PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

Pitre, Sylvain; Dehne, Frank; Chan, Albert; Cheetham, James J.; Duong, Alex; Emili, Andrew; Gebbia, Marinella; Greenblatt, Jack; Jessulat, Matthew; Krogan, Nevan J.; Luo, Xi; Golshani, Ashkan

doi:10.1186/1471-2105-7-365

Cited by 170 publications

(116 citation statements)

References 41 publications

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“…Similarly, Gid8 interacts directly with Gid1 [13]; in addition, gid8 deletion mutants in S. cerevisiae indicated that Gid8 functions as an adapter for Gid2 and Gid9 [13]. An in silico prediction of protein–protein domain interactions in S. cerevisiae implicated a strong involvement of Gid8 within a “core” GID complex: tandem affinity purification of Gid1 and the loss of several Gid1-co-purifying proteins in a Gid8 gene deletion yeast strain (ΔYMR135C) give substance to this hypothesis [27]. Whereas LisH domains from several unrelated proteins have been crystallized [18,24,28] and the LisH domain of muskelin has been crystallized in combination with its N-terminal discoidin domain [29], almost nothing is known about the biochemical properties of TWA1, Gid8 or their orthologues in other eukaryotes.…”

Section: Introductionmentioning

confidence: 99%

Studies of recombinant TWA1 reveal constitutive dimerization

et al. 2017

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The mammalian muskelin/RanBP9/C-terminal to LisH (CTLH) complex and the Saccharomyces cerevisiae glucose-induced degradation (GID) complex are large, multi-protein complexes that each contain a RING E3 ubiquitin ligase. The yeast GID complex acts to degrade a key enzyme of gluconeogenesis, fructose 1,6-bisphosphatase, under conditions of abundant fermentable carbon sources. However, the assembly and functions of the mammalian complex remain poorly understood. A striking feature of these complexes is the presence of multiple proteins that contain contiguous lissencephaly-1 homology (LisH), CTLH and C-terminal CT11-RanBP9 (CRA) domains. TWA1/Gid8, the smallest constituent protein of these complexes, consists only of LisH, CTLH and CRA domains and is highly conserved in eukaryotes. Towards better knowledge of the role of TWA1 in these multi-protein complexes, we established a method for bacterial expression and purification of mouse TWA1 that yields tag-free, recombinant TWA1 in quantities suitable for biophysical and biochemical studies. CD spectroscopy of recombinant TWA1 indicated a predominantly α-helical protein. Gel filtration chromatography, size-exclusion chromatography (SEC) with multi-angle light scattering (SEC-MALS) and native PAGE demonstrated a propensity of untagged TWA1 to form stable dimers and, to a lesser extent, higher order oligomers. TWA1 has a single cysteine residue, Cys139, yet the dimeric form was preserved when TWA1 was purified in the presence of the reducing agent tris(2-carboxyethyl)phosphine (TCEP). These findings have implications for understanding the molecular role of TWA1 in the yeast GID complex and related multi-protein E3 ubiquitin ligases identified in other eukaryotes.

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Section: Introductionmentioning

confidence: 99%

Studies of recombinant TWA1 reveal constitutive dimerization

et al. 2017

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“…Then, use the gathered information to find correlation with query protein partners of a probed interaction. Many methods apply this approach, which have delivered powerful tools for finding new interactions [Pitre et al 2006] and even to corroborate with the protein co-evolution hypothesis [Kim et al 2004]. In the next three Sections we describe three of these methods: PIPE, which compares aminoacid subsequences between probed protein partners and partners of verified protein interactions from a database; and PSIbase and PRISM, both which compare structural characteristics of probed and verified interactions.…”

Section: Methods Based On Verified Interactionsmentioning

confidence: 99%

“…Another, relatively inexpensive, way to predict protein-protein interactions does not include wet lab analysis, using instead a variety of computational approaches. These approaches can complement experimental wet lab techniques and are often supported by either the hypothesis of protein co-evolution [Tan et al 2004, Tillier et al 2006, Izarzugaza et al 2006], structural similarities [Gong et al 2005, Ogmen et al 2005 or amino-acids sequence conservation [Pitre et al 2006].…”

Section: Current Computational Approaches For Predicting Protein-protmentioning

confidence: 99%

“…Three of them, supported by the protein co-evolution hypothesis, are: TSEMA [Izarzugaza et al 2006], ADVICE [Tan et al 2004], Codep [Tillier et al 2006]. The other three, supported by datasets of verified interactions, are: PIPE [Pitre et al 2006], PSIbase [Gong et al 2005], and PRISM [Ogmen et al 2005]. In the next Sections, we describe each one of these two types of methods.…”

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confidence: 99%

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Computational Approaches to Elucidating Transient Protein-Protein Interactions, Predicting Receptor-Ligand Pairings

Iacucci¹,

Xavier‐de‐Souza²,

Moreau³

2012

Protein-Protein Interactions - Computational and Experimental Tools

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“…Our computational inference makes use of the Protein-protein Interaction Prediction Engine (PIPE), an algorithm that predicts PPIs on the basis of protein primary sequence only [32–36]. PIPE breaks query proteins into short overlapping polypeptide segments and searches within a list of known and experimentally verified PPIs to find similar segments.…”

Section: Introductionmentioning

confidence: 99%

Evolution of protein-protein interaction networks in yeast

et al. 2017

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Interest in the evolution of protein-protein and genetic interaction networks has been rising in recent years, but the lack of large-scale high quality comparative datasets has acted as a barrier. Here, we carried out a comparative analysis of computationally predicted protein-protein interaction (PPI) networks from five closely related yeast species. We used the Protein-protein Interaction Prediction Engine (PIPE), which uses a database of known interactions to make sequence-based PPI predictions, to generate high quality predicted interactomes. Simulated proteomes and corresponding PPI networks were used to provide null expectations for the extent and nature of PPI network evolution. We found strong evidence for conservation of PPIs, with lower than expected levels of change in PPIs for about a quarter of the proteome. Furthermore, we found that changes in predicted PPI networks are poorly predicted by sequence divergence. Our analyses identified a number of functional classes experiencing fewer PPI changes than expected, suggestive of purifying selection on PPIs. Our results demonstrate the added benefit of considering predicted PPI networks when studying the evolution of closely related organisms.

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PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

Cited by 170 publications

References 41 publications

Studies of recombinant TWA1 reveal constitutive dimerization

Studies of recombinant TWA1 reveal constitutive dimerization

Computational Approaches to Elucidating Transient Protein-Protein Interactions, Predicting Receptor-Ligand Pairings

Evolution of protein-protein interaction networks in yeast

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