Assessment of Computational Modeling of Fc-Fc Receptor Binding Through Protein-protein Docking Tool
- Authors
- Jebamani, Petrina; Sokalingam, Sriram; Sriramulu, Dinesh Kumar; Jung, Sang Taek; Lee, Sun-Gu
- Issue Date
- 9월-2020
- Publisher
- KOREAN SOC BIOTECHNOLOGY & BIOENGINEERING
- Keywords
- protein-protein docking; HADDOCK; Fc fragment; Fc receptor; binding residues; molecular interaction
- Citation
- BIOTECHNOLOGY AND BIOPROCESS ENGINEERING, v.25, no.5, pp.734 - 741
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- BIOTECHNOLOGY AND BIOPROCESS ENGINEERING
- Volume
- 25
- Number
- 5
- Start Page
- 734
- End Page
- 741
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/53226
- DOI
- 10.1007/s12257-020-0050-5
- ISSN
- 1226-8372
- Abstract
- Structural information of Fc-Fc receptor interaction may contribute to the design of drugs or therapeutic antibodies associated with the interaction. Computational protein-protein docking can be employed in structural study of protein-protein interaction, but its efficiency and reliability are still unstable and need to be validated and optimized for respective target protein complexes. In this study, we investigated and assessed the computational modeling efficiency of Fc-Fc gamma R complex through HADDOCK by defining five different sets of active residues, a major parameter to determine the prediction efficiency of HADDOCK. The binding residues identified experimentally or the residues in the binding pocket were confirmed to be efficient active residues to achieve a high prediction efficiency, and too narrower or wider specification of active residues led to poor prediction efficiency. Most binding residues and crucial molecular interactions such as conserved interactions and hydrogen bonds in the crystal structure were reproduced in the best model. The HADDOCK docking condition determined in this study is expected to be applied to the computational characterization of various Fc-Fc receptor complexes and mutants.
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Collections - Graduate School > Department of Biomedical Sciences > 1. Journal Articles
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