Structural aspects of amyloid formation

Elucidating the inhibitory effects of rationally designed novel hexapeptide against hen egg white lysozyme fibrillation at acidic and physiological pH

Inhibition of highly ordered cross-β-sheet-rich aggregates of misfolded amyloid proteins using rationally designed sequence-based short peptides is a promising therapeutic strategy for the treatment of neurodegenerative diseases. Here, we have explored the anti-amyloidogenic potency of a rationally designed hexapeptide (Tyr-Pro-Gln-Ile-Pro-Asn) on in vitro hen egg white lysozyme (HEWL) amyloid fibril formation at acidic pH and physiological pH using computational docking as well as various biophysical techniques such as fluorescence spectroscopy, UV-vis spectroscopy, FTIR spectroscopy, confocal microscopy and TEM. The peptide was designed based on the aggregation-prone region (APR) of HEWL and thus referred to as SqP1 (Sequence-based Peptide 1). SqP1 showed over 70% inhibition of HEWL amyloid formation at pH 2.2 and approximately 50% inhibition at pH 7.5. We propose that SqP1 binds to the APR of HEWL and interacts strongly with the Trp62/Trp63, ultimately stabilizing monomeric HEWL at both the pH conditions and preventing conformation changes in the structure of HEWL, leading to the formation of amyloidogenic fibrillar structures. A sequence-based peptide inhibitor of HEWL amyloid formation was not reported previously, making this a critical study that will further emphasize the importance of short synthetic peptides as amyloid inhibitors.

Aggregate Size Dependence of Amyloid Adsorption onto Charged Interfaces

Amyloid aggregates are associated with a range of human neurodegenerative disorders, and it has been shown that neurotoxicity is dependent on aggregate size. Combining molecular simulation with analytical theory, a predictive model is proposed for the adsorption of amyloid aggregates onto oppositely charged surfaces, where the interaction is governed by an interplay between electrostatic attraction and entropic repulsion. Predictions are experimentally validated against quartz crystal microbalance-dissipation experiments of amyloid beta peptides and fragmented fibrils in the presence of a supported lipid bilayer. Assuming amyloids as rigid, elongated particles, we observe nonmonotonic trends for the extent of adsorption with respect to aggregate size and preferential adsorption of smaller aggregates over larger ones. Our findings describe a general phenomenon with implications for stiff polyions and rodlike particles that are electrostatically attracted to a surface.

Allosteric modulation of protein oligomerization: an emerging approach to drug design

Many disease-related proteins are in equilibrium between different oligomeric forms. The regulation of this equilibrium plays a central role in maintaining the activity of these proteins in vitro and in vivo. Modulation of the oligomerization equilibrium of proteins by molecules that bind preferentially to a specific oligomeric state is emerging as a potential therapeutic strategy that can be applied to many biological systems such as cancer and viral infections. The target proteins for such compounds are diverse in structure and sequence, and may require different approaches for shifting their oligomerization equilibrium. The discovery of such oligomerization-modulating compounds is thus achieved based on existing structural knowledge about the specific target proteins, as well as on their interactions with partner proteins or with ligands. In silico design and combinatorial tools such as peptide arrays and phage display are also used for discovering compounds that modulate protein oligomerization. The current review highlights some of the recent developments in the design of compounds aimed at modulating the oligomerization equilibrium of proteins, including the "shiftides" approach developed in our lab.

MetAmyl: a METa-predictor for AMYLoid proteins

The aggregation of proteins or peptides in amyloid fibrils is associated with a number of clinical disorders, including Alzheimer's, Huntington's and prion diseases, medullary thyroid cancer, renal and cardiac amyloidosis. Despite extensive studies, the molecular mechanisms underlying the initiation of fibril formation remain largely unknown. Several lines of evidence revealed that short amino-acid segments (hot spots), located in amyloid precursor proteins act as seeds for fibril elongation. Therefore, hot spots are potential targets for diagnostic/therapeutic applications, and a current challenge in bioinformatics is the development of methods to accurately predict hot spots from protein sequences. In this paper, we combined existing methods into a meta-predictor for hot spots prediction, called MetAmyl for METapredictor for AMYLoid proteins. MetAmyl is based on a logistic regression model that aims at weighting predictions from a set of popular algorithms, statistically selected as being the most informative and complementary predictors. We evaluated the performances of MetAmyl through a large scale comparative study based on three independent datasets and thus demonstrated its ability to differentiate between amyloidogenic and non-amyloidogenic polypeptides. Compared to 9 other methods, MetAmyl provides significant improvement in prediction on studied datasets. We further show that MetAmyl is efficient to highlight the effect of point mutations involved in human amyloidosis, so we suggest this program should be a useful complementary tool for the diagnosis of these diseases.