https://orcid.org/0000-0001-6355-8640
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Abstract
SARS-CoV-2 nsp13 is a multifunctional helicase from helicase superfamily 1B. It unwinds the viral RNA genome for replication and is thought to play a role in 5’ mRNA capping to produce mature mRNA using its triphosphatase activity. The sequence and structure are highly conserved in nidovirales and the protein is essential to the viral infection cycle, acting as a standalone enzyme and in conjunction with other SARS-CoV-2 proteins, making SARS-CoV-2 helicase a promising target for structure-based drug design. By inhibiting helicase activity, phosphatase activity, or its interaction with the RNA-dependent RNA polymerase we could interrupt viral replication. A total of 72 structures of SARS-CoV-2 nsp13 have been published in the protein databank (PDB) to date, 56 monomers and 16 as part of a complex. The structure of nsp13 is made up of five conserved folds, from N- to C-terminus, a zinc-binding domain, stalk domain, beta barrel domain 1B, RecA-like subdomain 1A, and RecA-like subdomain 1B. This review summarizes the current structural and functional knowledge surrounding SARS-CoV-2 nsp13 and related helicases, as well as the structure-based drug design efforts to date, and other complementary knowledge to provide downstream users of SARS-CoV-2 structures with a solid foundation to better inform their work.
Acknowledgements
The authors would like to thank the other members of the Corona Virus Structural Taskforce for support and discussion, particularly Pairoh Seeliger for all she did behind the scenes and Lisa Schmidt for providing the beautiful illustrations for the Corona Virus Structural Task Force and insidecorona.net. The Coronavirus Structural Task Force retains copywright for the text and figures.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Subject Index
Helicase Superfamilies 203
Domains 203, 204, 206
Nucleotide binding site 206
RNA dependent RNA Polymerase 206, 213
RNA Caping 206
Assembly 211
Zinc binding domain 204, 205, 207
Stalk Domain 204, 206
1B domain 204, 206
RecA like helicase subdomain 1A 204, 207
RecA like helicase subdomain 2A 204, 208
Helicase Motifs 206, 209
SARS-CoV-1 helicase structure errors 203, 204, 206
Fragment 208, 210
RNA Binding 206, 210
Mechanism 208, 209
β19-β20 loop 213
Replication Transcription Complex 206
Backtracking 214, 215
Docking/MD 217
Bananin 216
Bismuth Compounds 216
FPA-124 217
Suramin-like compounds 217
Additional information
Funding
Notes on contributors
Sam Horrell
Sam Horrell is a beamline scientist at Diamond Light Source Beamline I24. His research interests are focused on method development around time-resolved serial crystallography at synchrotrons and XFELs. He is interested in bridging the gap between ultrafast time-resolved structural biology at XFELs and what can be offered at synchrotrons. Sam has a particular interest in radiation damage in X-ray crystallography and how it can be minimized, mitigated, or used to drive reactions in crystals, such as in metalloproteins where a redox reaction can be kicked off by the electrons generated from X-rays hitting the sample. Sam was the president of the Young Crystallographers Group of the British Crystallographic Association and a member of the BCA Spring meeting organizing committee (2016–2018).
Sam Martino
Sam Martino is a PhD Student in the Rosta Research group at University College London’s Department of Physics and Astronomy. Specializing in the biophysical study of macromolecules, his research revolves around developing simulation and machine-learning techniques to efficiently sample, represent, and understand the kinetic spaces of biomolecular systems, in particular phosphate-catalytic enzymes. Sam’s research interests include understanding the kinetic mechanisms of signalling kinases, atomistic simulations of helicase mechanisms, and the application of modern ML techniques for representing dynamics and 3D-point clouds to protein structural data.
Ferdinand Kirsten
Ferdinand Kirsten finished his bachelor in biochemistry at the University of Würzburg in 2021 and did his bachelor-thesis at Thorn Lab on solvent exchange and interactions in macromolecular crystals. Still new to the world of crystallography and structural refinement, his work in the Coronavirus structural taskforce focused mostly on literature and genome research as well as structural refinement with Coot and the development of 3D models. After his bachelor and work for the taskforce, he moved his focus on Bio-innovations, starting a master at the University of Utrecht in the Netherlands.
Dénes Berta
Dénes Berta is a computational chemist, specialized in discovery of reaction mechanisms. His work revolves around catalytic systems both in small molecule catalysis and enzymatic reactions and inhibition. His approach combines various levels of computational tools, bioinformatics, classical modelling and quantum chemical calculations. He is interested in effective enhanced sampling of high-dimensional system and development of in silico screening procedures. Dénes engages in collaborative efforts with experts of adjacent fields in physics, chemistry and biology.
Gianluca Santoni
Gianluca Santoni’s work is focused on the development of methods for synchrotron serial crystallography, from the comparison of datasets for multi-crystal data collection methods to the implementation of new measurement techniques at synchrotron beamlines. He got his PhD in structural biology studying the structure of acetylcholinesterase in complex with organophosphate nerve agents, applying a mixture of crystallography and computational methods. More recently he has been involved in the data strategies implementation for open science, participating in activities concerning the storage of experimental metadata, the distribution of raw data along with publication according to FAIR principle, and the definition of the Gold standard format for protein diffraction data. His work with the coronavirus structural taskforce has been focused on the implementation of routines to evaluate the quality of both deposited datasets and models.
Andrea Thorn
Andrea Thorn is a specialist for structure solution by crystallography and Cryo-EM, having contributed to programs like SHELX, ANODE and PHASER in the past. Her group at the University of Hamburg develops AI-based methods in crystallography such as the diffraction diagnostics tool AUSPEX and a neural network for secondary structure annotation of Cryo-EM maps (HARUSPEX). Her methods enable other scientists to solve new structures and to answer challenging biological questions. Andrea is very passionate about structural biology and good at bringing people together. She started and leads the Coronavirus Structural Task Force.