Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 나승진 | - |
dc.date.accessioned | 2022-03-02T06:05:15Z | - |
dc.date.available | 2022-03-02T06:05:15Z | - |
dc.date.issued | 2020-06 | - |
dc.identifier.citation | COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, v. 18, page. 1391-1402 | en_US |
dc.identifier.issn | 2001-0370 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S2001037020302907?via%3Dihub | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/168728 | - |
dc.description.abstract | Mass spectrometry (MS) has made enormous contributions to comprehensive protein identification and quantification in proteomics. MS is also gaining momentum for structural biology in a variety of ways, complementing conventional structural biology techniques. Here, we will review how MS-based techniques, such as hydrogen/deuterium exchange, covalent labeling, and chemical cross-linking, enable the characterization of protein structure, dynamics, and interactions, especially from a perspective of their data analyses. Structural information encoded by chemical probes in intact proteins is decoded by interpreting MS data at a peptide level, i.e., revealing conformational and dynamic changes in local regions of proteins. The structural MS data are not amenable to data analyses in traditional proteomics workflow, requiring dedicated software for each type of data. We first provide basic principles of data interpretation, including isotopic distribution and peptide sequencing. We then focus particularly on computational methods for structural MS data analyses and discuss outstanding challenges in a proteome-wide large scale analysis. | en_US |
dc.description.sponsorship | This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2017R1E1A1A01077412, 2019M3E5D3073568). S.N. was supported by BK21 Plus project. | en_US |
dc.language.iso | en | en_US |
dc.publisher | ELSEVIER | en_US |
dc.subject | Structural biology | en_US |
dc.subject | Mass spectrometry | en_US |
dc.subject | Hydrogen/deuterium exchange | en_US |
dc.subject | Covalent labeling | en_US |
dc.subject | Chemical cross-linking | en_US |
dc.subject | Computational proteomics | en_US |
dc.subject | Bioinformatics software | en_US |
dc.title | Computational methods in mass spectrometry-based structural proteomics for studying protein structure, dynamics, and interactions | en_US |
dc.type | Article | en_US |
dc.relation.volume | 18 | - |
dc.identifier.doi | 10.1016/j.csbj.2020.06.002 | - |
dc.relation.page | 1391-1402 | - |
dc.relation.journal | COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL | - |
dc.contributor.googleauthor | Na, Seungjin | - |
dc.contributor.googleauthor | Paek, Eunok | - |
dc.relation.code | 2020049734 | - |
dc.sector.campus | S | - |
dc.sector.daehak | RESEARCH INSTITUTE[S] | - |
dc.sector.department | INSTITUTION FOR ARTIFICIAL INTELLIGENCE RESEARCH HY_AIR | - |
dc.identifier.pid | sna | - |
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