Biology subjects

Sykacek, P.

Publications and source records attributed to Sykacek, P..

3 recordsLinked to original sources

bioRxiv2026

The topology of transmembrane protein-protein interaction interfaces is encoded in their physicochemical features

Transmembrane (TM) protein-protein interactions (PPIs) are essential mediators of signal transduction, transport of solutes and communication, yet the biophysical features that characterize their diverse topologies remain poorly understood. To reduce this knowledge gap we use the human solute carrier (SLC) interactome to study whether physicochemical features of PPI interfaces encode information about their TM topology (i.e., their position and arrangement with respect to the membrane). To this end we predicted structures for 2, 055 experimentally validated PPIs using AlphaFold v3.0, performed molecular dynamics simulations and annotated the PPI interfaces by TM coverage. As a result every interface is characterized by 63 physicochemical, structural and energy features. A reproducible machine learning workflow allows us to study the interdependence between these interface properties and interface topology. We found that amino acid composition and secondary structure contributed most to distinguishing soluble from fully membrane-embedded interfaces. Membrane-embedded interfaces contained a larger fraction of hydrophobic residues and -helices, while charged residues were depleted. For partially and full membrane-embedded interfaces, amino acid composition and secondary structure get more similar and differences are increasingly observed in charge and energy related features. As particularly noteworthy we find that PPI interface characteristics vary with the number of annotated TM segments mainly through differences in proportions of secondary structure, charge, and flexibility. We hence conclude that PPI interface characteristics harbor substantial information about TM interface topology and provide a framework for the study and design of membrane protein interaction interfaces.

bioinformatics↗

bioRxiv2024

The solute carrier superfamily interactome

Solute carrier (SLC) transporters form a protein superfamily that enables transmembrane transport of diverse substrates including nutrients, ions and drugs. There are about 450 different SLCs, residing in a variety of subcellular membranes. Loss-of-function of an unusually high proportion of SLC transporters is genetically associated with a plethora of human diseases, making SLCs a rapidly emerging but challenging drug target class. Knowledge of their protein environment may elucidate the molecular basis for their functional integration with metabolic and cellular pathways and help conceive pharmacological interventions based on modulating proteostatic regulation. We aimed at obtaining a global survey of the SLC protein interaction landscape and mapped the protein-protein interactions of 396 SLCs by interaction proteomics. We employed a functional assessment based on RNA interference of interactors in combination with measurement of protein stability and localization. As an example, we detail the role of a SLC16A6 phospho-degron, and the contributions of PDZ-domain proteins LIN7C and MPP1 to the trafficking of SLC43A2. Overall, our work offers a resource for SLC-protein interactions for the scientific community.

systems biology↗

bioRxiv2020

Systematic protein complex profiling and differential analysis from co-fractionation mass spectrometry data

Protein complexes, macro-molecular assemblies of two or more proteins, play vital roles in numerous cellular activities and collectively determine the cellular state. Despite the availability of a range of methods for analysing protein complexes, systematic analysis of complexes under multiple conditions has remained challenging. Approaches based on biochemical fractionation of intact, native complexes and correlation of protein profiles have shown promise, for instance in the combination of size exclusion chromatography (SEC) with accurate protein quantification by SWATH/DIA-MS. However, most approaches for interpreting co-fractionation datasets to yield complex composition, abundance and rearrangements between samples depend heavily on prior evidence. We introduce PCprophet, a computational framework to identify novel protein complexes from SEC-SWATH-MS data and to characterize their changes across different experimental conditions. We demonstrate accurate prediction of protein complexes (AUC >0.99 and accuracy around 97%) via five-fold cross-validation on SEC-SWATH-MS data, show improved performance over state-of-the-art approaches on multiple annotated co-fractionation datasets, and describe a Bayesian approach to analyse altered protein-protein interactions across conditions. PCprophet is a generic computational tool consisting of modules for data pre-processing, hypothesis generation, machine-learning prediction, post-prediction processing, and differential analysis. It can be applied to any co-fractionation MS dataset, independent of separation or quantitative LC-MS workflow employed, and to support the detection and quantitative tracking of novel protein complexes and their physiological dynamics.

systems biology↗