Kerstin Spirohn

Dynamic engagement of dual-role regulators by the Sin3 complex

The paper investigates how dual-role regulators interact with the Sin3 complex using structural and functional analyses, revealing mechanisms for transcriptional crosstalk.

A scalable approach to resolving variants of uncertain significance

The paper develops a scalable workflow to reclassify variants of uncertain significance using experimental and predictive evidence, resolving 75% of VUS in 40 genes.

Predicting interaction-specific protein-protein interaction perturbations by missense variants with MutPred-PPI

MutPred-PPI predicts interaction-specific effects of missense variants using graph attention networks, showing strong performance on both seen and unseen proteins.

Viral transcriptional regulators extensively rewire host pathways through diverse mechanisms

This study systematically profiles 95 viral transcriptional regulators (vTRs) across multiple assays, revealing their diverse mechanisms of rewiring host pathways to promote viral replication and disease links.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

The paper identifies two categories of transcription factor isoforms with distinct molecular functions and shows they contribute to gene regulatory complexity.

A comprehensive two-hybrid analysis to explore the L. pneumophila effector-effector interactome

The paper uses a yeast two-hybrid screen to identify novel effector-effector interactions in L. pneumophila, doubling the known number of such interactions.

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

The paper presents an AI-guided pipeline for PPI drug discovery, identifying a SARS-CoV-2 inhibitor by combining experimental assays, machine learning, and virtual screening.

Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors

The paper introduces paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism between transcription factors and demonstrates their application across various TF pairs.

N-terminal proteoforms may engage in different protein complexes

The paper investigates N-terminal proteoforms and finds they can engage in different protein complexes compared to their canonical counterparts.

Expanding the HDAC druggable landscape beyond enzymatic activity

This paper identifies a non-enzymatic HDAC inhibitor with anti-tumor and anti-psychedelic effects, showing reduced gene modulation compared to enzymatic inhibitors.

A map of binary SARS-CoV-2 protein interactions implicates host immune regulation and ubiquitination

The paper maps binary SARS-CoV-2 protein interactions with host proteins, identifying key processes like immune signaling and ubiquitination, and suggests therapeutic targets.

Assessment of community efforts to advance computational prediction of protein-protein interactions

The paper evaluates 24 network-based methods for predicting protein-protein interactions across five interactomes, identifies top-performing methods, and validates their predictions experimentally.

A quantitative mapping approach to identify direct interactions within complexomes

The paper presents a framework combining two high-throughput interaction assays to distinguish direct from indirect protein interactions in complexes.

Binary Interactome Models of Inner- Versus Outer-Complexome Organization

The paper constructs a high-quality yeast binary interactome map and compares inner- and outer-complexome organization, finding the outer-complexome contains more interactions and exhibits higher functional heterogeneity.

Maximizing binary interactome mapping with a minimal number of assays

The paper introduces an assayome concept to optimize binary interactome mapping by combining multiple assay versions, achieving high true positive detection with minimal assays.

A reference map of the human protein interactome

The paper presents HuRI, a comprehensive human protein-protein interaction map, and demonstrates its utility in understanding cellular function and disease mechanisms.

Network-based prediction of protein interactions

The paper challenges the Triadic Closure Principle in protein interaction prediction and introduces the L3 principle, which outperforms existing methods and identifies novel interactions.