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Pujols, J.

Publications and source records attributed to Pujols, J..

2 recordsLinked to original sources

α-Helical peptidic scaffolds to target α-synuclein pathogenic species with high affinity and selectivity.

-Synuclein aggregation is a key driver of neurodegeneration in Parkinsons disease and related syndromes. Accordingly, obtaining a molecule that targets -synuclein pathogenic assemblies with high affinity and selectivity is a long-pursued objective. Here, we have exploited the biophysical properties of toxic oligomers and amyloid fibrils to identify a family of -helical peptides that bind selectively to these -synuclein species with low nanomolar affinity, without interfering with the monomeric functional protein. This activity is translated into an unprecedented anti-aggregation potency and the ability to abrogate the oligomers toxicity. With a structure-function relationship in hand, we identified a human peptide expressed in the brain and in the gastrointestinal tract with exceptional binding, antiaggregation, and detoxifying properties, which suggests it might play a protective role against synucleinopathies. The chemical entities we describe here represent a new therapeutic paradigm and are promising tools to assist diagnosis by selectively detecting -synuclein pathogenic species in biofluids.

biophysics

Protocols for rational design of protein solubility and aggregation properties using Aggrescan3D standalone

Protein aggregation is a major hurdle in the development and manufacturing of protein-based therapeutics. Development of aggregation-resistant and stable protein variants can be guided by rational redesign using computational tools. Here, we describe the architecture and functionalities of the Aggrescan3D (A3D) standalone package for the rational design of protein solubility and aggregation properties based on three-dimensional protein structures. We present the case studies of the three therapeutic proteins, including antibodies, exploring the practical use of the A3D standalone tool. The case studies demonstrate that protein solubility can be easily improved by the A3D prediction of non-destabilizing amino acid mutations at the protein surfaces.

bioinformatics