Ampicillin/penicillin-binding protein interactions as a model drug-target system to optimize affinity pull-down and mass spectrometric strategies for target and pathway identification.

The identification and validation of the targets of active compounds identified in cell-based assays is an important step in preclinical drug development. New analytical approaches that combine drug affinity pull-down assays with mass spectrometry (MS) could lead to the identification of new targets and druggable pathways. In this work, we investigate a drug-target system consisting of ampicillin- and penicillin-binding proteins (PBPs) to evaluate and compare different amino-reactive resins for the immobilization of the affinity compound and mass spectrometric methods to identify proteins from drug affinity pull-down assays. First, ampicillin was immobilized onto various amino-reactive resins, which were compared in the ampicillin-PBP model with respect to their nonspecific binding of proteins from an Escherichia coli membrane extract. Dynal M-270 magnetic beads were chosen to further study the system as a model for capturing and identifying the targets of ampicillin, PBPs that were specifically and covalently bound to the immobilized ampicillin. The PBPs were identified, after in situ digestion of proteins bound to ampicillin directly on the beads, by using either one-dimensional (1-D) or two-dimensional (2-D) liquid chromatography (LC) separation techniques followed by tandem mass spectrometry (MS/MS) analysis. Alternatively, an elution with N-lauroylsarcosine (sarcosyl) from the ampicillin beads followed by in situ digestion and 2-D LC-MS/MS analysis identified proteins potentially interacting noncovalently with the PBPs or the ampicillin. The in situ approach required only little time, resources, and sample for the analysis. The combination of drug affinity pull-down assays with in situ digestion and 2-D LC-MS/MS analysis is a useful tool in obtaining complex information about a primary drug target as well as its protein interactors.

Average peptide score: a useful parameter for identification of proteins derived from database searches of liquid chromatography/tandem mass spectrometry data.

The quantity and variable quality of data that can be generated from liquid chromatography (LC)/mass spectrometry (MS)-based proteomics analyses creates many challenges in interpreting the spectra in terms of the actual proteins in a complex sample. In spite of improvements in algorithms that match putative peptide sequences to MS/MS spectra, the assembly of these lists of possible or probable peptides into a 'correct' set of proteins is still problematic. We have observed a trend in a simple relationship, derived from standard database search outputs, which can be useful in assessing the quality of a MS/MS-based protein identification. Specifically, the ratio of the protein score and number of non-redundant peptides, or average peptide score (APS), can facilitate initial filtering of database search results in addition to providing a useful measure of confidence for the proteins identified. This parameter has been applied to results from the analysis of multi-protein complexes derived from pull-down experiments analyzed using a two-dimensional LC/MS/MS workflow. In particular, the complex list of protein identifications derived from a drug affinity pull-down with immobilized ampicillin and an E. coli lysate was greatly simplified by applying the APS as a filter, allowing for facile identification of the penicillin-binding proteins known to interact with ampicillin. Furthermore, an APS threshold can be used for any data sets derived from electrospray ionization (ESI)- or matrix-assisted laser desorption/ionization (MALDI)-MS/MS experiments and is also not specific to any database search program.