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Title: | Combining Information from Crosslinks and Monolinks in the Modeling of Protein Structures |
Authors: | Sinnott, Matthew Malhotra, Sony MADHUSUDHAN, M. S. Thalassinos, Konstantinos Topf, Maya Dept. of Biology |
Keywords: | XLMS Crosslinks Monolinks|Rresidue depth Protein structure modeling Mass spectrometry Integrative modeling Structure prediction 2020 2020-SEP-WEEK3 TOC-SEP-2020 |
Issue Date: | Sep-2020 |
Publisher: | Elsevier B.V. |
Citation: | Structure, 28(9), 1061-1070.e3. |
Abstract: | Monolinks are produced in a chemical crosslinking mass spectrometry experiment and are more abundant than crosslinks. They convey residue exposure information, but so far have not been used in the modeling of protein structures. Here, we present the Monolink Depth Score (MoDS), for assessing structural models based on the depth of monolinked residues, corresponding to their distance to the nearest bulk water. Using simulated and reprocessed experimental data from the Proteomic Identification Database, we compare the performance of MoDS to MNXL, our previously developed score for assessing models based on crosslinking data. Our results show that MoDS can be used to effectively score models based on monolinks, and that a crosslink/monolink combined score (XLMO) leads to overall higher performance. The work strongly supports the use of monolink data in the context of integrative structure determination. We also present XLM-Tools, a program to assist in this effort, available at: https://github.com/Topf-Lab/XLM-Tools. |
URI: | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/5053 https://doi.org/10.1016/j.str.2020.05.012 |
ISSN: | 0969-2126 1878-4186 |
Appears in Collections: | JOURNAL ARTICLES |
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