Journal of Chemical Information and ModelingBiophysicsPeer-reviewed journal article
Synergistic Effects of pH and Temperature on Dengue VirusEnvelope Dimers: Insights from Microsecond MolecularDynamics Simulations
Georcki Ropón‐PalaciosiD, Luís Gustavo Fávaro CrespiiD, Ingrid B. S. MartinsiD, Walter RocchiaiD, Alexandre Suman de AraújoiD
Abstract
Dengue pathogenesis depends on a conformational rearrangement of the envelope (E) glycoprotein induced by low pH; however, how pH and temperature cooperate to destabilize its prefusion dimeric state, a fundamental step that enables the formation of the fusion-active trimer, remains unclear. Here, we investigate this synergy for Dengue serotypes of greatest medical relevance, DENV-2 and DENV-3. All-atom molecular dynamics simulations were performed on the microsecond scale, at 28 {degrees}C, 37 {degrees}C, and 40 {degrees}C under pH 5-7, using CHARMM36m force fields. The increase in temperature from 28 {degrees}C to 37 {degrees}C doubled the conformational space explored at neutral pH and weakened both dimers through the reduction or loss of the interaction network along the dimeric interface. Acidification amplified this effect in a serotype-specific manner: DENV-2 required pH 5, while DENV-3 responded at pH 6. Distance and principal component analyses revealed an asymmetric dissociation route, termed the "compensatory embrace", in which retraction of Domains I and III in one monomer is balanced by advancement of its partner on the opposite side, temporarily preserving the number of inter-subunit contacts. Structural analyses highlighted the difference in histidine distribution between the serotypes. These results outline hierarchical physicochemical triggers that convert the dimer into fusion-competent monomers. Targeting the interfacial interaction network or reinforcing the "compensatory embrace" to prevent completion of dissociation offers new perspectives for broad-spectrum antivirals and immunogen design, underscoring the value of long-timescale molecular dynamics in drug discovery.
- organism: virus
- assay: structural biology
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 25th percentile
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