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Cell Communication and Signaling
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Cell Communication and Signaling
Article . 2021
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Computer-aided design of PVR mutants with enhanced binding affinity to TIGIT

Authors: Xiaowen Zhou; Jiangfeng Du; Xiuman Zhou; Xiaoshuang Niu; Wanqiong Li; Chunxia Chen; Sifan Lv; +8 Authors

Computer-aided design of PVR mutants with enhanced binding affinity to TIGIT

Abstract

Abstract Background TIGIT, as a novel immune checkpoint molecule involved in T cell and NK cell anergy, could induce the immune tolerance and escape through binding with its ligand PVR. Blockade of TIGIT/PVR is considered as a promising strategy in cancer immunotherapy. However, to facilitate the design of inhibitors targeting TIGIT/PVR, the structural characteristics and binding mechanism still need to be further studied. Methods In this study, molecular dynamics (MD) simulations and in silico mutagenesis were used to analyze the interaction between TIGIT and its ligand PVR. Then, PVR mutants were designed and their activities were determined by using TIGIT overexpressed Jurkat cells. Results The results suggested that the loops of PVR (CC′ loop, C′C″ loop, and FG loop) underwent a large intra-molecular rearrangement, and more hydrogen bond crosslinking between PVR and TIGIT were formed during MD simulations. The potential residues for PVR to interact with TIGIT were identified and utilized to predict high affinity PVR mutants. Through the biological activity evaluation, four PVR mutants (PVRS72W, PVRS72R, PVRG131V and PVRS132Q) with enhanced affinity to TIGIT were discovered, which could elicit more potent inhibitory effects compared with the wild type PVR. Conclusions The MD simulations analysis provided new insights into the TIGIT/PVR interaction model, and the identified PVR mutants (PVRS72W, PVRS72R, PVRG131V and PVRS132Q) could serve as new candidates for immunotherapy to block TIGIT/PVR.

Related Organizations
Keywords

Cancer immunotherapy, CHO Cells, Molecular dynamics, Molecular Dynamics Simulation, Drug design, Jurkat Cells, Cricetulus, Animals, Humans, Receptors, Immunologic, QH573-671, Research, R, Coculture Techniques, TIGIT/PVR, HEK293 Cells, Mutagenesis, Mutation, Medicine, Computer-Aided Design, Receptors, Virus, Cytology, Protein Binding

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    citations
    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).
    6
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
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!
6
Top 10%
Average
Top 10%
Green
gold
Related to Research communities
Cancer Research