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Knowledge-based Approaches for Modelling the 3D Structural Interactome

Anisah Ghoorah 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Understanding how the protein interactome works at a structural level could provide useful insights into the mechanisms of diseases. Comparative homology modelling and ab initio protein docking are two computational methods for modelling the three-dimensional (3D) structures of protein-protein interactions (PPIs). Previous studies have shown that both methods give significantly better predictions when they incorporate experimental PPI information. However, in general, PPI information is often not available in an easily accessible way, and cannot be re-used by 3D PPI modelling algorithms. Hence, there is currently a need to develop a reliable framework to facilitate the reuse of PPI data. This thesis presents a systematic knowledge-based approach for representing, describing and manipulating 3D interactions to study PPIs on a large scale and to facilitate knowledge-based modelling of protein-protein complexes. The main contributions of this thesis are: (1) it describes an integrated database of non-redundant 3D hetero domain interactions; (2) it presents a novel method of describing and clustering DDIs according to the spatial orientations of the binding partners, thus introducing the notion of "domain family-level binding sites" (DFBS); (3) it proposes a structural classification of DFBSs similar to the CATH classification of protein folds, and it presents a study of secondary structure propensities of DFBSs and interaction preferences; (4) it introduces a systematic case-base reasoning approach to model on a large scale the 3D structures of protein complexes from existing structural DDIs. All these contributions have been made publicly available through a web server ( The KBDOCK database contains 2,721 non-redundant hetero DDIs corresponding to 1,439 DFBSs located in 947 distinct domain families. The KBDOCK database allows large-scale studies. For example, it was used to show that: (1) nearly 70% of protein domain families have just one binding site and the remaining families have a small number of binding sites which suggests that DDIs often re-use the same binding sites; (2) over 80% of DFBSs interact with just one other type of protein domain family, and very few DFBSs interact with more than three different Pfam domain families, which indicates that most DFBSs are primarily monogamous in their structural relationships with other domains; (3) Pfam families often have secondary structure pairing preferences, which might be useful for the prediction of unknown DDIs; (4) when DFBSs are in fact re-used, focused docking improves significantly the docking predictions. Thus, KBDOCK provides a useful framework for enriching our knowledge of the structural interactome.
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Contributor : Anisah Ghoorah <>
Submitted on : Friday, December 7, 2012 - 10:27:52 AM
Last modification on : Friday, October 23, 2020 - 4:36:26 PM
Long-term archiving on: : Monday, March 11, 2013 - 11:35:13 AM


  • HAL Id : tel-01749614, version 2


Anisah Ghoorah. Knowledge-based Approaches for Modelling the 3D Structural Interactome. Bioinformatics [q-bio.QM]. Université de Lorraine, 2012. English. ⟨NNT : 2012LORR0204⟩. ⟨tel-01749614v2⟩



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