Biology subjects

Busch, F.

Publications and source records attributed to Busch, F..

2 recordsLinked to original sources

bioRxiv2021

Accurate and automated high-coverage identification of chemically cross-linked peptides with MaxLynx

Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the 3D structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to non-cleavable and MS-cleavable cross linkers. For both we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For non-cleavable peptides, we implemented a novel di-peptide Andromeda score, which is the basis for a computationally efficient N-squared search engine. Additionally, partial scores summarize the evidence for the two constituents of the di-peptide individually. A posterior error probability based on total and partial scores is used to control false discovery rates. For MS-cleavable cross linkers a scoring of signature peaks is combined with the conventional Andromeda score on the cleavage products. The MaxQuant 3D-peak detection was improved to ensure more accurate determination of the monoisotopic peak of isotope patterns for heavy molecules, which cross-linked peptides typically are. A wide selection of filtering parameters can replace manual filtering of identifications, which is often necessary when using other pipelines. On benchmark datasets of synthetic peptides, MaxLynx outperforms all other tested software on data for both types of cross linkers as well as on a proteome-wide dataset of cross-linked D. melanogaster cell lysate. The workflow also supports ion-mobility enhanced MS data. MaxLynx runs on Windows and Linux, contains an interactive viewer for displaying annotated cross-linked spectra and is freely available at https://www.maxquant.org/.

bioinformatics↗

bioRxiv2020

Generation of ordered protein assemblies using rigid three-body fusion

Protein nanomaterial design is an emerging discipline with applications in medicine and beyond. A longstanding design approach uses genetic fusion to join protein homo-oligomer subunits via -helical linkers to form more complex symmetric assemblies, but this method is hampered by linker flexibility and a dearth of geometric solutions. Here, we describe a general computational method that performs rigid three-body fusion of homo-oligomer and spacer building blocks to generate user-defined architectures, while at the same time significantly increasing the number of geometric solutions over typical symmetric fusion. The fusion junctions are then optimized using Rosetta to minimize flexibility. We apply this method to design and test 92 dihedral symmetric protein assemblies from a set of designed homo-dimers and repeat protein building blocks. Experimental validation by native mass spectrometry, small angle X-ray scattering, and negative-stain single-particle electron microscopy confirms the assembly states for 11 designs. Most of these assemblies are constructed from DARPins (designed ankyrin repeat proteins), anchored on one end by -helical fusion and on the other by a designed homo-dimer interface, and we explored their use for cryo-EM structure determination by incorporating DARPin variants selected to bind targets of interest. Although the target resolution was limited by preferred orientation effects, small scaffold size, and the low-order symmetry of these dihedral scaffolds, we found that the dual anchoring strategy reduced the flexibility of the target-DARPIN complex with respect to the overall assembly, suggesting that multipoint anchoring of binding domains could contribute to cryo-EM structure determination of small proteins.

synthetic biology↗