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Article . 2024
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Article . 2024
License: CC BY
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Article . 2024
License: CC BY
Data sources: Datacite
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In silico modelling and characterization of Epstein–Barr virus LMP1 protein

Authors: Dayang-Sharyati D.A. Salam; Kavinda Kashi Juliyan Gunasinghe; Hwang Siaw San; Irine Runnie Henry Ginjom; Xavier Chee Wezen; Taufiq Rahman;

In silico modelling and characterization of Epstein–Barr virus LMP1 protein

Abstract

Abstract Latent membrane protein 1 (LMP1) plays a crucial role in Epstein-Barr virus (EBV)’s ability to establish latency and is involved in the development and progression of EBV-associated cancers. Additionally, EBV-infected cells affect the immune responses, making it challenging for immune system to eliminate. Due to the aforementioned reasons, it is important to understand the structural features of LMP1 which is essential for the development of novel cancer therapies that target its signaling pathways. To date, there is no complete LMP1 protein structure therefore in our work, we modeled the full-length LMP1 containing the short cytoplasmic N-terminus, six transmembrane domains and a long-simulated C-terminus. Our model showed good stability and protein compactness evaluated through accelerated-Molecular Dynamics where the conformational ensemble exhibited compact folds, particularly in the transmembrane domains. Our results suggest that specific domains or motifs, predominantly in the C-terminus domain of LMP1 show promise as potential drug targets. As a whole, our work provides insights on key strucutral features of LMP1 that will allow the development of novel LMP1 therapies.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid
Related to Research communities
Cancer Research