Dataset Information

Native mass spectrometry of an allosteric heterodimer of SARS-CoV-2

ABSTRACT: The capability of native MS to probe protein-protein and protein-ligand interactions was exemplified with the allosteric heterodimer from SARS-CoV-2 consisting of the nonstructural proteins (nsp) nsp10 and nsp16. Complex dynamics, allostery, and ligand binding were shown. A metadata Excel file, 'nsp1016_metadata.xlsx' is included to help orient users which raw files were used for which analyses. Supplementary binding affinity calculations for ligand binding results are found in an Excel file found in directory 'Kd_analysis'. UniDec (Universal Deconvolution of Mass and Ion Mobility Spectra) configuration '.dat' files are found in their respective directories.

INSTRUMENT(S): SYNAPT G2-Si, Orbitrap Exploris 480, Q Exactive HF

ORGANISM(S): Escherichia Coli Bl21(de3) (ncbitaxon:469008)

SUBMITTER: Mowei Zhou

PROVIDER: MSV000092776 | MassIVE | Mon Aug 28 22:08:00 BST 2023

REPOSITORIES: MassIVE

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Publications

Expanding Native Mass Spectrometry to the Masses.

Harvey Sophie R SR Gadkari Varun V VV Ruotolo Brandon T BT Russell David H DH Wysocki Vicki H VH Zhou Mowei M

Journal of the American Society for Mass Spectrometry 20240201 3

At the 33rd ASMS Sanibel Meeting, on Membrane Proteins and Their Complexes, a morning roundtable discussion was held discussing the current challenges facing the field of native mass spectrometry and approaches to expanding the field to nonexperts. This Commentary summarizes the discussion and current initiatives to address these challenges. ...[more]

PMID: 38303101

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Project description:Allosteric communication between distant sites in proteins is central to nearly all biological regulation but still poorly characterised for most proteins, limiting conceptual understanding, biological engineering and allosteric drug development. Typically only a few allosteric sites are known in model proteins, but theoretical, evolutionary and some experimental studies suggest they may be much more widely distributed. An important reason why allostery remains poorly characterised is the lack of methods to systematically quantify long-range communication in diverse proteins. Here we address this shortcoming by developing a method that uses deep mutational scanning to comprehensively map the allosteric landscapes of protein interaction domains. The key concept of the approach is the use of ‘multidimensional mutagenesis’: mutational effects are quantified for multiple molecular phenotypes—here binding and protein abundance—and in multiple genetic backgrounds. This is an efficient experimental design that allows the underlying causal biophysical effects of mutations to be accurately inferred en masse by fitting thermodynamic models using neural networks. We apply the approach to two of the most common human protein interaction domains, an SH3 domain and a PDZ domain, to produce the first global atlases of allosteric mutations for any proteins. Allosteric mutations are widely dispersed with extensive long-range tuning of binding affinity and a large mutational target space of network-altering ‘edgetic’ variants. Mutations are more likely to be allosteric closer to binding interfaces, at Glycines in secondary structure elements and at particular sites including a chain of residues connecting to an opposite surface in the PDZ domain. This general approach of quantifying mutational effects for multiple molecular phenotypes and in multiple genetic backgrounds should allow the energetic and allosteric landscapes of many proteins to be rapidly and comprehensively mapped.