The Journal of Physical Chemistry BBiophysicsPeer-reviewed journal article
Insertion and Anchoring of HIV-1 Fusion Peptide into Complex Membrane Mimicking Human T-cell
Mingfei ZhaoiD, Laura J. S. LopesiD, Harshita Sahni, Anju Yadav, Hung Nguyen DoiD, Tyler J. ReddyiD, César A. LópeziD, Chris NealeiD, Sandrasegaram GnanakaraniD
Abstract
A fundamental understanding of how HIV-1 envelope (Env) protein facilitates fusion is still lacking. The HIV-1 fusion peptide, consisting of 15 to 22 residues, is the N-terminus of the gp41 subunit of the Env protein. Further, this peptide, a promising vaccine candidate, initiates viral entry into target cells by inserting and anchoring into human immune cells. The influence of membrane lipid reorganization and the conformational changes of the fusion peptide during the membrane insertion and anchoring processes, which can significantly affect HIV-1 cell entry, remains largely unexplored due to the limitations of experimental measurements. In this work, we investigate the insertion of the fusion peptide into an immune cell membrane mimic through multiscale molecular dynamics simulations. We mimic the native T-cell by constructing a 9-lipid asymmetric membrane, along with geometrical restraints accounting for insertion in the context of gp41. To account for the slow timescale of lipid mixing while enabling conformational changes, we implement a protocol to go back and forth between atomistic and coarse-grained simulations. Our study provides a molecular understanding of the interactions between the HIV-1 fusion peptide and the T-cell membrane, highlighting the importance of conformational flexibility of fusion peptides and local lipid reorganization in stabilizing the anchoring of gp41 into the targeted host membrane during the early events of HIV-1 cell entry. Importantly, we identify a motif within the fusion peptide critical for fusion that can be further manipulated in future immunological studies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/606381v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@d80eedorg.highwire.dtl.DTLVardef@bc2482org.highwire.dtl.DTLVardef@f715org.highwire.dtl.DTLVardef@15dba11_HPS_FORMAT_FIGEXP M_FIG Table of Content. C_FIG
- organism: human
- assay: structural biology
- research focus: host-pathogen & immune response
- approach: deep learning
- approach: statistical model
- Citations
- 6
- FWCI
- 0.69
- Field percentile
- top 35%
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