A Resource for the Network Representation of Cell Perturbations Caused by SARS-CoV-2 Infection

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has caused more than 2.3 million casualties worldwide and the lack of effective treatments is a major health concern. The development of targeted drugs is held back due to a limited understanding of the molecular mechanisms underlying the perturbation of cell physiology observed after viral infection. Recently, several approaches, aimed at identifying cellular proteins that may contribute to COVID-19 pathology, have been reported. Albeit valuable, this information offers limited mechanistic insight as these efforts have produced long lists of cellular proteins, the majority of which are not annotated to any cellular pathway. We have embarked in a project aimed at bridging this mechanistic gap by developing a new bioinformatic approach to estimate the functional distance between a subset of proteins and a list of pathways. A comprehensive literature search allowed us to annotate, in the SIGNOR 2.0 resource, causal information underlying the main molecular mechanisms through which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and related coronaviruses affect the host–cell physiology. Next, we developed a new strategy that enabled us to link SARS-CoV-2 interacting proteins to cellular phenotypes via paths of causal relationships. Remarkably, the extensive information about inhibitors of signaling proteins annotated in SIGNOR 2.0 makes it possible to formulate new potential therapeutic strategies. The proposed approach, which is generally applicable, generated a literature-based causal network that can be used as a framework to formulate informed mechanistic hypotheses on COVID-19 etiology and pathology.

SIGNOR 3.0, the SIGnaling network open resource 3.0: 2022 update

“…( A ) The SIGNOR 2.0 and 3.0 home pages. ( B ) SIGNOR 3.0 provides direct access to related projects: DisNor ( 14 ), CancerGeneNet ( 15 ), Myo-REG ( 16 ) and the COVID-19 ( 17 ). ( C ) The disease browser builds causal network connecting genes that have been found to be mutated in patients affected by a specific disease (GDA, nodes in yellow), as provided by the DisGeNET ( 20 ), IntOGen ( 21 ) and Cancer Gene Census ( 22 ) resources.…”

“…The most important updates of the newly redesigned resource are within the scope of functionality. These include 1) the direct access to SIGNOR-related projects (Figure 3B ), namely, DisNor ( 14 ), CancerGeneNet ( 15 ), Myo-REG ( 16 ) and the COVID-19 ( 17 ); 2) novel search and filtering options, organized as tabs in the search box. Briefly, the tabs ‘Search’, ‘Disease Browser’, ‘Pathway Browser’ and ‘Advanced methods’ give access to search and graph tools to explore the SIGNOR dataset (Figure 3A , Supplementary Figure S1A ).…”

A Resource to Infer Molecular Paths Linking Cancer Mutations to Perturbation of Cell Metabolism

“…We developed a tool that, for each query node and metabolic pathway, “navigates” the network graph and retrieves the shortest paths connecting the query node to a rate-limiting enzyme of the end pathway. Shortest paths are identified using a strategy adapted from Perfetto et al (2021) . For each query protein and metabolic pathway, we retrieve all the directional paths (of length of four steps or fewer) connecting the query protein and the rate-limiting enzymes (RLEs) of the pathway.…”

Autophagy and Mitophagy-Related Pathways at the Crossroads of Genetic Pathways Involved in Familial Sarcoidosis and Host-Pathogen Interactions Induced by Coronaviruses

“…As suggested recently by Perfetto and collaborators, gene set enrichment methods frequently exploit molecular interaction networks and miss functional consequences-i.e., activation or repression of intracellular pathways-of these interactions. [143].…”