The purpose of this work was to construct a consensus prediction algorithm of ‘aggregation-prone’ peptides in globular proteins, combining existing tools. This allows comparison of the different algorithms and the production of more objective and accurate results. Eleven (11) individual methods are combined and produce AMYLPRED2, a publicly, freely available web tool to academic users (http://biophysics.biol.uoa.gr/AMYLPRED2), for the consensus prediction of amyloidogenic determinants/‘aggregation-prone’ peptides in proteins, from sequence alone. The performance of AMYLPRED2 indicates that it functions better than individual aggregation-prediction algorithms, as perhaps expected. AMYLPRED2 is a useful tool for identifying amyloid-forming regions in proteins that are associated with several conformational diseases, called amyloidoses, such as Altzheimer's, Parkinson's, prion diseases and type II diabetes. It may also be useful for understanding the properties of protein folding and misfolding and for helping to the control of protein aggregation/solubility in biotechnology (recombinant proteins forming bacterial inclusion bodies) and biotherapeutics (monoclonal antibodies and biopharmaceutical proteins).

Background: Amyloidoses are a group of usually fatal diseases, probably caused by protein misfolding and subsequent aggregation into amyloid fibrillar deposits. The mechanisms involved in amyloid fibril formation are largely unknown and are the subject of current, intensive research. In an attempt to identify possible amyloidogenic regions in proteins for further experimental investigation, we have developed and present here a publicly available online tool that utilizes five different and independently published methods, to form a consensus prediction of amyloidogenic regions in proteins, using only protein primary structure data.

Chorion is the major component of silkmoth eggshell. More than 95% of its dry mass consists of proteins that have remarkable mechanical and chemical properties protecting the oocyte and the developing embryo from a wide range of environmental hazards. We present data from electron microscopy (negative staining and shadowing), X-ray diffraction and modeling studies of synthetic peptide analogues of silkmoth chorion proteins indicating that chorion is a natural amyloid. The folding and self-assembly models of chorion peptides strongly support the L L-sheet helix model of amyloid fibrils proposed recently by Blake and Serpell [Structure 4 (1996) 9899 98]. ß

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Amyloidoses are a group of diseases including neurodegenerative diseases like Alzheimer's disease and also type II diabetes, spongiform encephalopathies and many others, believed to be caused by protein aggregation and subsequent amyloid fibril formation. However, occasionally, living organisms exploit amyloid fibril formation, a property inherent into amino acid sequences, and perform specific physiological functions from amyloids, in differing biological contexts. Some of these functional amyloids are natural protective amyloids. Here, we review recent evidence on silkmoth chorion protein synthetic peptide-analogues that documents the function of silkmoth chorion, the major component of the eggshell, a structure with extraordinary physiological and mechanical properties, as a natural protective amyloid. Also, we briefly discuss the reported function of other natural, protective amyloids like fish chorion, the protein Pmel17 which forms amyloid fibrils that act as templates and accelerate the covalent polymerization of reactive small molecules into melanin, the hydrophobins and the antifreeze protein from winter flounder. Molecular self-assembly is becoming an increasingly popular route to new supramolecular structures and molecular materials and the inspiration for such structures is commonly derived from self-assembling systems in biology. Therefore, a careful examination of these studies may set the basis for the exploration of new routes for the formation of novel biocompatible polymeric structures with exceptional physico-chemical properties, for potentially new biomedical and industrial applications.

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