The present study demonstrates that one-step peptide backbone fragmentations can be achieved using the TEMPO [2-(2,2,6,6-tetramethyl piperidine-1-oxyl)]-assisted free radical-initiated peptide sequencing (FRIPS) mass spectrometry in a hybrid quadrupole time-of-flight (Q-TOF) mass spectrometer and a Q-Exactive Orbitrap instrument in positive ion mode, in contrast to two-step peptide fragmentation in an ion-trap mass spectrometer (reference Anal. Chem. 85, 7044-7051 (30)). In the hybrid Q-TOF and Q-Exactive instruments, higher collisional energies can be applied to the target peptides, compared with the low collisional energies applied by the ion-trap instrument. The higher energy deposition and the additional multiple collisions in the collision cell in both instruments appear to result in one-step peptide backbone dissociations in positive ion mode. This new finding clearly demonstrates that the TEMPO-assisted FRIPS approach is a very useful tool in peptide mass spectrometry research. Graphical Abstract ᅟ.

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Screening and identifying unknown erectile dysfunction (ED) drugs and analogues, which are often illicitly added to health supplements, is a challenging analytical task. The analytical technique most commonly used for this purpose, liquid chromatography−tandem mass spectrometry (LC−MS/MS), is based on the strategy of searching the LC− MS/MS spectra of target compounds against database spectra. However, such a strategy cannot be applied to unknown ED drugs and analogues. To overcome this dilemma, we have constructed a standalone software named AI-SIDA (artificial intelligence screener of illicit drugs and analogues). AI-SIDA consists of three layers: LC-MS/MS viewer, AI classif ier, and Identif ier. In the second AI classifier layer, an artificial neural network (ANN) classification model, which was constructed by training 149 LC−MS/MS spectra (including 27 sildenafil-type, 6 vardenafil-type, 11 tadalafil-type ED drugs/analogues and other 105 compounds), is included to classify the LC−MS/MS spectra of the query compound into four categories: i.e., sildenafil, vardenafil, and tadalafil families and non-ED compounds. This ANN model was found to show 100% classification accuracy for the 187 LC−MS/MS modeling and test data sets. In the third Identifier layer, three search algorithms (pick-count scoring, simple similarity search, and hybrid similarity search) are implemented. In particular, the hybrid similarity search was found to be very powerful in identifying unknown ED drugs/ analogues with a single modification from the library ED drugs/analogues. Altogether, the AI-SIDA software provides a very useful and powerful platform for screening unknown ED drugs and analogues.

Bacterial pathogens have evolved diverse types of efficient machinery to acquire haem, the most abundant source of iron in the human body, and degrade it for the utilization of iron. Gram-positive bacteria commonly encode IsdG-family proteins as haem-degrading monooxygenases. Listeria monocytogenes is predicted to possess an IsdG-type protein (Lmo2213), but the residues involved in haem monooxygenase activity are not well conserved and there is an extra N-terminal domain in Lmo2213. Therefore, its function and mechanism of action cannot be predicted. In this study, the crystal structure of Lmo2213 was determined at 1.75 Å resolution and its haem-binding and haem-degradation activities were confirmed. Structure-based mutational and functional assays of this protein, designated as an Isd-type L. monocytogenes haem-degrading enzyme (Isd-LmHde), identified that Glu71, Tyr87 and Trp129 play important roles in haem degradation and that the N-terminal domain is also critical for its haem-degrading activity. The haem-degradation product of Isd-LmHde is verified to be biliverdin, which is also known to be the degradation product of other bacterial haem oxygenases. This study, the first structural and functional report of the haem-degradation system in L. monocytogenes, sheds light on the concealed haem-utilization system in this life-threatening human pathogen.