The self-assembly of α-synuclein is closely associated with Parkinson’s disease and related syndromes. We show that squalamine, a natural product with known anticancer and antiviral activity, dramatically affects α-synuclein aggregation in vitro and in vivo. We elucidate the mechanism of action of squalamine by investigating its interaction with lipid vesicles, which are known to stimulate nucleation, and find that this compound displaces α-synuclein from the surfaces of such vesicles, thereby blocking the first steps in its aggregation process. We also show that squalamine almost completely suppresses the toxicity of α-synuclein oligomers in human neuroblastoma cells by inhibiting their interactions with lipid membranes. We further examine the effects of squalamine in a Caenorhabditis elegans strain overexpressing α-synuclein, observing a dramatic reduction of α-synuclein aggregation and an almost complete elimination of muscle paralysis. These findings suggest that squalamine could be a means of therapeutic intervention in Parkinson’s disease and related conditions. Significance Parkinson’s disease is characterized by the presence in brain tissues of aberrant aggregates primarily formed by the protein α-synuclein. It has been difficult, however, to identify compounds capable of preventing the formation of such deposits because of the complexity of the aggregation process of α-synuclein. By exploiting recently developed highly quantitative in vitro assays, we identify a compound, squalamine, that blocks α-synuclein aggregation, and characterize its mode of action. Our results show that squalamine, by competing with α-synuclein for binding lipid membranes, specifically inhibits the initiation of the aggregation process of α-synuclein and abolishes the toxicity of α-synuclein oligomers in neuronal cells and in an animal model of Parkinson’s disease.

Antibodies play essential roles in the immune system of vertebrates and are powerful tools in research and diagnostics. While hypervariable regions of antibodies, which are responsible for binding, can be readily identified from their amino acid sequence, it remains challenging to accurately pinpoint which amino acids will be in contact with the antigen (the paratope). In this work, we present a sequence-based probabilistic machine learning algorithm for paratope prediction, named Parapred. Parapred uses a deep-learning architecture to leverage features from both local residue neighbourhoods and across the entire sequence. The method significantly improves on the current state-of-the-art methodology, and only requires a stretch of amino acid sequence corresponding to a hypervariable region as an input, without any information about the antigen. We further show that our predictions can be used to improve both speed and accuracy of a rigid docking algorithm. The Parapred method is freely available as a webserver at http://www-mvsoftware.ch.cam.ac.uk/and for download at https://github.com/eliberis/parapred. el398@cam.ac.uk (E. L.), ps589@cam.ac.uk (P. S.) Supplementary information is available at Bioinformatics online.

Protein aggregation is a complex process resulting in the formation of heterogeneous mixtures of aggregate populations that are closely linked to neurodegenerative conditions, such as Alzheimer’s disease. Here, we find that soluble aggregates formed at different stages of the aggregation process of amyloid beta (Aβ42) induce the disruption of lipid bilayers and an inflammatory response to different extents. Further, by using gradient ultracentrifugation assay, we show that the smaller aggregates are those most potent at inducing membrane permeability and most effectively inhibited by antibodies binding to the C-terminal region of Aβ42. By contrast, we find that the larger soluble aggregates are those most effective at causing an inflammatory response in microglia cells and more effectively inhibited by antibodies targeting the N-terminal region of Aβ42. These findings suggest that different toxic mechanisms driven by different soluble aggregated species of Aβ42 may contribute to the onset and progression of Alzheimer’s disease.

The MobiDB (URL: mobidb.bio.unipd.it) database of protein disorder and mobility annotations has been significantly updated and upgraded since its last major renewal in 2014. Several curated datasets for intrinsic disorder and folding upon binding have been integrated from specialized databases. The indirect evidence has also been expanded to better capture information available in the PDB, such as high temperature residues in X-ray structures and overall conformational diversity. Novel nuclear magnetic resonance chemical shift data provides an additional experimental information layer on conformational dynamics. Predictions have been expanded to provide new types of annotation on backbone rigidity, secondary structure preference and disordered binding regions. MobiDB 3.0 contains information for the complete UniProt protein set and synchronization has been improved by covering all UniParc sequences. An advanced search function allows the creation of a wide array of custom-made datasets for download and further analysis. A large amount of information and cross-links to more specialized databases are intended to make MobiDB the central resource for the scientific community working on protein intrinsic disorder and mobility.

To function effectively proteins must avoid aberrant aggregation, and hence they are expected to be expressed at concentrations safely below their solubility limits. By analyzing proteome-wide mass spectrometry data of Caenorhabditis elegans, however, we show that the levels of about three-quarters of the nearly 4,000 proteins analyzed in adult animals are close to their intrinsic solubility limits, indeed exceeding them by about 10% on average. We next asked how aging and functional self-assembly influence these solubility limits. We found that despite the fact that the total quantity of proteins within the cellular environment remains approximately constant during aging, protein aggregation sharply increases between days 6 and 12 of adulthood, after the worms have reproduced, as individual proteins lose their stoichiometric balances and the cellular machinery that maintains solubility undergoes functional decline. These findings reveal that these proteins are highly prone to undergoing concentration-dependent phase separation, which on aging is rationalized in a decrease of their effective solubilities, in particular for proteins associated with translation, growth, reproduction, and the chaperone system. Significance More than a decade ago, we put forward the “life on the edge of solubility” hypothesis, according to which proteins are expressed in the cellular environment at levels close to their solubility limits. This observation was based on the analysis of a small number of proteins for which solubility and cellular concentration information was available at the time. To confirm this hypothesis we have now taken advantage of recent advances in mass spectrometry that have enabled the proteome-wide analysis of protein concentrations in both the soluble and insoluble forms. We have been able to show in this way that the vast majority of proteins in a model organism are indeed expressed above their solubility limits, and to investigate the consequences of this phenomenon.