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Background: Building extensive drug candidate libraries as early in the development pipeline as possible, with high-throughput in vitro absorption, distribution, metabolism, and excretion (ADME) profiling, is crucial for the selection of lead compounds to guide subsequent research and production phases. Traditionally, the analysis of metabolic stability assays heavily relies on high-throughput LC-MS/MS (liquid chromatography tandem mass spectrometry) techniques to meet with the lead profiling demands. Laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) is a quick and efficient technique for characterizing complex biological samples without laborious sample preparation. Objective: In this study, using an automated LA-REIMS well plate reader, achieving an 8 s per sample measurement time, the oxidative metabolic stability of active drug agents was assessed using biomimetic metalloporphyrin-based oxidative model reactions. Results: The results obtained using the novel LA-REIMS-based protocol were compared to and corroborated by those obtained using conventional HPLC-UV-MS (high performance liquid chromatography with ultra-violet detection coupled with mass spectrometry) measurements. Conclusions: LA-REIMS emerges as a promising technique, demonstrating potential suitability for semi-quantitative high-throughput metabolic stability in an optimized solvent environment.

Fragment screening is a popular strategy of generating viable chemical starting points especially for challenging targets. Although fragments provide a better coverage of chemical space and they have typically higher chance of binding, their weak affinity necessitates highly sensitive biophysical assays. Here, we introduce a screening concept that combines evolutionary optimized fragment pharmacophores with the use of a photoaffinity handle that enables high hit rates by LC-MS-based detection. The sensitivity of our screening protocol was further improved by a target-conjugated photocatalyst. We have designed, synthesized, and screened 100 diazirine-tagged fragments against three benchmark and three therapeutically relevant protein targets of different tractability. Our therapeutic targets included a conventional enzyme, the first bromodomain of BRD4, a protein-protein interaction represented by the oncogenic KRas G12D protein, and the yet unliganded N-terminal domain of the STAT5B transcription factor. We have discovered several fragment hits against all three targets and identified their binding sites via enzymatic digestion, structural studies and modeling. Our results revealed that this protocol outperforms screening traditional fully functionalized and photoaffinity fragments in better exploration of the available binding sites and higher hit rates observed for even difficult targets., (© 2024. The Author(s).)

Mass spectrometry has established itself as a powerful tool in the chemical, biological, medical, environmental, and agricultural fields. However, experimental approaches and potential application areas have been limited by a traditional reliance on sample preparation, extraction, and chromatographic separation. Ambient ionization mass spectrometry methods have addressed this challenge but are still somewhat restricted in requirements for sample manipulation to make it suitable for analysis. These limitations are particularly restrictive in view of the move toward high-throughput and automated analytical workflows. To address this, we present what we consider to be the first automated sample-preparation-free mass spectrometry platform utilizing a carbon dioxide (CO 2 ) laser for sample thermal desorption linked to the rapid evaporative ionization mass spectrometry (LA-REIMS) methodology. We show that the pulsatile operation of the CO 2 laser is the primary factor in achieving high signal-to-noise ratios. We further show that the LA-REIMS automated platform is suited to the analysis of three diverse biological materials within different application areas. First, clinical microbiology isolates were classified to species level with an accuracy of 97.2%, the highest accuracy reported in current literature. Second, fecal samples from a type 2 diabetes mellitus cohort were analyzed with LA-REIMS, which allowed tentative identification of biomarkers which are potentially associated with disease pathogenesis and a disease classification accuracy of 94%. Finally, we showed the ability of the LA-REIMS system to detect instances of adulteration of cooking oil and determine the geographical area of production of three protected olive oil products with 100% classification accuracy.

Rapid evaporative ionization mass spectrometry (REIMS) is a highly versatile technique allowing the sampling of a range of biological solid or liquid samples with no sample preparation. The cost of such a direct approach is that certain sample types provide only moderate amounts of chemical information. Here, we introduce a matrix assisted version of the technique (MA-REIMS), where an aerosol of a pure solvent, such as isopropanol, is mixed with the sample aerosol generated by rapid evaporation of the sample, and it is shown to enhance the signal intensity obtained from a REIMS sampling event by over 2 orders of magnitude. Such an increase greatly expands the scope of the technique, while providing additional benefits such as reducing the fouling of the REIMS source and allowing for a simple method of constant introduction of a calibration correction compound for accurate mass measurements. A range of experiments are presented in order to investigate the processes that occur within this modified approach, and applications where such enhancements are critical, such as intrasurgical tissue identification, are discussed.

Desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) is typically known for the ionisation of small molecules such as lipids and metabolites, in singly charged form. Here we present a method that allows the direct detection of proteins and peptides in multiply charged forms directly from tissue sections by DESI. Utilising a heated mass spectrometer inlet capillary, combined with ion mobility separation (IMS), the conditions with regard to solvent composition, nebulising gas flow, and solvent flow rate have been explored and optimised. Without the use of ion mobility separation prior to mass spectrometry analysis, only the most abundant charge series were observed. In addition to the dominant haemoglobin subunit(s) related trend line in the m/z vs drift time (DT) 2D plot, trend lines were found relating to background solvent peaks, residual lipids and, more importantly, small proteins/large peptides of lower abundance. These small proteins/peptides were observed with charge states from 1+ to 12+, the majority of which could only be resolved from the background when using IMS. By extracting charge series from the 2D m/z vs DT plot, a number of proteins could be tentatively assigned by accurate mass. Tissue images were acquired with a pixel size of 150 μm showing a marked improvement in protein image resolution compared to other liquid-based ambient imaging techniques such as liquid extraction surface analysis (LESA) and continuous-flow liquid microjunction surface sampling probe (LMJ-SSP) imaging. Graphical Abstract ᅟ.

The recently developed automated, high-throughput monopolar REIMS platform is suited for the identification of clinically important microorganisms. Although already comparable to the previously reported bipolar forceps method, optimization of the geometry of monopolar electrodes, at the heart of the system, holds the most scope for further improvements to be made. For this, sharp tip and round shaped electrodes were optimized to maximize species-level classification accuracy. Following optimization of the distance between the sample contact point and tube inlet with the sharp tip electrodes, the overall cross-validation accuracy improved from 77% to 93% in negative and from 33% to 63% in positive ion detection modes, compared with the original 4 mm distance electrode. As an alternative geometry, round tube shaped electrodes were developed. Geometry optimization of these included hole size, number, and position, which were also required to prevent plate pick-up due to vacuum formation. Additional features, namely a metal "X"-shaped insert and a pin in the middle were included to increase the contact surface with a microbial biomass to maximize aerosol production. Following optimization, cross-validation scores showed improvement in classification accuracy from 77% to 93% in negative and from 33% to 91% in positive ion detection modes. Supervised models were also built, and after the leave 20% out cross-validation, the overall classification accuracy was 98.5% in negative and 99% in positive ion detection modes. This suggests that the new generation of monopolar REIMS electrodes could provide substantially improved species level identification accuracies in both polarity detection modes. Graphical abstract.

A new, more robust sprayer for desorption electrospray ionization (DESI) mass spectrometry imaging is presented. The main source of variability in DESI is thought to be the uncontrolled variability of various geometric parameters of the sprayer, primarily the position of the solvent capillary, or more specifically, its positioning within the gas capillary or nozzle. If the solvent capillary is off-center, the sprayer becomes asymmetrical, making the geometry difficult to control and compromising reproducibility. If the stiffness, tip quality, and positioning of the capillary are improved, sprayer reproducibility can be improved by an order of magnitude. The quality of the improved sprayer and its potential for high spatial resolution imaging are demonstrated on human colorectal tissue samples by acquisition of images at pixel sizes of 100, 50, and 20 μm, which corresponds to a lateral resolution of 40-60 μm, similar to the best values published in the literature. The high sensitivity of the sprayer also allows combination with a fast scanning quadrupole time-of-flight mass spectrometer. This provides up to 30 times faster DESI acquisition, reducing the overall acquisition time for a 10 mm × 10 mm rat brain sample to approximately 1 h. Although some spectral information is lost with increasing analysis speed, the resulting data can still be used to classify tissue types on the basis of a previously constructed model. This is particularly interesting for clinical applications, where fast, reliable diagnosis is required. Graphical Abstract ᅟ.

Members of the genus Candida, such as C. albicans and C. parapsilosis, are important human pathogens. Other members of this genus, previously believed to carry minimal disease risk, are increasingly recognised as important human pathogens, particularly because of variations in susceptibilities to widely used anti-fungal agents. Thus, rapid and accurate identification of clinical Candida isolates is fundamental in ensuring timely and effective treatments are delivered. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has previously been shown to provide a high-throughput platform for the rapid and accurate identification of bacterial and fungal isolates. In comparison to commercially available matrix assisted laser desorption ionisation time of flight mass spectrometry (MALDI-ToF), REIMS based methods require no preparative steps nor time-consuming cell extractions. Here, we report on the ability of REIMS-based analysis to rapidly and accurately identify 153 clinical Candida isolates to species level. Both handheld bipolar REIMS and high-throughput REIMS platforms showed high levels of species classification accuracy, with 96% and 100% of isolates classified correctly to species level respectively. In addition, significantly different (FDR corrected P value < 0.05) lipids within the 600 to 1000 m/z mass range were identified, which could act as species-specific biomarkers in complex microbial communities., Competing Interests: This work was partly funded and supported by the Waters Corporation (through funding of Waters Corporation staff salaries, provision of equipment and consumables, and research funding to Imperial College London), and through funding from the UK Biotechnology and Biological Sciences Research Council via grant BB/L020858/1. ZT provides paid consultancy to the Waters Corporation. Neither funder had input into initial study design nor on decision of when and where to publish this manuscript. This paper does not promote any commercially available product of the Waters Corporation.

Rapid evaporative ionization mass spectrometry (REIMS) has been shown to quickly and accurately speciate microorganisms based upon their species-specific lipid profile. Previous work by members of this group showed that the use of a hand-held bipolar probe allowed REIMS to analyze microbial cultures directly from culture plates without any prior preparation. However, this method of analysis would likely be unsuitable for a high-throughput clinical microbiology laboratory. Here, we report the creation of a customized platform that enables automated, high-throughput REIMS analysis that requires minimal user input and operation and is suitable for use in clinical microbiology laboratories. The ability of this high-throughput platform to speciate clinically important microorganisms was tested through the analysis of 375 different clinical isolates collected from distinct patient samples from 25 microbial species. After optimization of our data analysis approach, we achieved substantially similar results between the two REIMS approaches. For hand-held bipolar probe REIMS, a speciation accuracy of 96.3% was achieved, whereas for high-throughput REIMS, an accuracy of 93.9% was achieved. Thus, high-throughput REIMS offers an alternative mass spectrometry based method for the rapid and accurate identification of clinically important microorganisms in clinical laboratories without any preanalysis preparative steps.

Rapid evaporative ionization mass spectrometry (REIMS) technology allows real time intraoperative tissue classification and the characterization and identification of microorganisms. In order to create spectral libraries for training the classification models, reference data need to be acquired in large quantities as classification accuracy generally improves as a function of number of training samples. In this study, we present an automated high-throughput method for collecting REIMS data from heterogeneous organic tissue. The underlying instrumentation consists of a 2D stage with an additional high-precision z-axis actuator that is equipped with an electrosurgical diathermy-based sampling probe. The approach was validated using samples of human liver with metastases and bacterial strains, cultured on solid medium, belonging to the species P. aeruginosa, B. subtilis, and S. aureus. For both sample types, spatially resolved spectral information was obtained that resulted in clearly distinguishable multivariate clustering between the healthy/cancerous liver tissues and between the bacterial species.

A chemical model for the H2O2 promoted oxidation by nitric oxide synthase (NOS) has been developed. Biomimetic oxidations were carried out using H2O2 and tetrakis(perfluorophenyl)porphyrinato-iron(III) chloride (FeTPPF20) as a catalyst. Similarly to NOS our model system produces Ndelta-cyanoornithine, citrulline and NO from NOHA and did not oxidize arginine itself. Based on these results we propose a peroxide shunt to be involved in the catalytic cycle of NOS. To the best of our knowledge this is the first chemical system that semiquantitatively mimics NOS activity.

Overpressured layer chromatography was combined with the highly sensitive and rapid digital autoradiography (DAR) and mass spectrometry to separate, detect, and identify 3H- and 14C-labeled deramciclane metabolites in different biological matrixes. Several minor and major metabolites were separated from plasma and urine samples. The radioactive metabolites localized by DAR were scraped from the thin-layer chromatographic plate and transferred to a mass spectrometer for structure identification. Several metabolites were isolated and characterized, including hydroxy-N-desmethyl deramciclane, which is described in detail. The combination of techniques is efficient and has good sensitivity: about 2 micrograms metabolite from a biological matrix was isolated and identified this way.

Cytochrome P450 (CP450) catalyzed oxidative metabolism of carbofuran (1), carbaryl (2), and pirimicarb (3) has been modeled using biomimetic oxidations catalyzed by iron(III) tetraarylporphyrins. Oxidation products of 1 were identified by comparison of HPLC retention times measured under standardized conditions for metabolites synthesized and characterized by (1)H and (13)C NMR spectroscopy. Comparison of product distributions to in vivo metabolic profiles revealed that the H(2)O(2)/meso-tetrakis(pentafluorophenyl)porphyrin iron(III) chloride [Fe(TF(20)PP)] system mimics the action of insect CP450s against carbofuran. The effectiveness of this system was further demonstrated by the biomimetic oxidation of other carbamate insecticides (2 and 3) monitored by HPLC/electrospray MS. The predictive power of this biomimetic model was compared to that of knowledge-based expert systems. Although similar models were recently applied in pharmaceutical research, the usefulness of this approach has first been demonstrated for the prediction of metabolic profiles of agrochemicals.

The manufacture-characteristic impurity profile of nifedipine drug substance was studied by HPLC and on-line LC/MS coupling. Using a new gradient HPLC procedure and MS detection, spectroscopic evidences for the chemical structure of some previously unknown minor impurities (all under 0.1%) were obtained.