Communication network model of the immune system identifies the impact of interactions with SARS-CoV-2 proteins

TL;DR

This paper introduces a communication network model of the immune system to quantify how SARS-CoV-2 proteins transfer information and cause dysregulation, aiding in understanding COVID-19 immunopathology and therapy efficacy.

Contribution

It presents a novel network-based approach to measure information transfer from viral proteins to the immune system, linking it to biological process dysregulation and treatment effectiveness.

Findings

Quantifies immune system control by viral proteins.

Identifies biological processes susceptible to dysregulation.

Provides a measure for therapy efficacy based on information transfer.

Abstract

Interactions between SARS-CoV-2 and human proteins (SARS-CoV-2 PPIs) cause information transfer through biochemical pathways that contribute to the immunopathology of COVID-19. Here, we present a communication network model of the immune system to compute the information transferred by the viral proteins using the available SARS-CoV-2 PPIs data. The amount of transferred information depends on the reference state of the immune system, or the state without SARS-CoV-2 PPIs, and can quantify how many variables of the immune system are controlled by the viral proteins. The information received by the immune system proteins from the viral proteins is useful to identify the biological processes (BPs) susceptible to dysregulation, and also to estimate the duration of viral PPIs necessary for the dysregulation to occur. We found that computing the drop in information from viral PPIs due to drugs provides a direct measure for the efficacy of therapies.