PINOT: an intuitive resource for integrating protein-protein interactions

Tomkins, James E.; Ferrari, Raffaele; Vavouraki, Nikoleta; Hardy, John; Lovering, Ruth C.; Lewis, Patrick A.; McGuffin, Liam J.; Manzoni, Claudia

doi:10.1186/s12964-020-00554-5

Cited by 28 publications

(35 citation statements)

References 33 publications

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“…The HSP seeds (HSP genes, n=66 and test seeds, n=17; see Table 1, Supplementary Table 1, and Materials and Methods) were used as the input list to query the online tool, PINOT (Tomkins et al , 2020), generating a list of experimentally validated, human PPIs. Briefly, PINOT collects PPIs from 7 manually curated databases that fully or partially comply with the IMEx annotation guidelines (Orchard et al , 2012), and scores each interaction based on the number of different methods and publications in which it has been described.…”

Section: Resultsmentioning

confidence: 99%

“…By containing all the shared interactors and connections among seeds, the core HSP-PPIN can be used to infer shared functions communal to multiple HSP genes. (Tomkins et al ., 2020).…”

Section: Discussionmentioning

confidence: 99%

“…The 83 seeds were used as the input to query the PINOT webtool (Tomkins et al ., 2020) [http://www.reading.ac.uk/bioinf/PINOT/PINOT_form.html]. PINOT produces a list of experimentally demonstrated binary PPIs containing unique, human PPI data obtained by merging and processing PPI data from 7 databases: BioGrid (Oughtred et al , 2019), InnateDB (Breuer et al , 2013), IntAct (Orchard et al , 2014), MBInfo (Singapore, 2019), MINT (Licata et al , 2012), UniProt (UniProt, 2019) and bhf-ucl.…”

Section: Methodsmentioning

confidence: 99%

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Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias

Vavouraki

Tomkins

Kara

et al. 2021

Preprint

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The Hereditary Spastic Paraplegias are a group of neurodegenerative diseases characterized by spasticity and weakness in the lower body. Despite the identification of causative mutations in over 70 genes, the molecular aetiology remains unclear. Due to the combination of genetic diversity and variable clinical presentation, the Hereditary Spastic Paraplegias are a strong candidate for protein-protein interaction network analysis as a tool to understand disease mechanism(s) and to aid functional stratification of phenotypes. In this study, experimentally validated human protein-protein interactions were used to create a protein-protein interaction network based on the causative Hereditary Spastic Paraplegia genes. Network evaluation as a combination of both topological analysis and functional annotation led to the identification of core proteins in putative shared biological processes such as intracellular transport and vesicle trafficking. The application of machine learning techniques suggested a functional dichotomy linked with distinct sets of clinical presentations, suggesting there is scope to further classify conditions currently described under the same umbrella term of Hereditary Spastic Paraplegias based on specific molecular mechanisms of disease.

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Section: Resultsmentioning

confidence: 99%

“…By containing all the shared interactors and connections among seeds, the core HSP-PPIN can be used to infer shared functions communal to multiple HSP genes. (Tomkins et al ., 2020).…”

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias

Vavouraki

Tomkins

Kara

et al. 2021

Preprint

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“…However, there are several proteins that are the common interactors of both LRRK2 and CORO1C: ABCE1, ACTR2, CDC42, DAPK1, MYO1C, RAC1, and TP53, identified using PINOT. 43 Among those 1,805 variants that were obtained from the study of Nalls et al 2019, 4…”

Section: Resultsmentioning

confidence: 99%

Genome-wide association studies of LRRK2 modifiers of Parkinson's disease

Lai

Alipanahi

Fontanillas

et al. 2020

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Objective: The aim of this study was to search for genes/variants that modify the effect of LRRK2 mutations in terms of penetrance and age-at-onset of Parkinson's disease. Methods: We performed the first genome-wide association study of penetrance and age-at-onset of Parkinson's disease in LRRK2 mutation carriers (776 cases and 1,103 non-cases at their last evaluation). Cox proportional hazard models and linear mixed models were used to identify modifiers of penetrance and age-at-onset of LRRK2 mutations, respectively. We also investigated whether a polygenic risk score derived from a published genome-wide association study of Parkinson's disease was able to explain variability in penetrance and age-at-onset in LRRK2 mutation carriers. Results: A variant located in the intronic region of CORO1C on chromosome 12 (rs77395454; P-value=2.5E-08, beta=1.27, SE=0.23, risk allele: C) met genome-wide significance for the penetrance model. A region on chromosome 3, within a previously reported linkage peak for Parkinson's disease susceptibility, showed suggestive associations in both models (penetrance top variant: P-value=1.1E-07; age-at-onset top variant: P-value=9.3E-07). A polygenic risk score derived from publicly available Parkinson's disease summary statistics was a significant predictor of penetrance, but not of age-at-onset. Interpretation: This study suggests that variants within or near CORO1C may modify the penetrance of LRRK2 mutations. In addition, common Parkinson's disease associated variants collectively increase the penetrance of LRRK2 mutations.

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“…We generated a human interactome of LRRK2 and compared it with the signi cant hits found in kidney total and phospho-proteomics using the PINOT searching tool (http://www.reading.ac.uk/bioinf/PINOT/PINOT_form.html) which collates published, experimentally validated protein-protein interaction (PPI) data from 7 different databases (bhf-ucl, BioGRID, InnateDB, IntAct, MBInfo, MINT and UniProt), merged the annotations and performed quality control providing a nal score indicative of reproducibility (23). The PPIs of LRRK2 with a nal score >2 were kept as rst layer interactors (i.e.…”

Section: Human Lrrk2 Interactome Analysesmentioning

confidence: 99%

Preclinical Modeling of Chronic Inhibition of the Parkinson’s Disease Associated Kinase LRRK2 Reveals Altered Function of the Endolysosomal System in Vivo

Kluss

Mazza

et al. 2020

Preprint

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BackgroundThe most common mutation in the Leucine-rich repeat kinase 2 gene (LRRK2), G2019S, causes familial Parkinson’s Disease (PD) and renders the encoded protein kinase hyperactive. To date, the molecular effects of chronic LRRK2 inhibition have not yet been examined in vivo. MethodsWe evaluated the utility of newly available phospho-antibodies for Rab substrates pT73 Rab10, pS106 Rab12, pT71 Rab29 and LRRK2 autophosphorylation to examine the pharmacodynamic response to acute treatment paradigms with the potent and specific LRRK2 inhibitor, MLi-2, in brain and peripheral tissue in G2019S LRRK2 knock-in mice to define the relative target engagement between brain and LRRK2-enriched peripheral tissues. The molecular effects of 10 days and 10 weeks of chronic in-diet dosing were also evaluated using TMTpro reagents for LC-MS/MS total and phospho- proteomics in brain and kidney tissues. ResultsWe report higher sensitivity of LRRK2 autophosphorylation to MLi-2 treatment and slower recovery in washout conditions compared to Rab GTPases phosphorylation, and we identify pS106 Rab12 as a robust readout of downstream LRRK2 activity across tissues. The downstream effects of long-term chronic LRRK2 inhibition in vivo were evaluated in G2019S LRRK2 knock-in mice by phospho- and total proteomic analyses following an in-diet administration of MLi-2 for 10 weeks. We observed alterations in endolysosomal and trafficking pathways in the kidney that were sensitive to MLi-2 treatment and that we validated biochemically. Furthermore, a subtle but distinct biochemical signature affecting mitochondrial proteins was observed in brain tissue in the same animals that was reverted by kinase inhibition. ConclusionsThis is the first study to examine the molecular underpinnings of chronic LRRK2 inhibition in a preclinical in vivo PD model and highlights cellular processes that may be influenced by therapeutic strategies aimed at restoring LRRK2 physiological activity in PD patients.

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PINOT: an intuitive resource for integrating protein-protein interactions

Cited by 28 publications

References 33 publications

Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias

Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias

Genome-wide association studies of LRRK2 modifiers of Parkinson's disease

Preclinical Modeling of Chronic Inhibition of the Parkinson’s Disease Associated Kinase LRRK2 Reveals Altered Function of the Endolysosomal System in Vivo

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