Target Identification and Mode of Action of Four Chemically Divergent Drugs against Ebolavirus Infection

Here, we show that four chemically divergent approved drugs reported to inhibit Ebolavirus infection, benztropine, bepridil, paroxetine and sertraline, directly interact with the Ebolavirus glycoprotein. Binding of these drugs destabilizes the protein, suggesting that this may be the mechanism of inhibition, as reported for the anticancer drug toremifene and the painkiller ibuprofen, which bind in the same large cavity on the glycoprotein. Crystal structures show that the position of binding and the mode of interaction within the pocket vary significantly between these compounds. The binding constants (<i>K</i>_d) determined by thermal shift assay correlate with the protein–inhibitor interactions as well as with the antiviral activities determined by virus cell entry assays, supporting the hypothesis that these drugs inhibit viral entry by binding the glycoprotein and destabilizing the prefusion conformation. Details of the protein–inhibitor interactions of these complexes and their relation with binding affinity may facilitate the design of more potent inhibitors

Plots of the the precision and accuracy of each program (a–e) and a consensus of any two or all three of the top three methods at identifying the known epitopes for each serotype with a structure available.

<p>Plots of the the precision and accuracy of each program (a–e) and a consensus of any two or all three of the top three methods at identifying the known epitopes for each serotype with a structure available.</p

Interval plot showing the mean probability excess (and confidence intervals) of each program and a consensus of any two or all three of the top three methods.

<p>Interval plot showing the mean probability excess (and confidence intervals) of each program and a consensus of any two or all three of the top three methods.</p

Evaluation and Use of <i>In-Silico</i> Structure-Based Epitope Prediction with Foot-and-Mouth Disease Virus

<div><p>Understanding virus antigenicity is of fundamental importance for the development of better, more cross-reactive vaccines. However, as far as we are aware, no systematic work has yet been conducted using the 3D structure of a virus to identify novel epitopes. Therefore we have extended several existing structural prediction algorithms to build a method for identifying epitopes on the appropriate outer surface of intact virus capsids (which are structurally different from globular proteins in both shape and arrangement of multiple repeated elements) and applied it here as a proof of principle concept to the capsid of foot-and-mouth disease virus (FMDV). We have analysed how reliably several freely available structure-based B cell epitope prediction programs can identify already known viral epitopes of FMDV in the context of the viral capsid. To do this we constructed a simple objective metric to measure the sensitivity and discrimination of such algorithms. After optimising the parameters for five methods using an independent training set we used this measure to evaluate the methods. Individually any one algorithm performed rather poorly (three performing better than the other two) suggesting that there may be value in developing virus-specific software. Taking a very conservative approach requiring a consensus between all three top methods predicts a number of previously described antigenic residues as potential epitopes on more than one serotype of FMDV, consistent with experimental results. The consensus results identified novel residues as potential epitopes on more than one serotype. These include residues 190–192 of VP2 (not previously determined to be antigenic), residues 69–71 and 193–197 of VP3 spanning the pentamer-pentamer interface, and another region incorporating residues 83, 84 and 169–174 of VP1 (all only previously experimentally defined on serotype A). The computer programs needed to create a semi-automated procedure for carrying out this epitope prediction method are presented.</p></div

Graph showing the number of known epitopes for each serotype identified by each program compared to the total number of known epitopes for each serotype.

<p>Graph showing the number of known epitopes for each serotype identified by each program compared to the total number of known epitopes for each serotype.</p

List of residues selected by a consensus of the three best performing programs (Discotope, Ellipro and Epitopia) for each selected FMDV structure compared to locations of known antigenic sites of all serotypes.

<p>Those residues coloured red are an already known epitope on at least one serotype of FMDV, those in blue are adjacent to a known epitope of FMDV. Regions A–G are predicted to be antigenic on the majority of the serotypes tested and are coloured the same on <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061122#pone-0061122-g008" target="_blank">Figures 8</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061122#pone-0061122-g009" target="_blank">9</a>. The remaining residues are coloured grey, as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061122#pone-0061122-g008" target="_blank">Figures 8</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0061122#pone-0061122-g009" target="_blank">9</a>. Note that the SAT-1 virus VP1 has a incorporated several additional residues into the G–H loop and the A serotype also aligns slightly differently to the O and C structures, therefore the numbering is different in region C as they are aligned according to position on structure. All other residues are in approximately the same location relative to each other.</p

Structures of Ebola Virus Glycoprotein Complexes with Tricyclic Antidepressant and Antipsychotic Drugs

A large number of Food and Drug Administration (FDA)-approved drugs have been found to inhibit the cell entry of Ebola virus (EBOV). However, since these drugs have various primary pharmacological targets, their mechanisms of action against EBOV remain largely unknown. We have previously shown that six FDA-approved drugs inhibit EBOV infection by interacting with and destabilizing the viral glycoprotein (GP). Here we show that antidepressants imipramine and clomipramine and antipsychotic drug thioridazine also directly interact with EBOV GP and determine the mode of interaction by crystallographic analysis of the complexes. The compounds bind within the same pocket as observed for other, chemically divergent complexes but with different binding modes. These details should be of value for the development of potent EBOV inhibitors

Structures of Ebola Virus Glycoprotein Complexes with Tricyclic Antidepressant and Antipsychotic Drugs

A large number of Food and Drug Administration (FDA)-approved drugs have been found to inhibit the cell entry of Ebola virus (EBOV). However, since these drugs have various primary pharmacological targets, their mechanisms of action against EBOV remain largely unknown. We have previously shown that six FDA-approved drugs inhibit EBOV infection by interacting with and destabilizing the viral glycoprotein (GP). Here we show that antidepressants imipramine and clomipramine and antipsychotic drug thioridazine also directly interact with EBOV GP and determine the mode of interaction by crystallographic analysis of the complexes. The compounds bind within the same pocket as observed for other, chemically divergent complexes but with different binding modes. These details should be of value for the development of potent EBOV inhibitors

Venn diagrams showing the regognition of residues by each program for FMDV serotype O1K-Reduced (a), O1K (b), A1061 (c), SAT-1 (d) and Cs8 c1 (e).

<p>The key on the far right hand side indicates the colour of each program as represented on the Venn Diagram. For clarity the two worst perfoming algorithms are not coloured. In regions of overalap the colour is represented as the sum of the RGB colour channels of the overlapping mathods Diagrams made using the Venn master program (Kestler et al., 2008). Note that formally there need be no perfect projection of the multi-dimensional overlap information into the Venn diagram, so these represent best approximations.</p

Sensitivity and specificity results for polio and rhinovirus at the optimum threshold value for scoring a residue an epitope (the default given by the developers is also shown for comparison).

<p>Sensitivity and specificity results for polio and rhinovirus at the optimum threshold value for scoring a residue an epitope (the default given by the developers is also shown for comparison).</p