MOTIVATION: The FoldX force field was originally validated with a database of 1000 mutants at a time when there were few high-resolution structures. Here, we have manually curated a database of 5556 mutants affecting protein stability, resulting in 2484 highly confident mutations denominated FoldX stability dataset (FSD), represented in non-redundant X-ray structures with <2.5 Å resolution, not involving duplicates, metals, or prosthetic groups. Using this database, we have created a new version of the FoldX force field by introducing pi stacking, pH dependency for all charged residues, improving aromatic-aromatic interactions, modifying the Ncap contribution and α-helix dipole, recalibrating the side-chain entropy of methionine, adjusting the H-bond parameters, and modifying the solvation contribution of tryptophan and others. RESULTS: These changes have led to significant improvements for the prediction of specific mutants involving the above residues/interactions and a statistically significant increase of FoldX predictions, as well as for the majority of the 20 aa. Removing all training sets data from FSD [Validation FoldX Stability Dataset (VFSD) dataset] resulted in improved predictions from R = 0.693 (RMSE = 1.277 kcal/mol) to R = 0.706 (RMSE = 1.252 kcal/mol) when compared with the previously released version. FoldX achieves 95% accuracy considering an error of ±0.85 kcal/mol in prediction and an area under the curve = 0.78 for the VFSD, predicting the sign of the energy change upon mutation. AVAILABILITY AND IMPLEMENTATION: FoldX versions 4.1 and 5.1 are freely available for academics at https://foldxsuite.crg.eu/.

SUMMARY: Amyloid polymorphism is emerging as a key property that is differentially linked to various conformational diseases, including major neurodegenerative disorders, but also as a feature that potentially relates to complex structural mechanisms mediating transmissibility barriers and selective vulnerability of amyloids. In response to the rapidly expanding number of amyloid fibril structures formed by full-length proteins, we here have developed StAmP-DB, a public database that supports the curation and cross-comparison of experimentally determined three-dimensional amyloid polymorph structures. AVAILABILITY AND IMPLEMENTATION: StAmP-DB is freely accessible for queries and downloads at https://stamp.switchlab.org.

Abstract Motivation: Protein aggregation is associated with a number of protein misfolding diseases and is a major concern for therapeutic proteins. Aggregation is caused by the presence of aggregation-prone regions (APRs) in the amino acid sequence of the protein. The lower the aggregation propensity of APRs and the better they are protected by native interactions within the folded structure of the protein, the more aggregation is prevented. Therefore, both the local thermodynamic stability of APRs in the native structure and their intrinsic aggregation propensity are a key parameter that needs to be optimized to prevent protein aggregation. Results: The Solubis method presented here automates the process of carefully selecting point mutations that minimize the intrinsic aggregation propensity while improving local protein stability. Availability and implementation: All information about the Solubis plugin is available at http://solubisyasara.switchlab.org/. Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.