Lessons from molecular modeling human α-L-iduronidase.

Human α-L-iduronidase (IDUA) is a member of glycoside hydrolase family and is involved in the catabolism of glycosaminoglycans (GAGs), heparan sulfate (HS) and dermatan sulfate (DS). Mutations in this enzyme are responsible for mucopolysaccharidosis I (MPS I), an inherited lysosomal storage disorder. Despite great interest in determining and studying this enzyme structure, the lack of a high identity to templates and other technical issues have challenged both bioinformaticians and crystallographers, until the recent publication of an IDUA crystal structure (PDB: 4JXP). In the present work, four alternative IDUA models, generated and evaluated prior to crystallographic determination, were compared to the 4JXP structure. A combined analysis using several viability assessment tools and molecular dynamics simulations highlights the strengths and limitations of different comparative modeling protocols, all of which are based on the same low identity template (only 22%). Incorrect alignment between the target and template was confirmed to be a major bottleneck in homology modeling, regardless of the modeling software used. Moreover, secondary structure analysis during a 50ns simulation seems to be useful for indicating alignment errors and structural instabilities. The best model was achieved through the combined use of Phyre 2 and Modeller, suggesting the use of this protocol for the modeling of other proteins that still lack high identity templates.

Structural in silico analysis of cross-genotype-reactivity among naturally occurring HCV NS3-1073-variants in the context of HLA-A*02:01 allele.

Cellular immune response plays a central role in outcome of Hepatitis C Virus (HCV) infection. While specific T-cell responses are related to viral clearance, impaired responses can lead to chronic infection, turning HCV variability into a major obstacle for vaccine development. In a recent work, Fytili et al. (2008) studied the cross reactive potential of HCV specific CD8+ T-cells and observed a large variation in immunogenicity among 28 naturally occurring NS3(1073) variants. In this work, we intend to evaluate this immunogenic variation at molecular level, through bioinformatics approaches. The D1-EM-D2 strategy was used to build in silico MHC:peptide complexes (pMHC) of these HCV-derived peptides in the context of HLA-A*02:01 allele. The TCR-interacting surface of these complexes were evaluated using the GRASP2 program. Structural analysis indicated a sharing of topological and electrostatic features among complexes that induced strong response in vitro. Besides, complexes that induced low response presented an important positively charged spot in the center of TCR-interacting area. This spot was seen even in complexes with conservative amino acid changes and is consistent with the impairment of recognition by wild-type-specific T-cells, observed in vitro. Furthermore, the most remarkable difference in electrostatic potential was seen precisely in the only complex unable to induce in vitro stimulation. All these observations were confirmed by Principal Component Analysis (PCA) and this approach was also applied to a set of 45 non-related immunogenic viral epitopes, indicating possible new targets for cross-reactivity studies. Our results suggest structural in silico analysis of pMHC complexes as a reliable tool for vaccine development, affording to predict the impact of viral escape mutations and selection of epitopes with potential to induce cross-reactive immune responses.