Large scale modelling of SARS-CoV-2 Protein-Protein Interactions in humans and their role in COVID-19 disease
Title: Large scale modelling of SARS-CoV-2 Protein-Protein Interactions in humans and their role in COVID-19 disease
SNIC Project: SNIC 2020/6-74
Project Type: SNIC Medium Storage
Principal Investigator: Claudio Mirabello <claudio.mirabello@scilifelab.se>
Affiliation: Linköpings universitet
Duration: 2020-03-31 – 2021-04-01
Classification: 10610 10203 10601
Keywords:

Abstract

The interaction between proteins (protein-protein interactions, or PPIs) play a most significant role inside and outside the cells of all organisms. Unfortunately, these mechanisms can also be used by parasites to take advantage of a host's resources and cause it harm. It is what happens with viral infections such as those caused by the recent SARS-CoV-2 virus pandemic. The virus attaches itself to human cells, hijacks the protein machinery inside them and uses it to create more copies of itself so that it can spread. All of these steps involve the interaction between SARS-CoV-2 proteins and human proteins, and one way to stop the infection is to understand how these interactions are happening and to find out how they can be disrupted (for example, by drugs that keeps viral proteins from being able to attach to the host's proteins). We have developed a software pipeline called InterPred that represents the state of the art for in silico PPI prediction and modelling, outperforming also experimental methods for PPI detection such as Y2H assays (see here: https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.25280). Our first aim is to use InterPred to model all possible interactions between SARS-CoV-2 and human proteins, and to make our findings available to the scientific community as quickly as possible. This is quite a computationally intensive task that involves structural modelling of thousands of protein structures as well as running structural alignments on massive scale. Our second aim is to use another software we have developed, InterComp (https://academic.oup.com/bioinformatics/article/34/17/i787/5093254), to scan the SARS-CoV-2 proteins for possible interfaces, i.e. patches on the surface of the protein that are interacting with other molecules (human proteins, DNA, RNA, small molecules etc). These interfaces would be prime candidates for the design of molecules to inhibit interaction with host organisms. This project is part of a larger, emergency effort by SciLifeLab and the Swedish research community to tackle the COVID-19 pandemic. InterPred is already up and running on Tetralith, but we need a large amount of computing hours if we want to reach our goal in good time.