AIMC Topic: Protein Folding

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The breakthrough in protein structure prediction.

The Biochemical journal
Proteins are the essential agents of all living systems. Even though they are synthesized as linear chains of amino acids, they must assume specific three-dimensional structures in order to manifest their biological activity. These structures are ful...

State-of-the-art web services for de novo protein structure prediction.

Briefings in bioinformatics
Residue coevolution estimations coupled to machine learning methods are revolutionizing the ability of protein structure prediction approaches to model proteins that lack clear homologous templates in the Protein Data Bank (PDB). This has been patent...

ProtFold-DFG: protein fold recognition by combining Directed Fusion Graph and PageRank algorithm.

Briefings in bioinformatics
As one of the most important tasks in protein structure prediction, protein fold recognition has attracted more and more attention. In this regard, some computational predictors have been proposed with the development of machine learning and artifici...

A novel sequence alignment algorithm based on deep learning of the protein folding code.

Bioinformatics (Oxford, England)
MOTIVATION: From evolutionary interference, function annotation to structural prediction, protein sequence comparison has provided crucial biological insights. While many sequence alignment algorithms have been developed, existing approaches often ca...

GraphQA: protein model quality assessment using graph convolutional networks.

Bioinformatics (Oxford, England)
MOTIVATION: Proteins are ubiquitous molecules whose function in biological processes is determined by their 3D structure. Experimental identification of a protein's structure can be time-consuming, prohibitively expensive and not always possible. Alt...

Protein sequence design by conformational landscape optimization.

Proceedings of the National Academy of Sciences of the United States of America
The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowe...

Fold-LTR-TCP: protein fold recognition based on triadic closure principle.

Briefings in bioinformatics
As an important task in protein structure and function studies, protein fold recognition has attracted more and more attention. The existing computational predictors in this field treat this task as a multi-classification problem, ignoring the relati...

MotifCNN-fold: protein fold recognition based on fold-specific features extracted by motif-based convolutional neural networks.

Briefings in bioinformatics
Protein fold recognition is one of the most critical tasks to explore the structures and functions of the proteins based on their primary sequence information. The existing protein fold recognition approaches rely on features reflecting the character...