The XRCC4-like factor (XLF)-XRCC4 complex is essential for nonhomologous end joining, the major repair pathway for DNA double strand breaks in human cells. Yet, how XLF binds XRCC4 and impacts nonhomologous end joining functions has been enigmatic. Here, we report the XLF-XRCC4 complex crystal structure in combination with biophysical and mutational analyses to define the XLF-XRCC4 interactions. Crystal and solution structures plus mutations characterize alternating XRCC4 and XLF head domain interfaces forming parallel super-helical filaments. XLF Leu-115 (“Leu-lock”) inserts into a hydrophobic pocket formed by XRCC4 Met-59, Met-61, Lys-65, Lys-99, Phe-106, and Leu-108 in synergy with pseudo-symmetric β-zipper hydrogen bonds to drive specificity. XLF C terminus and DNA enhance parallel filament formation. Super-helical XLF-XRCC4 filaments form a positively charged channel to bind DNA and align ends for efficient ligation. Collective results reveal how human XLF and XRCC4 interact to bind DNA, suggest consequences of patient mutations, and support a unified molecular mechanism for XLF-XRCC4 stimulation of DNA ligation.
SUMMARY
The integration of biophysical data from multiple sources is critical for developing accurate structural models of large multiprotein systems and their regulators. Mass spectrometry (MS) can be used to measure the insertion location for a wide range of topographically sensitive chemical probes, and such insertion data provide a rich, but disparate set of modeling restraints. We have developed a software platform that integrates the analysis of label-based MS data with protein modeling activities (Mass Spec Studio). Analysis packages can mine any labeling data from any mass spectrometer in a proteomics-grade manner, and link labeling methods with data-directed protein interaction modeling using HADDOCK. Support is provided for hydrogen/ deuterium exchange (HX) and covalent labeling chemistries, including novel acquisition strategies such as targeted HX-tandem MS (MS2) and data-independent HX-MS2. The latter permits the modeling of highly complex systems, which we demonstrate by the analysis of microtubule interactions.
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