Buzafalvi, D. | Search bioRxiv

bioRxiv2026

Insights into mechanisms of ATM activation via constitutively active mutants

The Ser/Thr kinase ATM orchestrates cellular responses to DNA double-strand breaks (DSBs) and promotes DSB repair by homologous recombination. In this process, ATM is activated by DNA and the MRN (MRE11, RAD50, and NBS1) complex. Here we show that mutations of the conserved PIKK regulatory domain (PRD) within ATMs kinase domain can confer a maximally active state that no longer requires MRN/DNA. In ATM-knockout human cells, the PRD mutants display substantially higher phosphorylation of histone H2AX, KAP1, and CHK2 than wild-type ATM, with or without IR-induced DNA damage. Cryo-EM structures of two PRD mutants each revealed basal or activated conformations depending on bound ligands, suggesting that disrupting the ordered portion of the PRD results in an enzyme poised to transition to the active conformation. However, the identity of the active-site nucleotide is a key driver of the conformational switching. We speculate that this plasticity might be exploited to develop small-molecule ATM modulators for therapeutic applications.

molecular biology↗

bioRxiv2026

DeltaMut: An Integrative Database of AlphaFold2-Derived Missense Variant Structures

The widespread use of next-generation sequencing has led to a surge in the number of identified variants with uncertain effects on protein function. These variants pose a significant challenge in diagnostics and hinder patient treatment strategies. Numerous variant effect predictors (VEPs) are available to assess variant impact, but they primarily rely on sequence-derived information. The recent development of AlphaFold2 has raised questions about whether information retrieved from wild-type or predicted structures of missense variants can improve the predictive power of these algorithms. While the AlphaFold Protein Structure Database serves as a valuable resource for wild-type protein structures, a large-scale collection of missense variant structures is not available, limiting current efforts to wild-type conformations and a handful of modeled variants. To address this limitation, we developed DeltaMut, a comprehensive database containing over 77,000 protein structures, including 65,000 pathogenic and neutral missense variants. All structural models were generated using ParaFold, a high-performance computing-optimized implementation of AlphaFold2. The large-scale and systematic generation of variant protein structures distinguish DeltaMut as a unique resource for both expansive statistical studies and detailed, case-specific investigations of variant-induced structural changes. Furthermore, the DeltaMut database is freely accessible without registration. HighlightsO_LIDeltaMut is currently the largest database of AlphaFold2-predicted variant structures. C_LIO_LIContains 77,713 structures covering 12,101 wild-type and 65,612 variant proteins. C_LIO_LI70.6% of predicted structures have high or very high confidence (pLDDT [≥] 70). C_LIO_LIFreely accessible web server with visualization and download of variant models. C_LI

bioinformatics↗