Dataset Information

Improved affinity at the cost of decreased specificity: a recurring theme in PDZ-peptide interactions.

ABSTRACT: The E6 protein from human papillomavirus (HPV) plays an important role during productive infection and is a potential drug target. We have previously designed a high affinity bivalent protein binder for the E6 protein, a fusion between a helix from the E6 associated protein and PDZØ9, an engineered variant (L391F/K392M) of the second PDZ domain from synapse associated protein 97 (SAP97 PDZ2). How the substitutions improve the affinity of SAP97 PDZ2 for HPV E6 is not clear and it is not known to what extent they affect the specificity for cellular targets. Here, we explore the specificity of wild type SAP97 PDZ2 and PDZØ9 through proteomic peptide phage display. In addition, we employ a double mutant cycle of SAP97 PDZ2 in which the binding kinetics for nine identified potential cellular peptide ligands are measured and compared with those for the C-terminal E6 peptide. The results demonstrate that PDZØ9 has an increased affinity for all peptides, but at the cost of specificity. Furthermore, there is a peptide dependent coupling free energy between the side chains at positions 391 and 392. This corroborates our previous allosteric model for PDZ domains, involving sampling of intramolecular energetic pathways.

SUBMITTER: Karlsson OA

PROVIDER: S-EPMC5046105 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Improved affinity at the cost of decreased specificity: a recurring theme in PDZ-peptide interactions.

Karlsson O Andreas OA Sundell Gustav N GN Andersson Eva E Ivarsson Ylva Y Jemth Per P

Scientific reports 20161003

The E6 protein from human papillomavirus (HPV) plays an important role during productive infection and is a potential drug target. We have previously designed a high affinity bivalent protein binder for the E6 protein, a fusion between a helix from the E6 associated protein and PDZØ9, an engineered variant (L391F/K392M) of the second PDZ domain from synapse associated protein 97 (SAP97 PDZ2). How the substitutions improve the affinity of SAP97 PDZ2 for HPV E6 is not clear and it is not known to ...[more]

PMID: 27694853

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Project description:BACKGROUND: PDZ domains are one of the most promiscuous protein recognition modules that bind with short linear peptides and play an important role in cellular signaling. Recently, few high-throughput techniques (e.g. protein microarray screen, phage display) have been applied to determine in-vitro binding specificity of PDZ domains. Currently, many computational methods are available to predict PDZ-peptide interactions but they often provide domain specific models and/or have a limited domain coverage. RESULTS: Here, we composed the largest set of PDZ domains derived from human, mouse, fly and worm proteomes and defined binding models for PDZ domain families to improve the domain coverage and prediction specificity. For that purpose, we first identified a novel set of 138 PDZ families, comprising of 548 PDZ domains from aforementioned organisms, based on efficient clustering according to their sequence identity. For 43 PDZ families, covering 226 PDZ domains with available interaction data, we built specialized models using a support vector machine approach. The advantage of family-wise models is that they can also be used to determine the binding specificity of a newly characterized PDZ domain with sufficient sequence identity to the known families. Since most current experimental approaches provide only positive data, we have to cope with the class imbalance problem. Thus, to enrich the negative class, we introduced a powerful semi-supervised technique to generate high confidence non-interaction data. We report competitive predictive performance with respect to state-of-the-art approaches. CONCLUSIONS: Our approach has several contributions. First, we show that domain coverage can be increased by applying accurate clustering technique. Second, we developed an approach based on a semi-supervised strategy to get high confidence negative data. Third, we allowed high order correlations between the amino acid positions in the binding peptides. Fourth, our method is general enough and will easily be applicable to other peptide recognition modules such as SH2 domains and finally, we performed a genome-wide prediction for 101 human and 102 mouse PDZ domains and uncovered novel interactions with biological relevance. We make all the predictive models and genome-wide predictions freely available to the scientific community.

Dataset Information

Improved affinity at the cost of decreased specificity: a recurring theme in PDZ-peptide interactions.

Publications

Improved affinity at the cost of decreased specificity: a recurring theme in PDZ-peptide interactions.

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