Hybrid structural modeling of alloantibody binding to human leukocyte antigen with rapid and reproducible cross-linking mass spectrometry

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Hybrid structural modeling of alloantibody binding to human leukocyte antigen with rapid and reproducible cross-linking mass spectrometry
Title:
Hybrid structural modeling of alloantibody binding to human leukocyte antigen with rapid and reproducible cross-linking mass spectrometry
Journal Title:
Cell Reports Methods
Publication Date:
30 August 2023
Citation:
Ser, Z., Gu, Y., Yap, J., Lim, Y. T., Wang, S. M., Hamidinia, M., Murali, T. M., Kumar, R., Gascoigne, N. RJ., MacAry, P. A., & Sobota, R. M. (2023). Hybrid structural modeling of alloantibody binding to human leukocyte antigen with rapid and reproducible cross-linking mass spectrometry. Cell Reports Methods, 3(9), 100569. https://doi.org/10.1016/j.crmeth.2023.100569
Abstract:
Alloantibody recognition of donor human leukocyte antigen (HLA) is associated with poor clinical transplantation outcomes. However, the molecular and structural basis for the alloantibody-HLA interaction is not well understood. Here, we used a hybrid structural modeling approach on a previously studied alloantibody-HLA interacting pair with inputs from ab initio, in silico, and in vitro data. Highly reproducible cross-linking mass spectrometry data were obtained with both discovery- and targeted mass spectrometry-based approaches approaches. The cross-link information was then used together with predicted antibody Fv structure, predicted antibody paratope, and in silico-predicted interacting surface to model the antibody-HLA interaction. This hybrid structural modeling approach closely recapitulates the key interacting residues from a previously solved crystal structure of an alloantibody-HLA-A∗11:01 pair. These results suggest that a predictive-based hybrid structural modeling approach supplemented with cross-linking mass spectrometry data can provide functionally relevant structural models to understand the structural basis of antibody-HLA mismatch in transplantation
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the Agency for Science, Technology and Research - Career Development Award
Grant Reference no. : 212D800074

This research / project is supported by the National Research Foundation, Singapore - NRF-SIS (Shared Infrastructure Support) - "Sing-Mass" scheme
Grant Reference no. : NRF2017_SISFP08

This research / project is supported by the Agency for Science, Technology and Research - Young Achiever award
Grant Reference no. :

This research / project is supported by the Ministry of Health National Medical Research Council - NMRC grant
Grant Reference no. : MOH-000438
Description:
ISSN:
2667-2375