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International audience; BACKGROUND: The availability of the P. falciparum genome has led to novel ways to identify potential vaccine candidates. A new approach for antigen discovery based on the bioinformatic selection of heptad repeat motifs corresponding to alpha-helical coiled coil structures yielded promising results. To elucidate the question about the relationship between the coiled coil motifs and their sequence conservation, we have assessed the extent of polymorphism in putative alpha-helical coiled coil domains in culture strains, in natural populations and in the single nucleotide polymorphism data available at PlasmoDB. METHODOLOGY/PRINCIPAL FINDINGS: 14 alpha-helical coiled coil domains were selected based on preclinical experimental evaluation. They were tested by PCR amplification and sequencing of different P. falciparum culture strains and field isolates. We found that only 3 out of 14 alpha-helical coiled coils showed point mutations and/or length polymorphisms. Based on promising immunological results 5 of these peptides were selected for further analysis. Direct sequencing of field samples from Papua New Guinea and Tanzania showed that 3 out of these 5 peptides were completely conserved. An in silico analysis of polymorphism was performed for all 166 putative alpha-helical coiled coil domains originally identified in the P. falciparum genome. We found that 82% (137/166) of these peptides were conserved, and for one peptide only the detected SNPs decreased substantially the probability score for alpha-helical coiled coil formation. More SNPs were found in arrays of almost perfect tandem repeats. In summary, the coiled coil structure prediction was rarely modified by SNPs. The analysis revealed a number of peptides with strictly conserved alpha-helical coiled coil motifs. CONCLUSION/SIGNIFICANCE: We conclude that the selection of alpha-helical coiled coil structural motifs is a valuable approach to identify potential vaccine targets showing a high degree of conservation.

BACKGROUND: Integrase (IN) of the type 1 human immunodeficiency virus (HIV-1) catalyzes the integration of viral DNA into host cellular DNA. We identified a bi-helix motif (residues 149-186) in the crystal structure of the catalytic core (CC) of the IN-Phe185Lys variant that consists of the alpha(4) and alpha(5) helices connected by a 3 to 5-residue turn. The motif is embedded in a large array of interactions that stabilize the monomer and the dimer. PRINCIPAL FINDINGS: We describe the conformational and binding properties of the corresponding synthetic peptide. This displays features of the protein motif structure thanks to the mutual intramolecular interactions of the alpha(4) and alpha(5) helices that maintain the fold. The main properties are the binding to: 1- the processing-attachment site at the LTR (long terminal repeat) ends of virus DNA with a K(d) (dissociation constant) in the sub-micromolar range; 2- the whole IN enzyme; and 3- the IN binding domain (IBD) but not the IBD-Asp366Asn variant of LEDGF (lens epidermal derived growth factor) lacking the essential Asp366 residue. In our motif, in contrast to the conventional HTH (helix-turn-helix), it is the N terminal helix (alpha(4)) which has the role of DNA recognition helix, while the C terminal helix (alpha(5)) would rather contribute to the motif stabilization by interactions with the alpha(4) helix. CONCLUSION: The motif, termed HTHi (i, for inverted) emerges as a central piece of the IN structure and function. It could therefore represent an attractive target in the search for inhibitors working at the DNA-IN, IN-IN and IN-LEDGF interfaces.

Formation of amyloid-like fibrils is involved in numerous human protein deposition diseases, but is also an intrinsic property of polypeptide chains in general. Progress achieved recently now allows the aggregation propensity of proteins to be analyzed over large scales. In this work we used a previously developed predictive algorithm to analyze the propensity of the 34,180 protein sequences of the human proteome to form amyloid-like fibrils. We show that long proteins have, on average, less intense aggregation peaks than short ones. Human proteins involved in protein deposition diseases do not differ extensively from the rest of the proteome, further demonstrating the generality of protein aggregation. We were also able to reproduce some of the results obtained with other algorithms, demonstrating that they do not depend on the type of computational tool employed. For example, proteins with different subcellular localizations were found to have different aggregation propensities, in relation to the various efficiencies of quality control mechanisms. Membrane proteins, intrinsically disordered proteins, and folded proteins were confirmed to have very different aggregation propensities, as a consequence of their different structures and cellular microenvironments. In addition, gatekeeper residues at strategic positions of the sequences were found to protect human proteins from aggregation. The results of these comparative analyses highlight the existence of intimate links between the propensity of proteins to form aggregates with β-structure and their biology. In particular, they emphasize the existence of a negative selection pressure that finely modulates protein sequences in order to adapt their aggregation propensity to their biological context., Author Summary Amyloid-like fibrils are insoluble proteinaceous fibrillar aggregates with a characteristic structure (the cross-β core) that form and deposit in more than 40 pathological conditions in humans. These include Alzheimer's disease, Parkinson's disease, type II diabetes, and the spongiform encephalopathies. A number of proteins not involved in any disease can also form amyloid-like fibrils in vitro, suggesting that amyloid fibril formation is an intrinsic property of proteins in general. Recent efforts in understanding the physico-chemical grounds of amyloid fibril formation has led to the development of several algorithms, capable of predicting a number of aggregation-related parameters of a protein directly from its amino acid sequence. In order to study the predicted aggregation behavior of the human proteome, we have run one of these algorithms on the 34,180 human protein sequences. Our results demonstrate that molecular evolution has acted on protein sequences to finely modulate their aggregation propensities, depending on different parameters related to their in vivo environment. Together with cellular control mechanisms, this natural selection protects proteins from aggregation during their lifetime.