Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Standard
Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches. / Landreh, Michael; Sahin, Cagla; Gault, Joseph; Sadeghi, Samira; Drum, Chester L.; Uzdavinys, Povilas; Drew, David; Allison, Timothy M.; Degiacomi, Matteo T.; Marklund, Erik G.
I: Analytical Chemistry, Bind 92, Nr. 18, 2020, s. 12297-12303.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches
AU - Landreh, Michael
AU - Sahin, Cagla
AU - Gault, Joseph
AU - Sadeghi, Samira
AU - Drum, Chester L.
AU - Uzdavinys, Povilas
AU - Drew, David
AU - Allison, Timothy M.
AU - Degiacomi, Matteo T.
AU - Marklund, Erik G.
PY - 2020
Y1 - 2020
N2 - In structural biology, collision cross sections (CCSs) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Although assigning protein shapes purely on CCS data is not possible, we find that we can distinguish oblate- and prolate-shaped protein complexes by using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures. Furthermore, comparing the CCS of a ferritin cage to the solution structures in the PDB reveals significant deviations caused by structural collapse in the gas phase. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and a eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.
AB - In structural biology, collision cross sections (CCSs) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Although assigning protein shapes purely on CCS data is not possible, we find that we can distinguish oblate- and prolate-shaped protein complexes by using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures. Furthermore, comparing the CCS of a ferritin cage to the solution structures in the PDB reveals significant deviations caused by structural collapse in the gas phase. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and a eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.
KW - GAS-PHASE PROTEIN
KW - MASS-SPECTROMETRY
KW - ION MOBILITY
KW - COMPACTION
KW - INSIGHTS
KW - CHARGE
KW - ELECTROSPRAY
KW - CALIBRATION
KW - ANTIPORTER
KW - MECHANISM
U2 - 10.1021/acs.analchem.0c01940
DO - 10.1021/acs.analchem.0c01940
M3 - Journal article
C2 - 32660238
VL - 92
SP - 12297
EP - 12303
JO - Industrial And Engineering Chemistry Analytical Edition
JF - Industrial And Engineering Chemistry Analytical Edition
SN - 0003-2700
IS - 18
ER -
ID: 249908692