Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Consensus guidelines for the use and interpretation of angiogenesis assays

The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference

An Imaging and Systems Modeling Approach to Fibril Breakage Enables Prediction of Amyloid Behavior

Delineating the nanoscale properties and the dynamic assembly and disassembly behaviors of amyloid fibrils is key for technological applications that use the material properties of amyloid fibrils, as well as for developing treatments of amyloid-associated disease. However, quantitative mechanistic understanding of the complex processes involving these heterogeneous supramolecular systems presents challenges that have yet to be resolved. Here, we develop an approach that is capable of resolving the time dependence of fibril particle concentration, length distribution, and length and position dependence of fibril fragmentation rates using a generic mathematical framework combined with experimental data derived from atomic force microscopy analysis of fibril length distributions. By application to amyloid assembly of ?2-microglobulin in vitro under constant mechanical stirring, we present a full description of the fibril fragmentation and growth behavior, and demonstrate the predictive power of the approach in terms of the samples’ fibril dimensions, fibril load, and their efficiency to seed the growth of new amyloid fibrils. The approach developed offers opportunities to determine, quantify, and predict the course and the consequences of amyloid assembly