Your browser doesn't support javascript.
loading
Native top-down mass spectrometry for higher-order structural characterization of proteins and complexes.
Liu, Ruijie; Xia, Shujun; Li, Huilin.
Afiliación
  • Liu R; School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
  • Xia S; School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
  • Li H; School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Mass Spectrom Rev ; 42(5): 1876-1926, 2023.
Article en En | MEDLINE | ID: mdl-35757976
ABSTRACT
Progress in structural biology research has led to a high demand for powerful and yet complementary analytical tools for structural characterization of proteins and protein complexes. This demand has significantly increased interest in native mass spectrometry (nMS), particularly native top-down mass spectrometry (nTDMS) in the past decade. This review highlights recent advances in nTDMS for structural research of biological assemblies, with a particular focus on the extra multi-layers of information enabled by TDMS. We include a short introduction of sample preparation and ionization to nMS, tandem fragmentation techniques as well as mass analyzers and software/analysis pipelines used for nTDMS. We highlight unique structural information offered by nTDMS and examples of its broad range of applications in proteins, protein-ligand interactions (metal, cofactor/drug, DNA/RNA, and protein), therapeutic antibodies and antigen-antibody complexes, membrane proteins, macromolecular machineries (ribosome, nucleosome, proteosome, and viruses), to endogenous protein complexes. The challenges, potential, along with perspectives of nTDMS methods for the analysis of proteins and protein assemblies in recombinant and biological samples are discussed.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Mass Spectrom Rev Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Mass Spectrom Rev Año: 2023 Tipo del documento: Article País de afiliación: China