Biology subjects

Cavadini, S.

Publications and source records attributed to Cavadini, S..

4 recordsLinked to original sources

bioRxiv2023

Massively parallel mapping of substrate cleavage sites defines dipeptidyl peptidase four subsite cooperativity

Substrate specificity determines protease functions in physiology and in clinical and biotechnological application, yet quantitative cleavage information is often unavailable, biased, or limited to a small number of events. Here, we develop qPISA (quantitative Protease specificity Inference from Substrate Analysis) to study Dipeptidyl Peptidase Four (DPP4), a key regulator of blood glucose levels. We use mass spectrometry to quantify its effects on >40,000 peptides from a complex, commercially available peptide mixture. By determining substrate turnover instead of focusing on product identification, we can reveal cooperative interactions within DPP4s active pocket and derive a sequence motif that predicts activity quantitatively. qPISA distinguishes DPP4 from the related C. elegans DPF-3 (a DPP8/9 orthologue), and we relate the differences to structural features of the two enzymes. We demonstrate that qPISA can direct protein engineering efforts like stabilization of GLP-1, a key DPP4 substrate used in treatment of diabetes and obesity. Thus, qPISA offers a versatile approach for profiling protease and especially exopeptidase specificity, facilitating insight into enzyme mechanisms and biotechnological and clinical applications.

biochemistry↗

bioRxiv2023

The genetic architecture of protein interaction affinity and specificity

Proteins function in crowded cellular environments in which they must bind to specific target proteins but also avoid binding to many other off-target proteins. In large protein families this task is particularly challenging because many off-target proteins have very similar structures. How this specificity of physical protein-protein interactions in cellular networks is encoded and evolves is not very well understood. Here we address the question of specificity-encoding by comprehensively quantifying the effects of all mutations in one protein, JUN, on its binding to all other members of a protein family, the 54 human basic leucine zipper transcription factors. Fitting a global thermodynamic model to the data reveals that most affinity changing mutations equally affect JUNs propensity to bind to all its interaction partners. Mutations that alter the specificity of binding are much rarer. These specificity-altering mutations are, however, distributed throughout the JUN interaction interface. JUNs interaction specificity is encoded by both positive determinants that promote on-target interactions and negative determinants that prevent off-target interactions. Indeed, about half of the specificity-defining residues in JUN have dual functions and both promote on-target binding and prevent off-target binding. Whereas nearly all mutations that alter specificity are pleiotropic and also alter the affinity of binding to all interaction partners, the converse is not true with mutations outside of the interface able to tune affinity without affecting specificity. Our results provide the first global view of how mutations in a protein affect binding to all its potential interaction partners and reveal the distributed encoding of specificity and affinity in an interaction interface. They also show how the modular architecture of coiled-coils provides an elegant solution to the challenge of optimising specificity and affinity in a large protein family.

systems biology↗

bioRxiv2023

GUIFold - A graphical user interface for local AlphaFold2

GUIFold is a graphical user interface for the open-source structure prediction pipeline AlphaFold2. A particular emphasis lies on tracking prediction jobs in a database as well as user-friendly submission to queueing systems. GUIFold is built on top of a modified AlphaFold2 pipeline that primarily allows more control of the feature generation step. Additionally, the application provides an evaluation pipeline to rank predictions and visualize confidence metrics. GUIFold can be installed along with AlphaFold2 in a virtual environment and, after initial setup, allows running jobs without particular technical expertise.

bioinformatics↗

bioRxiv2019

Live analysis and reconstruction of single-particle cryo-electron microscopy data with CryoFLARE

Efficient, reproducible and accountable single-particle cryo-electron microscopy structure determination is tedious and often impeded by lack of a standardized procedure for data analysis and processing. To address this issue, we have developed the FMI Live Analysis and Reconstruction Engine (CryoFLARE). CryoFLARE is a modular open-source platform offering easy integration of new processing algorithms developed by the cryo-EM community. It provides a user-friendly interface that allows fast setup of standardized workflows, serving the need of pharmaceutical industry and academia alike who need to optimize throughput of their microscope. To consistently document how data is processed, CryoFLARE contains an integrated reporting facility to create reports. Live analysis and processing parallel to data acquisition are used to monitor and optimize data quality. Problems at the level of the sample preparation (heterogeneity, ice thickness, sparse particles, areas selected for acquisition, etc.) or misalignments of the microscope optics can quickly be detected and rectified before data collection is continued. Interfacing with automated data collection software for retrieval of acquisition metadata reduces user input needed for analysis, and with it minimizes potential sources of errors and workflow inconsistencies. Local and remote export support in Relion-compatible job and data format allows seamless integration into the refinement process. The support for non-linear workflows and fine-grained scheduling for mixed workflows with separate CPU and GPU based calculation steps ensures optimal use of processing hardware. CryoFLAREs flexibility allows it to be used for all types of image acquisitions, ranging from sample screening to high-resolution data collection, and offers a new alternative for setting up image processing workflows. It can be used without modifications of the hardware/software delivered by the microscope supplier. As it is running on a server in parallel to the hardware used for acquisition, it can easily be set up for remote display connections and fast control of the acquisition status.

biophysics↗