to identify protein phosphorylation sites in viruses.

Journal of molecular graphics & modelling Dec 24, 2014
Phosphorylation of viral proteins plays important roles in enhancing replication and inhibition of normal host-cell functions. Given its importance in biology, a unique opportunity has arisen to identify viral protein phosphorylation sites. However, ...
Phosphoproteins Amino Acid Sequence Tyrosine Databases, Protein Phosphorylation Protein Structure, Tertiary Threonine Support Vector Machine Viral Proteins Serine Molecular Sequence Data
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Illuminating the "Twilight Zone": Advances in Difficult Protein Modeling.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2023
Homology modeling was long considered a method of choice in tertiary protein structure prediction. However, it used to provide models of acceptable quality only when templates with appreciable sequence identity with a target could be found. The thres...
Machine Learning Computational Biology Protein Folding Protein Structure, Tertiary Sequence Analysis, Protein Proteins Databases, Protein Protein Conformation
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ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features.

Briefings in bioinformatics Jan 17, 2022
MOTIVATION: The Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. As of CASP14, there are 79 global QA methods, and a minority of 39 residue-level QA methods with very few of them working on protein complex...
Protein Structure, Quaternary Protein Structure, Tertiary Sequence Analysis, Protein Machine Learning COVID-19 SARS-CoV-2 Models, Molecular Caspases Viral Proteins Humans
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Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.

Briefings in bioinformatics Sep 2, 2021
As an essential task in protein structure and function prediction, protein fold recognition has attracted increasing attention. The majority of the existing machine learning-based protein fold recognition approaches strongly rely on handcrafted featu...
Protein Interaction Maps Computational Biology Proteins Humans Neural Networks, Computer Machine Learning Protein Structure, Tertiary Data Visualization Semantics Protein Folding
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Artificial intelligence in structural biology is here to stay.

Nature Jul 1, 2021
Protein Folding Protein Structure, Tertiary Molecular Biology Artificial Intelligence Software
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