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Schumbera, E.

Publications and source records attributed to Schumbera, E..

2 recordsLinked to original sources

Systematic drug profiling across BAF complex perturbations reveals distinct dependencies

Chromatin remodeling by BAF complexes regulates access to DNA with implications in transcription, replication and the sensing and repair of DNA lesions, processes that are closely coupled to cell growth control. BAF complexes exist in three major subtypes each composed of a unique subset of about a dozen subunits. While for individual BAF subunits direct functions in DNA repair and cell growth have been described, we lack a more systematic interrogation of BAF perturbation and its implications in these processes. To fill this need, we subjected an isogenic BAF knockout collection to treatment with diverse genotoxic and cytotoxic compounds quantifying proliferation, cell cycle phase distributions, cell fate decisions, DNA double-strand break signaling, and transcriptional responses. The screen uncovered vulnerabilities of selected BAF-deficient cells to MEK and EGFR pathway inhibition, as well as unexpected resistance toward checkpoint inhibitors and certain DNA-damaging agents. Notably, loss of distinct ARID paralogs produced markedly divergent phenotypes, indicating limited functional redundancy and subtype-specific contributions to genome stability and cell cycle regulation. Collectively, these results provide a comparative resource linking BAF complex composition to genotoxic and cytotoxic stress responses, highlighting candidate synthetic-lethal interactions and generating hypotheses for mechanistic studies of BAF complexes in genome maintenance and cell growth control.

molecular biology↗

Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation

Structural resolution of protein interactions enables mechanistic and functional studies as well as interpretation of disease variants. However, structural data is still missing for most protein interactions because we lack computational and experimental tools at scale. We thoroughly assessed AlphaFold-Multimer accuracy for structure prediction of interactions involving folded domains binding to short linear motifs from the ELM database. The structure predictions were highly sensitive but not very specific when using small protein fragments. Sensitivity decreased substantially when using long protein fragments or full length proteins with intrinsically disordered regions. We delineated a fragmentation strategy to optimize sensitivity and applied it to interactions between proteins associated with neurodevelopmental disorders. This enabled prediction of highly confident and likely disease-related novel interfaces, but also resulted in many high scoring false positive predictions. Experiments supported predicted interfaces between CREBZF-HCFC1, FBXO23-STX1B, STX1B-VAMP2, ESRRG-PSMC5, PEX3-PEX19, PEX3-PEX16, and SNRPB-GIGYF1 providing novel molecular insights for diverse biological processes. Our work highlights exciting perspectives, but also reveals clear limitations and the need for future developments to maximize the power of Alphafold-Multimer for interface predictions.

systems biology↗