The X-ray crystal structure of the Head module, one-third of the Mediator of transcriptional regulation, has been determined as a complex with the C-terminal domain (CTD) of RNA polymerase II. The structure reveals multiple points of interaction with an extended conformation of the CTD; it suggests a basis for regulation by phosphorylation of the CTD. Biochemical studies show a requirement for Mediator-CTD interaction for transcription.

Chemical cross-linking mass spectrometry identifies interacting surfaces within a protein assembly through labeling with bifunctional reagents and identifying the covalently modified peptides. These yield distance constraints that provide a powerful means to model the three-dimensional structure of the assembly. Bioinformatic analysis of cross-linked data resulting from large protein assemblies is challenging because each cross-linked product contains two covalently linked peptides, each of which must be correctly identified from a complex matrix of potential confounders. Protein Prospector addresses these issues through a complementary mass modification strategy in which each peptide is searched and identified separately. We demonstrate this strategy with an analysis of RNA polymerase II. False discovery rates (FDRs) are assessed via comparison of cross-linking data to crystal structure, as well as by using a decoy database strategy. Parameters that are most useful for positive identification of cross-linked spectra are explored. We find that fragmentation spectra generally contain more product ions from one of the two peptides constituting the cross-link. Hence, metrics reflecting the quality of the spectral match to the less confident peptide provide the most discriminatory power between correct and incorrect matches. A support vector machine model was built to further improve classification of cross-linked peptide hits. Furthermore, the frequency with which peptides cross-linked via common acylating reagents fragment to produce diagnostic, cross-linker-specific ions is assessed. The threshold for successful identification of the cross-linked peptide product depends upon the complexity of the sample under investigation. Protein Prospector, by focusing the reliability assessment on the least confident peptide, is better able to control the FDR for results as larger complexes and databases are analyzed. In addition, when FDR thresholds are calculated separately for intraprotein and interprotein results, a further improvement in the number of unique cross-links confidently identified is achieved. These improvements are demonstrated on two previously published cross-linking datasets.

In native mass spectrometry, it has been difficult to discriminate between specific bindings of a ligand to a multiprotein complex target from the nonspecific interactions. Here, we present a deconvolution model that consists of two levels of data reduction. At the first level, the apparent association binding constants are extracted from the measured intensities of the target/ligand complexes by varying ligand concentration. At the second level, two functional forms representing the specific and nonspecific binding events are fit to the apparent binding constants obtained from the first level of modeling. Using this approach, we found that a power-law distribution described nonspecific binding of α-amanitin to yeast RNA polymerase II. Moreover, treating the concentration of the multiprotein complex as a fitting parameter reduced the impact of inaccuracies in this experimental measurement on the apparent association constants. This model improves upon current methods for separating specific and nonspecific binding to large, multiprotein complexes in native mass spectrometry, by modeling nonspecific binding with a power-law function.

Native electrospray-ionization mass spectrometry (native MS) measures biomolecules under conditions that preserve most aspects of protein tertiary and quaternary structure, enabling direct characterization of large intact protein assemblies. However, native spectra derived from these assemblies are often partially obscured by low signal-to-noise as well as broad peak shapes because of residual solvation and adduction after the electrospray process. The wide peak widths together with the fact that sequential charge state series from highly charged ions are closely spaced means that native spectra containing multiple species often suffer from high degrees of peak overlap or else contain highly interleaved charge envelopes. This situation presents a challenge for peak detection, correct charge state and charge envelope assignment, and ultimately extraction of the relevant underlying mass values of the noncovalent assemblages being investigated. In this report, we describe a comprehensive algorithm developed for addressing peak detection, peak overlap, and charge state assignment in native mass spectra, called PeakSeeker. Overlapped peaks are detected by examination of the second derivative of the raw mass spectrum. Charge state distributions of the molecular species are determined by fitting linear combinations of charge envelopes to the overall experimental mass spectrum. This software is capable of deconvoluting heterogeneous, complex, and noisy native mass spectra of large protein assemblies as demonstrated by analysis of (1) synthetic mononucleosomes containing severely overlapping peaks, (2) an RNA polymerase II/α-amanitin complex with many closely interleaved ion signals, and (3) human TriC complex containing high levels of background noise. Graphical Abstract ᅟ.