Unlocking the secrets of SARS-CoV-2 nsp3 by combining experiments with AlphaFold2 domain prediction

TL;DR

Researchers combined AI predictions and experiments to better understand the structure and function of a key SARS-CoV-2 protein.

Contribution

A previously unknown folded domain in SARS-CoV-2 nsp3 was predicted and experimentally confirmed.

Findings

A novel folded domain in nsp3 was identified and validated experimentally.

Domain Y1 may play a role in assembling viral proteins into a pore that exports RNA.

The study proposes a revised domain segmentation and naming system for nsp3.

Abstract

Combining structural bioinformatics, AI-based fold prediction, and traditional experiments sheds light on the largest SARS-CoV-2 protein.

Nonstructural protein 3 (nsp3) is crucial for SARS-CoV-2 infection. It is the largest protein of the virus with roughly 2000 residues, and a major drug target. However, because of its size, disordered regions, and transmembrane domains, the atomic structure of the whole protein has not yet been established. Only 10 out of its 16 domains were individually determined in experiments. Here, we demonstrate how structural bioinformatics, AI-based fold prediction, and traditional experiments complement each other and can shed light on the makeup of this important protein, both in SARS-CoV-2 and in related viruses. Our method can be generalized for other multidomain proteins. Our prediction-based approach reveals a previously undescribed folded domain, which we could confirm experimentally. Our research also suggests a potential function of the domain Y1: this domain may be involved in the assembly of nsp3, nsp4, and nsp6 into the hexameric pore, which was discovered by electron tomography and exports RNA into the cytosol. The Y1 hexamer, however, could not be expressed on its own. We revise domain segmentation and nomenclature of nsp3 domains.

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