Interactions between DC-SIGN and the envelope protein from Dengue and Zika viruses: a structural perspective based on molecular dynamics and MM/GBSA analyses

Bruno Stein Barbosa Menechino1, Rodrigo Bentes Kato2, Helena Cristina Ferreira Franz2, Pedro Eduardo Almeida da Silva2, Marcus Alexandre Finzi Corat1, Daniel Ferreira de Lima Neto2
1Multidisciplinary Center for Biological Research - Laboratory for the Development of Biological Models, University of Campinas, Campinas, Brazil
2General-Coordination of Public Health Laboratories, Department of Strategic Articulation in Health and Ambient, Ministry of Health, Brasília, Brazil

Tóm tắt

AbstractZika virus (ZIKV) and dengue virus (DENV) share a lot of similarities being both phylogenetically closely related, share the same insect vector passage for reaching the host, affinity for the same carbohydrate receptor domains (CRDs), indicating feasible competition between them on the natural field. Here, we prospected interactions of both envelope proteins with a DC-SIGN, a transmembrane c-type lectine receptor with the most implicated CRD with the Flavivirus infection presents on dendritic cells involved in viruses replication processes into the host, and among rares CRD receptors susceptible to interacting with a broad of subtypes of DENV. Protein–protein docking procedures produced structures for molecular dynamics experiments, suggesting the most energetically favorable complex. The difference found in the deltaG results prompted the experimentation with molecular dynamics. To investigate further specific residues involved with such interactions we produced a decomposition analysis using molecular dynamics of the docked proteins evaluated afterward with the Generalized Born Surface Area method. Solvent-accessible surface area (SASA) analysis for both showed very similar but with a slight reduction for ZIKV_E, which agreed with residues SASA analysis highlighting regions more exposed in the ZIVK protein than in DENV. Despite residues PHE313 is reponsible for most of the interactions with the envelope of these arboviruses, ZIKV interacted with this residue in DC-SIGN with lower energies and using more interactions with not expexted residues GLU241 and ARG386. Taken together these results suggest better competitive interaction of ZIKV with the DC-SIGN receptor, particularly in the CRD portion.

Từ khóa


Tài liệu tham khảo

Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013;496(7446):504–7.

Li J, Jia K, Liu Y, Yuan B, Xia M, Zhao W. Spatiotemporal distribution of zika virus and its spatially heterogeneous relationship with the environment. Int J Environ Res Public Health. 2021;18(1):290.

Paz S, Semenza JC. El Niño and climate change-contributing factors in the dispersal of Zika virus in the Americas? Lancet Lond Engl. 2016;387(10020):745.

Hassert M, Brien JD, Pinto AK. The temporal role of cytokines in flavivirus protection and pathogenesis. Curr Clin Microbiol Rep. 2019;6(1):25–33.

Tassaneetrithep B, Burgess TH, Granelli-Piperno A, Trumpfheller C, Finke J, Sun W, et al. DC-SIGN (CD209) mediates dengue virus infection of human dendritic cells. J Exp Med. 2003;197(7):823–9.

Frontiers | Flavivirus Receptors: Diversity, Identity, and Cell Entry [Internet]. [cited 2023 Apr 28]. https://doi.org/10.3389/fimmu.2018.02180/full

Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46(W1):W296-303.

Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF Chimera-a visualization system for exploratory research and analysis. J Comput Chem. 2004;25(13):1605–12.

Williams CJ, Headd JJ, Moriarty NW, Prisant MG, Videau LL, Deis LN, et al. MolProbity: more and better reference data for improved all-atom structure validation. Protein Sci Publ Protein Soc. 2018;27(1):293–315.

Eisenberg D, Lüthy R, Bowie JU. [20] VERIFY3D: Assessment of protein models with three-dimensional profiles. In: Methods in Enzymology [Internet]. Academic Press; 1997 [cited 2023 Apr 28]. pp. 396–404. (Macromolecular Crystallography Part B; vol. 277). https://www.sciencedirect.com/science/article/pii/S0076687997770228

Laskowski RA, MacArthur MW, Thornton JM. PROCHECK: validation of protein-structure coordinates. In: International Tables for Crystallography [Internet]. Wiley; 2012 [cited 2023 Apr 28]. pp 684–7. https://doi.org/10.1107/97809553602060000882

Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35(Web Server issue):W407–10.

Laskowski RA, Swindells MB. LigPlot+: multiple ligand-protein interaction diagrams for drug discovery. J Chem Inf Model. 2011;51(10):2778–86.

van Zundert GCP, Rodrigues JPGLM, Trellet M, Schmitz C, Kastritis PL, Karaca E, et al. The HADDOCK2.2 web server: user-friendly integrative modeling of biomolecular complexes. J Mol Biol. 2016;428(4):720–5.

Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, et al. GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1(1–2):19–25.

Valdés-Tresanco MS, Valdés-Tresanco ME, Valiente PA, Moreno E. gmx_MMPBSA: a new tool to perform end-state free energy calculations with GROMACS. J Chem Theory Comput. 2021;17(10):6281–91.

McGibbon RT, Beauchamp KA, Harrigan MP, Klein C, Swails JM, Hernández CX, Schwantes CR, Wang LP, Lane TJ, Pande VS. MDTraj: a modern open library for the analysis of molecular dynamics trajectories. Biophys J. 2015;109(8):1528–32.

Grant BJ, Rodrigues AP, ElSawy KM, McCammon JA, Caves LS. Bio3D: an R package for the comparative analysis of protein structures. Bioinformatics. 2006;22(21):2695–6.