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Evaluation and use of in-silico structure-based epitope prediction with foot-and-mouth disease virus.

Borley DW, Mahapatra M, Paton DJ, Esnouf RM, Stuart DI, Fry EE - PLoS ONE (2013)

Bottom Line: 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.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).

View Article: PubMed Central - PubMed

Affiliation: The Pirbright Institute, Pirbright, United Kingdom. daryl.borley@pirbright.ac.uk

ABSTRACT
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.

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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).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.
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pone-0061122-g006: 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).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.

Mentions: Although the programs utilise different algorithms there was considerable overlap in the residues identified, and there were epitopes on each serotype that were not identified by any of the programs (Figure 4). This suggests that although the programs utilise different algorithms for identifying epitopes they are not fully independent in terms of the outputs (this is seen graphically in Figure 6).


Evaluation and use of in-silico structure-based epitope prediction with foot-and-mouth disease virus.

Borley DW, Mahapatra M, Paton DJ, Esnouf RM, Stuart DI, Fry EE - PLoS ONE (2013)

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).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.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3646828&req=5

pone-0061122-g006: 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).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.
Mentions: Although the programs utilise different algorithms there was considerable overlap in the residues identified, and there were epitopes on each serotype that were not identified by any of the programs (Figure 4). This suggests that although the programs utilise different algorithms for identifying epitopes they are not fully independent in terms of the outputs (this is seen graphically in Figure 6).

Bottom Line: 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.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).

View Article: PubMed Central - PubMed

Affiliation: The Pirbright Institute, Pirbright, United Kingdom. daryl.borley@pirbright.ac.uk

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus