Další formáty:
BibTeX
LaTeX
RIS
@article{2425602,
author = {FernandezandGimenez, E. and Martinez, M M and Marabini, R. and Střelák, David and SanchezandGarcia, R. and Carazo, J M and Sorzano, C O S},
article_location = {UNITED STATES},
article_number = {4},
doi = {http://dx.doi.org/10.1016/j.jsb.2023.108024},
keywords = {Projection subtraction; Nanodisc; Ligand; SPA; Cryo-EM},
language = {eng},
issn = {1047-8477},
journal = {Journal of Structural Biology},
title = {A new algorithm for particle weighted subtraction to decrease signals from unwanted components in single particle analysis},
url = {https://www.sciencedirect.com/science/article/pii/S1047847723000874?via%3Dihub},
volume = {215},
year = {2023}
}
TY - JOUR
ID - 2425602
AU - Fernandez-Gimenez, E. - Martinez, M M - Marabini, R. - Střelák, David - Sanchez-Garcia, R. - Carazo, J M - Sorzano, C O S
PY - 2023
TI - A new algorithm for particle weighted subtraction to decrease signals from unwanted components in single particle analysis
JF - Journal of Structural Biology
VL - 215
IS - 4
SP - 1-8
EP - 1-8
PB - ACADEMIC PRESS INC ELSEVIER SCIENCE
SN - 10478477
KW - Projection subtraction
KW - Nanodisc
KW - Ligand
KW - SPA
KW - Cryo-EM
UR - https://www.sciencedirect.com/science/article/pii/S1047847723000874?via%3Dihub
N2 - Single particle analysis (SPA) in cryo-electron microscopy (cryo-EM) is highly used to obtain the near-atomic structure of biological macromolecules. The current methods allow users to produce high-resolution maps from many samples. However, there are still challenging cases that require extra processing to obtain high resolution. This is the case when the macromolecule of the sample is composed of different components and we want to focus just on one of them. For example, if the macromolecule is composed of several flexible subunits and we are interested in a specific one, if it is embedded in a viral capsid environment, or if it has additional components to stabilize it, such as nanodiscs. The signal from these components, which in principle we are not interested in, can be removed from the particles using a projection subtraction method. Currently, there are two projection subtraction methods used in practice and both have some limitations. In fact, after evaluating their results, we consider that the problem is still open to new solutions, as they do not fully remove the signal of the components that are not of interest. Our aim is to develop a new and more precise projection subtraction method, improving the performance of state-of-the-art methods. We tested our algorithm with data from public databases and an in-house data set. In this work, we show that the performance of our algorithm improves the results obtained by others, including the localization of small ligands, such as drugs, whose binding location is unknown a priori.
ER -
FERNANDEZ-GIMENEZ, E., M M MARTINEZ, R. MARABINI, David STŘELÁK, R. SANCHEZ-GARCIA, J M CARAZO a C O S SORZANO. A new algorithm for particle weighted subtraction to decrease signals from unwanted components in single particle analysis. \textit{Journal of Structural Biology}. UNITED STATES: ACADEMIC PRESS INC ELSEVIER SCIENCE, 2023, roč.~215, č.~4, s.~1-8. ISSN~1047-8477. Dostupné z: https://dx.doi.org/10.1016/j.jsb.2023.108024.
|
