ArticleMethods in molecular biology (Clifton, N.J.)2013
A modular perspective of protein structures: application to fragment based loop modeling.
Article in Methods in molecular biology (Clifton, N.J.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Physics Determines and Evolution Shapes Basic Units of Protein Function and Allosteric Regulation.Methods in molecular biology (Clifton, N.J.) · 2026Review
- On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction.NAR genomics and bioinformatics · 2021Article
- Assessing the accuracy of contact predictions in CASP13.Proteins · 2019Article
- Protein structural motifs in prediction and design.Current opinion in structural biology · 2017Review
- Distance-Guided Forward and Backward Chain-Growth Monte Carlo Method for Conformational Sampling and Structural Prediction of Antibody CDR-H3 Loops.Journal of chemical theory and computation · 2017Article
- Tertiary alphabet for the observable protein structural universe.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Modularity of Protein Folds as a Tool for Template-Free Modeling of Structures.PLoS computational biology · 2015Article
- Fast protein loop sampling and structure prediction using distance-guided sequential chain-growth Monte Carlo method.PLoS computational biology · 2014Article
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Authors and funding
2 authors.
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Abstract
Proteins can be decomposed into supersecondary structure modules. We used a generic definition of supersecondary structure elements, so-called Smotifs, which are composed of two flanking regular secondary structures connected by a loop, to explore the evolution and current variety of structure building blocks. Here, we discuss recent observations about the saturation of Smotif geometries in protein structures and how it opens new avenues in protein structure modeling and design. As a first application of these observations we describe our loop conformation modeling algorithm, ArchPred that takes advantage of Smotifs classification. In this application, instead of focusing on specific loop properties the method narrows down possible template conformations in other, often not homologous structures, by identifying the most likely supersecondary structure environment that cradles the loop. Beyond identifying the correct starting supersecondary structure geometry, it takes into account information of fit of anchor residues, sterical clashes, match of predicted and observed dihedral angle preferences, and local sequence signal.
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