Soluble guanylyl/guanylate cyclase (sGC) converts GTP to cGMP after binding nitric oxide, leading to smooth muscle relaxation and vasodilation. Impaired sGC activity is common in cardiovascular disease and sGC stimulatory compounds are greatly sought. sGC is a 150 kDa heterodimeric protein with two H-NOX domains (one with heme, one without), two PAS domains, a coiled-coil domain and two cyclase domains. Binding of NO to the sGC heme leads to proximal histidine release and stimulation of catalytic activity. To begin understanding how binding leads to activation, we examined truncated sGC proteins from Manduca sexta (tobacco hornworm) that bind NO, CO and stimulatory compound YC-1, but lack the cyclase domains. We determined the overall shape of truncated Ms sGC using analytical ultracentrifugation and small angle X-ray scattering (SAXS), revealing an elongated molecule 115 Å by 90 Å by 75 Å. Binding of NO, CO or YC-1 had little effect on shape. Using chemical cross-linking and tandem mass spectrometry, we identified 20 intermolecular contacts, allowing us to fit homology models of the individual domains into the SAXS-derived molecular envelope. The resulting model displays a central parallel coiled-coil platform upon which the H-NOX and PAS domains are assembled. The β1 H-NOX and α1 PAS domains are in contact and form the core signaling complex, while the α1 H-NOX domain can be removed without significant effect on ligand binding or overall shape. Removal of 21 residues from the C-terminus yields a protein with dramatically increased proximal histidine release rates upon NO binding.

To interpret LC-MS/MS data in proteomics, most popular protein identification algorithms primarily use predicted fragment m/z values to assign peptide sequences to fragmentation spectra. The intensity information is often undervalued, since it is not as easy to predict and incorporate into algorithms. Nevertheless, the use of intensity to assist peptide identification is an attractive prospect and can potentially improve the confidence of matches and generate more identifications. Based on our previously reported study of fragmentation intensity patterns, we developed a protein identification algorithm, SeQuence IDentfication (SQID), which makes use of the coarse intensity from a statistical analysis. The scoring scheme was validated by comparing with Sequest and X!Tandem using three datasets, and the results indicate an improvement in the number of identified peptides, including unique peptides that are not identified by Sequest or X!Tandem. The software and source code are available under the GNU GPL license at: http://quiz2.chem.arizona.edu/wysocki/bioinformatics.htm.

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