Investigating Ebola virus pathogenicity using molecular dynamics
- Morena Pappalardo†1,
- Francesca Collu†2,
- James Macpherson2,
- Martin Michaelis1,
- Franca Fraternali2Email author and
- Mark N. Wass1Email author
© The Author(s). 2017
Published: 11 August 2017
Ebolaviruses have been known to cause deadly disease in humans for 40 years and have recently been demonstrated in West Africa to be able to cause large outbreaks. Four Ebolavirus species cause severe disease associated with high mortality in humans. Reston viruses are the only Ebolaviruses that do not cause disease in humans. Conserved amino acid changes in the Reston virus protein VP24 compared to VP24 of other Ebolaviruses have been suggested to alter VP24 binding to host cell karyopherins resulting in impaired inhibition of interferon signalling, which may explain the difference in human pathogenicity. Here we used protein structural analysis and molecular dynamics to further elucidate the interaction between VP24 and KPNA5.
As a control experiment, we compared the interaction of wild-type and R137A-mutant (known to affect KPNA5 binding) Ebola virus VP24 with KPNA5. Results confirmed that the R137A mutation weakens direct VP24-KPNA5 binding and enables water molecules to penetrate at the interface. Similarly, Reston virus VP24 displayed a weaker interaction with KPNA5 than Ebola virus VP24, which is likely to reduce the ability of Reston virus VP24 to prevent host cell interferon signalling.
Our results provide novel molecular detail on the interaction of Reston virus VP24 and Ebola virus VP24 with human KPNA5. The results indicate a weaker interaction of Reston virus VP24 with KPNA5 than Ebola virus VP24, which is probably associated with a decreased ability to interfere with the host cell interferon response. Hence, our study provides further evidence that VP24 is a key player in determining Ebolavirus pathogenicity.
KeywordsEbola Molecular dynamics Virology Protein structure Pathogenicity
The potential of Ebolaviruses to cause large outbreaks has been highlighted by the recent Ebola virus outbreak in West Africa  resulting in 28,657 confirmed cases and 11,325 deaths as of 8th May 2016 (http://www.who.int/csr/disease/ebola/en/). To enable replication, viruses depend on mechanisms to antagonise the host cell interferon response. The Ebolavirus proteins that are known to be crucially involved in the suppression of interferon signalling are VP35 and VP24 [2–6]. VP35 prevents interferon signalling by binding and masking double stranded viral RNA. VP24 impairs the host interferon response by binding to the karyopherins α1 (KPNA1), α5 (KPNA5) and α6 (KPNA6) and the transcription factor STAT1 [3–5]. Karyopherins would normally bind STAT1 and transport it to the nucleus, a key step during interferon signalling. VP24 prevents this transport and the subsequent accumulation of STAT1 in the nucleus [2–6].
In this study, we compared the interaction of Ebola virus and Reston virus VP24 with human KPNA5 using protein structural analysis and molecular dynamics simulations.
Analysis of the effect of Ebola VP24 mutations on interaction with KPNA5
The crystal structure of the Ebola virus VP24 complex with KPNA5 is available  as well as co-immunoprecipitation studies that have investigated the effect of mutations on the ability of Ebola virus VP24 to bind KPNA5. The experimental data has shown that the Ebola virus VP24 mutations R137A and the combination of R137A,T138A,Q139A strongly reduce VP24-KPNA5 binding. Combined F134A,M136A mutations resulted in an intermediate level of VP24-KPNA5 binding. Other single point mutations (including Q139A that we used as a control) had limited effect on VP24-KPNA5 binding .
Predicted effect on Ebola VP24-KPNA5 complex stability by mutations in Ebola VP24
(ΔΔG - kcal/mol)
mCSM PP affinity
(ΔΔG - kcal/mol)
(ΔΔG - kcal/mol)
Investigating the effects of VP24 R137A mutation on interaction with KPNA5
According to the experimental data from Xu et al.  the single point mutation R137A is the only point mutation that largely removes binding of VP24 to KPNA5. Thus, we used this mutation to validate our system and to obtain additional molecular information on the interaction between the two proteins. The RMSF calculations (Fig. 2) indicated the greatest movement compared to the wild type VP24 centred around residue 115 and also from residues 135 to 150.
By considering how frequently each grid point (represented as spheres in Fig. 3) was visited by water molecules, we were able to identify solvation sites at the interface in a continuum range from “low density” grid points (short temporal permanence [ps] of water molecules, red spheres in Fig. 3) to “high density” grid points (long temporal permanence [ns] of water molecules, blue spheres in Fig. 3).
In the wild type Ebola virus complex, high density grid points were found close to the residues N185, H186, E203, P204 and D205 (Fig. 3). This means that at the interface there are solvation sites where water molecules are trapped and contribute to stabilise the complex. In contrast, the mutant R137A VP24-KPNA5 complex at the interface is characterised only by low density grids points, meaning that water molecules do not strongly localise stably at this spot and consequently they are not likely to contribute to the stabilisation of the complex. The mutation induces a long-range destabilisation of the complex creating a cleft at the interface where water molecules can freely enter and exit (Fig. 3b). This is an indication that the fit of the two protomers at the interface of the complex is not optimal. We interpret this conformational change as an early event of the detachment of the two proteins.
The correlation of conformational changes between VP24 and KPNA5 were considered next. Previous studies have found that the binding of a protein ligand to a protein receptor can result in correlated enthalpic backbone motions . Consequently, a model of signal propagation built on the analysis of local motions was generated. These were extracted from the molecular dynamics simulations by encoding trajectories into sequences of 4-residue fragment states with the M32 K25 structural alphabet (; see materials and methods for a full description of the numerical procedure used) to estimate the propensity of the Ebola virus VP24 R137A mutant to remain bound to KPNA5. The local error of the structural alphabet fit for the three complexes is shown in Additional file 1: Figure S3.
Comparison of Ebola virus and Reston virus VP24 interaction with KPNA5
Next, the complex formed between Reston virus VP24 and KPNA5 was investigated with the aim of identifying how the interaction between these two proteins may differ from the interaction between Ebola virus VP24 and KPNA5. Only an unbound structure of Reston VP24 was available. Hence, a model of Reston virus VP24 bound to KPNA5 was generated using the Ebola virus VP24-KPNA5 complex as a template (see Methods).
Predicted effect on Ebola virus VP24-KPNA5 complex stability by mutation of residues that are differentially conserved in Reston in Ebola VP24
(ΔΔG - Kcal/mol)
mCSM PP affinity
(ΔΔG - Kcal/mol)
(ΔΔG - Kcal/mol)
PISA and POSPCOMP Interface Analysis at 0 and 600 ns MD snapshots
Ebola VP24–KPNA5 complex
Reston VP24–KPNA5 complex
PISA results at 0 ns
Interface Area (Å2)
Solvation Free Energy (ΔiG, Kcal/M)
PISA results at 600 ns
Interface Area (Å2)
Solvatation Free Energy (ΔiG, Kcal/M)
POPSCOMP results after minimisation
Hydrophobic difference (Å2)
Hydrophilic difference (Å2)
Total difference (Å2)
Throughout the simulation, the RMSD of the main chain C-Alphas was stable for both complexes (Additional file 1: Figure S1). The RMSD of the Reston virus VP24-KPNA5 model is greater than of the Ebola virus VP24-KPNA5 complex, (Additional file 1: Figure S1). This could indicate a difference in the interaction between RESTV VP24 and KPNA5 and could also partly reflect that the simulation is based on a model rather than a solved structure.
For VP24 some minor differences in fluctuation (RMSF) were observed between the Reston virus and Ebola virus proteins. Two of these differences coincided with the interface site at residue 113 (Fig. 2a). Residue 113 is located in an alpha helix at the interface. For KPNA5 there are larger differences in RMSF in four regions, three of which coincide with the complex interface (Fig. 2a). The most pronounced difference is around residues 477–479 (a loop region between two alpha helices), where there is very little fluctuation of KPNA5 in the Ebola virus VP24 complex (around 1 Å) but a peak fluctuation of 8 Å in the Reston virus VP24 complex. The greater fluctuation in KPNA5 suggests that the interaction with Reston virus VP24 differs from that with Ebola virus VP24, supporting the evidence that Reston virus VP24 and human KPNA5 are weaker binding partners than Ebola virus VP24 and human KPNA5.
Analysis of the secondary structure (using DSSP ; see methods) during the simulation revealed minor changes in the VP24 secondary structure occurring at the interface site (Additional file 1: Figure S2). The most important changes were found around residue 76 where there is a prevalence of turns in Ebola virus VP24 which is a coiled structure in Reston virus VP24. Residues 133 and 134 (Additional file 1: Figure S2), as well as residue 146, which are proximal to the binding interface, lose their bend and beta bridge structures to become unstructured in the Reston virus complex. The largest changes in secondary structure were found in KPNA5, particularly in two regions between residues 365–375 and 385–395 (Additional file 1: Figure S2). The second region, which is involved in binding VP24, loses alpha helical structure after 220 ns in the Reston virus complex and changes to a turn structure instead.
For the Reston virus VP24-KPNA5 complex, analysis of solvation at the interface identified high-density grid points (visited by permanent water molecules) close to the residues E203, P204, D205, D124 and R137 (Fig. 3c). As in the case of the wild type Ebola virus VP24-KPNA5 complex, at the interface there are solvation sites where water molecules are trapped and contribute to the stabilisation of the complex. In both the wild type Ebola virus and Reston virus VP24-KPNA5 complexes high-density grid points were found close to the residues E203, P204 and D205. This means that these residues are important in enhancing the stability of both complexes while establishing favourable interactions with water molecules. These residues belong to a loop interacting with KPNA5 defining a cavity where the water molecules are trapped.
The presence in the Reston VP24-KPNA5 complex of high-density grid points, where water molecules are trapped, suggests that part of the interface between Reston virus VP24 and KPNA5 may be relatively stable compared to the R137A-mutated Ebola virus VP24-KPNA5 complex, where only low density grid points were observed, indicating an absence of water molecules that would stabilise the complex (Fig. 3).
Correlation of conformational changes in the Reston virus VP24-KPNA5 complex was compared to the results for the wild type and R137A mutant Ebola virus VP24-KPNA5 complexes. No correlated motions were detectable in the simulation of the Reston virus complex variant of the VP24-KPNA5 complex (Fig. 4c), whereas many were observed for the Ebola virus VP24-KPNA5 complex and fewer for the Ebola virus R137A VP24-KPNA5 complex (see above). Correlation of the conformational changes analysis supported this with the Ebola virus VP24-KPNA5 complex having a denser network of inter-subunit correlations than did the Reston virus VP24-KPNA5 complex, which reflects the results obtained for the R137A mutant Ebola virus VP24-KPNA5 complex (Fig. 4). Taken together, these findings suggest that Reston virus VP24 forms a less stable complex with KPNA5 than Ebola virus VP24, in particular due to the similarity of the results obtained for Reston virus VP24 and R137A-mutated Ebola virus VP24, which is known not to bind human KPNA5 .
This study investigated the dynamics of interaction of the Ebolavirus protein VP24 with human KPNA5. This interaction occurs during infection to prevent transport of STAT1 to the nucleus in order to inhibit interferon signaling [3–5]. Recent findings have identified positions that are differentially conserved between human-pathogenic Ebolaviruses and Reston virus, the only Ebolavirus that is not pathogenic to humans . In particular three of these positions in the interface site between VP24 and human KPNA5 were suggested to affect binding of Reston virus VP24 to KPNA5 and to contribute to the lack of human pathogenicity of Reston viruses .
Experimental evidence showed the R137A mutation in Ebola virus VP24 to reduce VP24 binding to human KPNA5 . Therefore, we compared the Ebola virus VP24-KPNA5 interaction with the R137A-mutant Ebola virus VP24-KPNA5 interaction to validate our system. In concert with the experimental findings , our analysis predicted that the R137A mutation reduces VP24-KPNA5 binding. Moreover, the correlations of conformational changes and solvation analysis provide novel molecular insights into how this mutation affects binding of the two proteins. They show that the mutation reduces the stability of the complex, enables the two proteins to move apart from each other, and for water to enter the interface.
The investigation of the interaction of Reston virus VP24 with human KPNA5 added further evidence that Reston VP24 is a weaker binding partner to human KPNA5 than Ebola virus VP24. This is most strongly suggested by the lack of correlated conformational movements between Reston virus VP24 and KPNA5. Some permanent water molecules are (in contrast to the R137A-mutated Ebola virus VP24-KPNA5 complex) observed in the interface of the Ebola virus VP24- and Reston Virus VP24-KPNA5 complexes. This indicates some differences between the interaction of R137A-mutated Ebola virus VP24 and Reston virus VP24 with human KPNA5.
In conclusion, our results suggest that Reston virus VP24 forms a weaker complex with human KPNA5 than Ebola virus VP24. This weaker binding is anticipated to reduce (in comparison to Ebola virus VP24) the capacity of Reston virus VP24 to inhibit KPNA5-mediated STAT1 transport into the nucleus and to anatagonise interferon signalling in human cells. This reduced Reston virus VP24-KPNA5 complex stability is likely to contribute to the lack of human pathogenicity observed in Reston viruses. Hence, our findings contribute novel evidence indicating VP24 to be an important regulator of species-specific Ebolavirus pathogenicity, as previously suggested by the analysis of conserved differences between Reston viruses and human-pathogenic Ebolaviruses . In addition, our findings provide novel mechanistic insights at the molecular level on the interaction of Ebolavirus VP24 with human KPNA5.
Modelling of a RESTV-VP24 KPNA5 complex
The Ebola and Reston virus VP24 sequences share 81.3% sequence identity and 96% similarity. The protein structures were aligned using Chimera  and a model for Reston VP24 in complex with human KPNA5 built using MODELLER 9.0 . The Reston virus VP24 crystal structure (PDB 4D9O) and the Ebola virus VP24-KPNA5 complex (PDB 4U2X) were used as templates for the Reston virus complex model. 200 models were obtained and the one with the lowest DOPE score was selected.
Comparison of interfaces
PISA  and mCSM  were used to analyse the structural properties at the complexe interfaces, including solvent accessibility and binding affinity. FoldX  was used to predict the effects of the changes in Energy upon mutation, in terms of effects in protein stability. POPSCOMP  was used to determine the contribution of the individual residues to the hydrophilicity and hydrophobicity at the interface, according to their solvent accessible surface area (SASA), using default parameters. The residues were classified as being part of the core, support or rim regions of the interface according to the change in SASA (when the percentage of hydrophobicity was greater than 40 and difference in SASA was less than 10 Å2 the residue was considered as core, otherwise it was rim).
Molecular dynamics simulations
Molecular dynamics simulations were performed for the wild type forms of Ebola virus VP24 and Reston virus VP24 in complex with human KPNA5. Other simulations were performed on the Ebola virus VP24-KPNA5 complex with mutations introduced into VP24 where the effect on KPNA5 binding had been experimentally determined . The mutations considered were: 1)R137A, 2)Q139A, 3)F134A,M136A and 4) R137A-Q139A.
Molecular dynamics simulations were performed using Gromacs 5.0.5 . The procedure used has been previously described . Briefly, starting structured were solvated in a cubic box of SPC water and the distance between the protein and box boundaries was set to a minimum of 12 Å. The standard protonation state (pH 7) for ionisable residues was used, with counterions used to neutralise the system. The GROMOS 53a6 parameter set  was used. Periodic boundary conditions were imposed. Temperature and pressure regulation was performed using the Berendsen algorithm  using coupling constants of 0.2 and 1 ps respectively. The Ewald method  (particle mesh) was used to calculate electrostatic interactions. The neighbour list for non-covalent interactions were updated every five steps. The first minimisation used the 1000 steps of steepest descent. Harmonic positional restraints were applied to the Heavy atoms in the protein (initially 4.8 kcal/mol/Å-2, reduced to 1.24.8 kcal/mol/Å-2) and the temperature (at constant volume) increased from 200 K to 300 K. The simulation was then performed for 100 ps at constant temperature and pressure (300 K and 1 bar). System coordinates were saved every 1 ps.
We selected the force field GROMOS 53a6 because is the latest version of the widely used force field  from the GROMOS family stemming from the most widely used GROMOS 43A1. These parameter sets are often selected in performance studies where force fields are assessed and compared [22–25], and where it is shown that it is still one of the best united-atom force fields available, providing in some cases even better results than some all-atom force fields. Additionally, it is known since a while that the 43A1 parameter set provides better alpha/beta relative stabilities than GROMOS parameter sets developed later .
600 ns MD trajectories were obtained for the Ebola virus VP24-KPNA5 complex and the model of the Reston virus VP24-KPNA5 complex. In our analysis, we omitted the first 280 ns of the simulation, as this was the approximate time required for each of the systems to reach conformational equilibrium. 200 ns trajectories were obtained for R137A and F134A, M136A and 100 ns for all other simulations.
Molecular dynamics analysis
Trajectories were analysed using the GROMACS analysis tools, VMD tools and the Bio3D package for R [27, 28]. For the analysis, standard Periodic Boundary Conditions were removed and Minimum Image Convention (MIC) were applied to all the trajectories. Rotational and translational movements were then deleted in order to perform the Principal Component Analysis. Secondary structure plots for trajectories were obtained using the DSSP  tool in gromacs. Root mean square deviation (RMSD) and fluctuation (RMSF) from the initial starting complex were obtained using Bio3D, as well as the PCA analysis and correlation plots.
Analysis of correlation of conformational changes
Analysis of solvation in the interaction surface
To perform the water density analysis, structures were simulated, as previously described, for 5 ns by MD with backbone restraints (1.2 kcal· mol − 1· Å − 2) to avoid any significant conformational changes of the protein during the simulation [11, 27]. Water density maps were calculated at discrete points r defined by a 0.5-Å spaced rectangular grid around the solute. To remove the overall roto-translational motion of the protein the structures of the last 10 ns of the trajectory were superimposed to a reference. From snapshots taken every 0.1 ps, the density of the water oxygen atoms was averaged for each grid point and normalised by the bulk density evaluated in a 6–8 Å shell around the solute. The hydration score S hyd was defined by identifying hydration sites as the local maxima of the density map with g(r) > 1 as previously described . Water density maps were calculated for representative conformations of the Ebola virus VP24-KPNA5 complex as extracted from the trajectory and compared to the solvent distribution for the representative conformations of Ebola virus R137A VP24-KPNA5 and Reston virus VP24-KPNA5 complex trajectories.
A good water model to use as a solvent in biomolecular simulations should be computationally efficient and at the same time reproduce accurately enough the properties of bulk water. Not to be underestimated, this model should be compatible with the force field used for the solute interactions. It is well known that simple effective pair potentials such as SPC, TIP3P and TIP4P are, in different measure, not able to accurately describe the entire range of water properties, nevertheless, they have all proven to successfully model water as a solvent in biomolecular simulations.
The general weakness demonstrated by these models is in the overestimation of the diffusion coefficient and the inaccurate description of the dielectric properties. On the other hand they are effective in the calculation of solute solvent energies and practical to use. In the past we have developed solvent density maps based on the SPC model [30, 31]. We were particularly interested in the water-protein interactions due to the localization of water at the surface of the protein, therefore we used the same model in this application as a matter of consistency with the force field and our previous calculations.
This project was supported by a Microsoft Azure Ebola Research Award to MNW, MM and FF. FC research was founded by Swiss National Science Foundation (SNSF) project P2BEP2_148877. The Article Processing Charge has been paid by the University of Kent.
Availability of data and materials
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
About this supplement
This article has been published as part of BMC Genomics Volume 18 Supplement 5, 2017: Proceedings of VarI-SIG 2016: identification and annotation of genetic variants in the context of structure, function, and disease: Genomics. The full contents of the supplement are available online at https://bmcgenomics.biomedcentral.com/articles/supplements/volume-18-supplement-5.
MNW and FF devised the research. MP, FC and JM performed experiments. MP, FC, JM, MM, FF and MNW analysed data. All authors wrote the manuscript, they have all read and approved the manuscript.
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