Characterization of Diverse Internal Binding Specificities of PDZ Domains by Yeast Two-Hybrid Screening of a Special Peptide Library

Mu, Yifen; Cai, Pengfei; Hu, Siqi; Ma, Sucan; Gao, Youhe

doi:10.1371/journal.pone.0088286

Cited by 24 publications

(28 citation statements)

References 58 publications

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“…Furthermore, the PDZ proteins PDZK1 and LNX were analyzed through Y2H screening against random peptide libraries [ 70 , 71 ]. Similarly, the binding preferences for internal PDZ binding motifs was profiled by screening of 24 PDZ domains against a nearly random octapeptide Y2H library [ 72 ]. Thus, Y2H can be adopted for domain-motif interaction screening.…”

Section: Introductionmentioning

confidence: 99%

High-throughput methods for identification of protein-protein interactions involving short linear motifs

Blikstad

Ivarsson

2015

Cell Commun Signal

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Interactions between modular domains and short linear motifs (3–10 amino acids peptide stretches) are crucial for cell signaling. The motifs typically reside in the disordered regions of the proteome and the interactions are often transient, allowing for rapid changes in response to changing stimuli. The properties that make domain-motif interactions suitable for cell signaling also make them difficult to capture experimentally and they are therefore largely underrepresented in the known protein-protein interaction networks. Most of the knowledge on domain-motif interactions is derived from low-throughput studies, although there exist dedicated high-throughput methods for the identification of domain-motif interactions. The methods include arrays of peptides or proteins, display of peptides on phage or yeast, and yeast-two-hybrid experiments. We here provide a survey of scalable methods for domain-motif interaction profiling. These methods have frequently been applied to a limited number of ubiquitous domain families. It is now time to apply them to a broader set of peptide binding proteins, to provide a comprehensive picture of the linear motifs in the human proteome and to link them to their potential binding partners. Despite the plethora of methods, it is still a challenge for most approaches to identify interactions that rely on post-translational modification or context dependent or conditional interactions, suggesting directions for further method development.

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Section: Introductionmentioning

confidence: 99%

High-throughput methods for identification of protein-protein interactions involving short linear motifs

Blikstad

Ivarsson

2015

Cell Commun Signal

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“…In general, PDZ domain classification can be approached from either a structure or sequence based predictions [ 13 – 16 ]. Even though, structural based methods can provide an in-depth understanding of PDZ binding, these methods can be plagued by low throughput and high cost [ 17 – 20 ]. Furthermore, they often provide a glimpse into a single or few PDZ domains, giving less focus to the role of point mutations in PDZ sequence, upstream and downstream sequences relative to the PDZ binding motif, as well as the exact PDZ domain cutoffs that affect ligand affinity [ 21 – 23 ].…”

Section: Introductionmentioning

confidence: 99%

Application of Wavelet Transform for PDZ Domain Classification

et al. 2015

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PDZ domains have been identified as part of an array of signaling proteins that are often unrelated, except for the well-conserved structural PDZ domain they contain. These domains have been linked to many disease processes including common Avian influenza, as well as very rare conditions such as Fraser and Usher syndromes. Historically, based on the interactions and the nature of bonds they form, PDZ domains have most often been classified into one of three classes (class I, class II and others - class III), that is directly dependent on their binding partner. In this study, we report on three unique feature extraction approaches based on the bigram and trigram occurrence and existence rearrangements within the domain's primary amino acid sequences in assisting PDZ domain classification. Wavelet packet transform (WPT) and Shannon entropy denoted by wavelet entropy (WE) feature extraction methods were proposed. Using 115 unique human and mouse PDZ domains, the existence rearrangement approach yielded a high recognition rate (78.34%), which outperformed our occurrence rearrangements based method. The recognition rate was (81.41%) with validation technique. The method reported for PDZ domain classification from primary sequences proved to be an encouraging approach for obtaining consistent classification results. We anticipate that by increasing the database size, we can further improve feature extraction and correct classification.

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“…Sequences of internal peptide binding PDZ domains were obtained from the published work of Mu et al 7 and multiple sequence alignments were carried out using Clustal Omega software 41 . All human PDZ sequences were taken from te velthius et al 4 and only which could be mapped to Uniprot ID 42 were used for alignment.…”

Section: Multiple Sequence Alignment Of Pdz Domainsmentioning

confidence: 99%

“…Hence, majority of the experimental as well as in silico studies for deciphering the specificity landscape of PDZ domains have concentrated on C-terminal peptide recognition. However, a recent genome wide screen using random octapeptide yeast two-hybrid library consisting of internal PDZ binding motifs (PBMs) has identified novel 24 PDZ domains 7 . This suggests that the ability of PDZ domains to bind internal peptides is much more prevalent than previously recognized.…”

Section: Introductionmentioning

confidence: 99%

Structural basis of internal peptide recognition by PDZ domains using molecular dynamics simulations

Sain

Mohanty

2019

Preprint

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PDZ domains are important peptide recognition modules which usually recognize short C-terminal stretches of their interaction partners, but certain PDZ domains can also recognize internal peptides in the interacting proteins. Due to the scarcity of data on internal peptide recognition and lack of understanding of the mechanistic details of internal peptide recognition, identification of PDZ domains capable of recognizing internal peptides has been a difficult task.Since Par-6 PDZ domain can recognize both C-terminal and internal peptides, we have carried out multiple explicit solvent MD simulations of 1 μs duration on free and peptide bound Par-6 PDZ to decipher mechanistic details of internal peptide recognition. These simulations have been analyzed to identify residues which play a crucial role in internal peptide recognition by PDZ domains. Based on the conservation profile of the identified residues, we have predicted 47 human PDZ domains to be capable of recognizing internal peptides in human. We have also investigated how binding of CDC42 to the CRIB domain adjacent to the Par6 PDZ allosterically modulate the peptide recognition by Par6 PDZ. Our MD simulations on CRIB-Par6_PDZ didomain in isolation as well as in complex with CDC42, indicate that in absence of CDC42 the adjacent CRIB domain induces open loop conformation of PDZ facilitating internal peptide recognition. On the other hand, upon binding of CDC42 to the CRIB domain, Par6 PDZ adopts closed loop conformation required for recognition of C-terminus peptides. These results provide atomistic details of how binding of interaction partners onto adjacent domains can allosterically regulate substrate binding to PDZ domains. In summary, MD simulations provide novel insights into the modulation of substrate recognition preference of PDZ by specific peptides, adjacent domains and binding of interaction partners at allosteric sites.

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Characterization of Diverse Internal Binding Specificities of PDZ Domains by Yeast Two-Hybrid Screening of a Special Peptide Library

Cited by 24 publications

References 58 publications

High-throughput methods for identification of protein-protein interactions involving short linear motifs

High-throughput methods for identification of protein-protein interactions involving short linear motifs

Application of Wavelet Transform for PDZ Domain Classification

Structural basis of internal peptide recognition by PDZ domains using molecular dynamics simulations

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