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ABSTRACT Many of the modeling targets in the blind CASP-11/CAPRI-30 experiment were protein homo-dimers and homo-tetramers. Here, we perform a retrospective docking-based analysis of the perfectly symmetrical CAPRI Round 30 targets whose crystal structures have been published. Starting from the CASP 'stage-2' fold prediction models, we show that using our recently developed 'SAM' polar Fourier symmetry docking algorithm combined with NAMD energy minimization often gives acceptable or better 3D models of the target complexes. We also use SAM to analyze the overall quality of all CASP structural models for the selected targets from a docking-based perspective. We demonstrate that docking only CASP 'center' structures for the selected targets provides a fruitful and economical docking strategy. Furthermore, our results show that many of the CASP models are dockable in the sense that they can lead to acceptable or better models of symmetrical complexes. Even though SAM is very fast, using docking and NAMD energy minimization to pull out acceptable docking models from a large ensemble of docked CASP models is computationally expensive. Nonetheless, thanks to our SAM docking algorithm, we expect that applying our docking protocol on a modern computer cluster will give us the ability to routinely model 3D structures of symmetrical protein complexes from CASP-quality models. Proteins 2017; 85:463-469. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

While the number of solved 3D protein structures continues to grow rapidly, the structural rules that distinguish protein-protein interactions between different structural families are still not clear. Here, we classify and analyse the secondary structural features and promiscuity of a comprehensive non-redundant set of domain family binding sites (DFBSs) and hetero domain-domain interactions (DDIs) extracted from our updated KBDOCK resource. We have partitioned 4001 DFBSs into five classes using their propensities for three types of secondary structural elements ("α" for helices, "β" for strands, and "γ" for irregular structure) and we have analysed how frequently these classes occur in DDIs. Our results show that β elements are not highly represented in DFBSs compared to α and γ elements. At the DDI level, all classes of binding sites tend to preferentially bind to the same class of binding sites and α/β contacts are significantly disfavored. Very few DFBSs are promiscuous: 80% of them interact with just one Pfam domain. About 50% of our Pfam domains bear only one single-partner DFBS and are therefore monogamous in their interactions with other domains. Conversely, promiscuous Pfam domains bear several DFBSs among which one or two are promiscuous, thereby multiplying the promiscuity of the concerned protein. [ABSTRACT FROM AUTHOR]

The question of how best to compare and classify the (three-dimensional) structures of proteins is one of the most important unsolved problems in computational biology. To help tackle this problem, we have developed a novel shape-density superposition algorithm called 3D-Blast which represents and superposes the shapes of protein backbone folds using the spherical polar Fourier correlation technique originally developed by us for protein docking. The utility of this approach is compared with several well-known protein structure alignment algorithms using receiver-operator-characteristic plots of queries against the 'gold standard' CATH database. Despite being completely independent of protein sequences and using no information about the internal geometry of proteins, our results from searching the CATH database show that 3D-Blast is highly competitive compared to current state-of-the-art protein structure alignment algorithms. A novel and potentially very useful feature of our approach is that it allows an average or 'consensus' fold to be calculated easily for a given group of protein structures. We find that using consensus shapes to represent entire fold families also gives very good database query performance. We propose that using the notion of consensus fold shapes could provide a powerful new way to index existing protein structure databases, and that it offers an objective way to cluster and classify all of the currently known folds in the protein universe. Proteins 2012. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03286-9. [ABSTRACT FROM AUTHOR]

Comparing and classifying protein domain interactions according to their three-dimensional (3D) structures can help to understand protein structure-function and evolutionary relationships. Additionally, structural knowledge of existing domain-domain interactions can provide a useful way to find structural templates with which to model the 3D structures of unsolved protein complexes. Here we present a straightforward guide to using the "Kbdock" protein domain structure database and its associated web site for exploring and comparing protein domain-domain interactions (DDIs) and domain-peptide interactions (DPIs) at the Pfam domain family level. We also briefly explain how the Kbdock web site works, and we provide some notes and suggestions which should help to avoid some common pitfalls when working with 3D protein domain structures.