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A structure-based classification and analysis of protein domain family binding sites and their interactions.

ABSTRACT: 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 ("?" for helices, "?" for strands, and "?" for irregular structure) and we have analysed how frequently these classes occur in DDIs. Our results show that ? elements are not highly represented in DFBSs compared to ? and ? elements. At the DDI level, all classes of binding sites tend to preferentially bind to the same class of binding sites and ?/? 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.

SUBMITTER: Ghoorah AW

PROVIDER: S-EPMC4498303 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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A structure-based classification and analysis of protein domain family binding sites and their interactions.

Ghoorah Anisah W AW Devignes Marie-Dominique MD Alborzi Seyed Ziaeddin SZ Smaïl-Tabbone Malika M Ritchie David W DW

Biology 20150409 2

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 usin ...[more]

PMID: 25860777

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Project description:The featureless interface formed by protein-protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.

Project description:BackgroundProtein interactions are essential for coordinating cellular functions. Proteomic studies have already elucidated a huge amount of protein-protein interactions that require detailed functional analysis. Understanding the structural basis of each individual interaction through their structural determination is necessary, yet an unfeasible task. Therefore, computational tools able to predict protein binding regions and recognition modes are required to rationalize putative molecular functions for proteins. With this aim, we previously created SCOWLP, a structural classification of protein binding regions at protein family level, based on the information obtained from high-resolution 3D protein-protein and protein-peptide complexes.DescriptionWe present here a new version of SCOWLP that has been enhanced by the inclusion of protein-nucleic acid and protein-saccharide interactions. SCOWLP takes interfacial solvent into account for a detailed characterization of protein interactions. In addition, the binding regions obtained per protein family have been enriched by the inclusion of predicted binding regions, which have been inferred from structurally related proteins across all existing folds. These inferences might become very useful to suggest novel recognition regions and compare structurally similar interfaces from different families.ConclusionsThe updated SCOWLP has new functionalities that allow both, detection and comparison of protein regions recognizing different types of ligands, which include other proteins, peptides, nucleic acids and saccharides, within a solvated environment. Currently, SCOWLP allows the analysis of predicted protein binding regions based on structure-based inferences across fold space. These predictions may have a unique potential in assisting protein docking, in providing insights into protein interaction networks, and in guiding rational engineering of protein ligands. The newly designed SCOWLP web application has an improved user-friendly interface that facilitates its usage, and is available at http://www.scowlp.org.

Project description:BACKGROUND: The SET (Su(var)3-9, Enhancer-of-zeste, Trithorax) domain is an evolutionarily conserved sequence of approximately 130-150 amino acids, and constitutes the catalytic site of lysine methyltransferases (KMTs). KMTs perform many crucial biological functions via histone methylation of chromatin. Histone methylation marks are interpreted differently depending on the histone type (i.e. H3 or H4), the lysine position (e.g. H3K4, H3K9, H3K27, H3K36 or H4K20) and the number of added methyl groups (i.e. me1, me2 or me3). For example, H3K4me3 and H3K36me3 are associated with transcriptional activation, but H3K9me2 and H3K27me3 are associated with gene silencing. The substrate specificity and activity of KMTs are determined by sequences within the SET domain and other regions of the protein. RESULTS: Here we identified 49 SET-domain proteins from the recently sequenced Brassica rapa genome. We performed sequence similarity and protein domain organization analysis of these proteins, along with the SET-domain proteins from the dicot Arabidopsis thaliana, the monocots Oryza sativa and Brachypodium distachyon, and the green alga Ostreococcus tauri. We showed that plant SET-domain proteins can be grouped into 6 distinct classes, namely KMT1, KMT2, KMT3, KMT6, KMT7 and S-ET. Apart from the S-ET class, which has an interrupted SET domain and may be involved in methylation of nonhistone proteins, the other classes have characteristics of histone methyltransferases exhibiting different substrate specificities: KMT1 for H3K9, KMT2 for H3K4, KMT3 for H3K36, KMT6 for H3K27 and KMT7 also for H3K4. We also propose a coherent and rational nomenclature for plant SET-domain proteins. Comparisons of sequence similarity and synteny of B. rapa and A. thaliana SET-domain proteins revealed recent gene duplication events for some KMTs. CONCLUSION: This study provides the first characterization of the SET-domain KMT proteins of B. rapa. Phylogenetic analysis data allowed the development of a coherent and rational nomenclature of this important family of proteins in plants, as in animals. The results obtained in this study will provide a base for nomenclature of KMTs in other plant species and facilitate the functional characterization of these important epigenetic regulatory genes in Brassica crops.

Dataset Information

A structure-based classification and analysis of protein domain family binding sites and their interactions.

Publications

A structure-based classification and analysis of protein domain family binding sites and their interactions.

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