Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign.

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For over two decades, peptide self-assembly has been the focus of attention and a great source of inspiration for biomedical and nanotechnological applications. The resulting peptide nanostructures and their properties are closely related to the information encoded within each peptide building block, their sequence, and their modes of self-organization. In this work. we assess the behavior and differences between the self-association of the aromatic−aliphatic Phe-Leu dipeptide compared to its retrosequence Leu-Phe and cyclic Cyclo(-Leu-Phe) counterparts, using a combination of simulation and experimental methods. Detailed all-atom molecular dynamics (MD) simulations offer a quantitative prediction at the molecular level of the conformational, dynamical and structural properties of the peptides' self-assembly, while field emission scanning electron microscopy (FESEM) experiments allow microscopic observation of the self-assembled end-structures. The complementarity and qualitative agreement between the two methods not only highlights the differences between the self-assembly propensity of cyclic and linear retro-sequence peptides but also sheds light on underlying mechanisms of self-organization. The self-assembling propensity was found to follow the order: Cyclo(-Leu-Phe) > Leu-Phe > Phe-Leu.