Availability of supporting data

 

 

"The data set(s) supporting the results of this article is (are) included within the article (and its additional file(s)" (Table 1).

These data served to justify our choice of strain-type variants of the study viral glycoproteins within the same species of virus. CD may be viewed as functional protein motifs, which by virtue of their inter-network molecules within a network assume evolutionary patterns of hub-proteins. Therefore as pathogens evolve (presumably across strains in the same species), the CD are maintained to sustain their functionality. Further, because CDs are functional motifs which must interact with ligands in the network, the same are often located on the surface, thereby explaining the confounding between CD and epitope (Geer et al., 2002; Marchler-Bauer et al., 2011). The multiple protein-domain conservation architecture (MPDCA) revealed that, on the other hand, may or may not be functional motifs as is elucidated by prior studies and further evidence provided. Nonetheless, it appears that the same MPDCA are under pressure from other interaction within the network; be they functional or structural (proxy).

 

MPDCA among the case-study viral glycoproteins

 

Six (6) MPDAs with more than six amino acids (Aa) length and 100% identity were unveiled in each of the case-study glycoprotein groups, HIV-1 gp120 and EBOV gp1,2. The respective details of these findings are shown by different color shades in supporting files S10 and S11 (Table 1). Fraser et al. (2002) previously found that the connectivity of well-conserved proteins in the network is negatively correlated with their rate of evolution. Overall, this group showed that proteins with more interactions evolve more slowly not because they are more important to the organism, but because a greater proportion of the protein is directly involved in its function. In contrast to this claim that proteins with more interaction partners (sometimes called hubs) are- owing to an assumed high density of binding sites, both physiologically more important and slow evolving; Batada et al. (2006) found that hub proteins are indeed more important for cellular growth rate and are under tight regulation but are not slow evolving. These studies suggest that at sites important for interaction between proteins (such as the MPDCA which were studied), evolutionary changes occur largely by coevolution, in which substitutions in one protein result in selection pressure for reciprocal changes in interacting partners. He argued that, in the same manner as evolutionary changes in the B cell paratrope could potentially influence epitope architecture, MPDCA may be under pressure from their indeterminate interactions. Such analogy to hub proteins with regards to the conservation patterns of protein domains is, however, debatable. Specifically, the primary reason for conservation of sequence across a domain is preservation of the domain fold and secondary structure elements (internal interactions). Conservation of active site residues and structure, and conservation of binding regions contribute to local sequence conservation (that is, within the same functional sub-family). Also, the assumption of a co-evolutionary model may not be universal, since this will only occur when the domain interacts with another protein (or DNA/RNA segment). However, most domain function (enzymes, signalling) involve interactions with small molecules which do not "evolve". Also, protein domains occur in proteins throughout the cell, and are not predominantly associated with cell walls or membranes (Huang and Honda, 2006; Korber et al., 2006; Emini et al., 1985; Chou and Fasman, 1978; Haste Andersen et al., 2006; Karplus and Schulz, 1985; Kolaskar and Tongaonkar, 1990; Larsen et al., 2006; Parker et al. 1986; Zhang et al., 2008; Sievers et al., 2011; Geer et al., 2002; Marchler-Bauer et al., 2011; Fraser  et al., 2002; Batada et al., 2006; Altschul et al., 1997; Labrosse et al., 2006; Bruce et al., 1993; Liu et al., 2009; Sanchez et al., 1993; Sanchez et al., 2004; Sanchez et al., 1996).

 

B cell epitopes within the case-study viral glycoproteins

 

We uncovered both linear and non-linear B cell epitopes in all case-study viral glycoproteins as is further detailed below.

 

Linear B cell epitopes prediction by bepipred

 

Several linear B cell epitopes were unveiled in all case-study viral glycoproteins that are shown further in supporting files S12, S13, S14, S15, S16 and S17  (Table 1).

 

Non-linear B cell epitopes prediction by discotope

 

The conformational B cell epitopes unveiled across the case- study viral glycoproteins are shown further in supporting files S18 and S19 (Table 1), respectively for HIV-1 and EBOV.

 

Correlation of MPDCA and predicted epitope among the case-study viral glycoproteins

 

The author observed an arbitrarily non-deterministic confounding of MPDCA with linear B cell epitope (LC); but no definitive correlation with discontinuous epitope (DE). Specifically, 4/6 (66.6%) of the linear epitopes confounded MPDCA, with 3/6 (50%) of these MPDCA’s confounding with the predicted linear epitopes (LE) at identities of > 50% (Tables 1 and 2) when compared to just 3/6 (50%) of the discontinuous epitopes (DE) that confounded with MPDCA at a < 50% identity (Tables 2 and 3). There are several weaknesses in our approach and findings. Since this was only a first-step in proof of concept, and the small sample size used (there are over 100,000 sequences for HIV GP120) could not allow for derivation of variation coefficients, he argued that further expanded work is sought in this direction to better inform the performance of MPDCA. Further, the methods to which he compare the performance of MPDCA as a predictor of B cell epitope, have variable precision and are not necessary the best (Emini et al., 1985; Chou and Fasman, 1978; Haste Andersen et al., 2006; Karplus and Schulz, 1985; Kolaskar and Tongaonkar, 1990; Larsen et al., 2006; Parker et al. 1986; Zhang et al., 2008). Certainly in the case of the linear predictor the false positive prediction rate is very high making it unusable as a benchmark (no false negative rate given, because not much could be determined as this stage).

 

 

 

Overall, these data show that MPDCA is a non-deterministic confounder of linear B cell epitope. Moreover, there appears to be no causal relationship between the two, much as there is an evident co-occurrence. Therefore, MPDCA cannot accurately be used as an additional parameter to predict linear and or non-linear B cell epitopes. The only possible applicability of MPDCA in epitope discovery is that of rapidly scanning across proteins to see areas that may be potentially epitopic. More important to note outside of our findings is that MPDCA cannot predict antigenicity or immunogenicity. Further, another major shortcoming with using MPDCA to predict linear epitopy, is that MPDCA have the potential to interact with other players in the network, a behavior that might mask or even conceal their architecture in-vivo, making them inappropriate vaccine or diagnostic targets.