Fragmentation of Polyfunctional Compounds Recorded Using Automated High-Throughput Desorption Electrospray Ionization

Baldwin and Whitehead's Manzamine Alkaloids Biosynthesis Hypothesis Involves a Finely Tuned Reactivity of Acrolein: Automated Extraction of Reactivity Patterns from LC-MS2 Data

Inspired by the multicomponent reaction-type scenario involving fatty dialdehydes, a nitrogen source, and acrolein, as a key C3 unit, put forward by Baldwin and Whitehead to explain the formation of manzamine-type alkaloids, 96 multicomponent reactions were designed, and their analytical readouts were deconvoluted using a herein-provided chemoinformatic workflow. This strategy pinpointed relevant conditions tuning the reactivity of acrolein to fulfill Baldwin and Whitehead's manzamine alkaloids biosynthetic hypothesis. This strategy can become part of a general method for the high-content analysis of multicomponent reactions applied to a natural product biosynthetic scenario.

Re-Imagining Drug Discovery using Mass Spectrometry

It is argued that each of the three key steps in drug discovery, (i) reaction screening to find successful routes to desired drug candidates, (ii) scale up of the synthesis to produce amounts adequate for testing, and (iii) bioactivity assessment of the candidate compounds, can all be performed using mass spectrometry (MS) in a sequential fashion. The particular ionization method of choice, desorption electrospray ionization (DESI), is both an analytical technique and a procedure for small-scale synthesis. It is also highly compatible with automation, providing for high throughput in both synthesis and analysis. Moreover, because accelerated reactions take place in the secondary DESI microdroplets generated from individual reaction mixtures, this allows either online analysis by MS or collection of the synthetic products by droplet deposition. DESI also has the unique advantage, amongst spray-based MS ionization methods, that complex buffered biological solutions can be analyzed directly, without concern for capillary blockage. Here, all these capabilities are illustrated, the unique chemistry at droplet interfaces is presented, and the possible future implementation of DESI-MS based drug discovery is discussed.

High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry

Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes.

Desorption Electrospray Ionization Mass Spectrometry Assay for Label-Free Characterization of SULT2B1b Enzyme Kinetics

The sulfotransferase (SULT) 2B1b, which catalyzes the sulfonation of 3β-hydroxysteroids, has been identified as a potential target for prostate cancer treatment. However, a major limitation for SULT2B1b-targeted drug discovery is the lack of robust assays compatible with high-throughput screening and inconsistency in reported kinetic data. For this reason, we developed a novel label-free assay based on high-throughput (>1 Hz) desorption electrospray ionization mass spectrometry (DESI-MS) for the direct quantitation of the sulfoconjugated product (CV<10 %; <1 ng analyte). The performance of this DESI-based assay was compared against a new fluorometric coupled-enzyme method that we also developed. Both methodologies provided consistent kinetic data for the reaction of SULT2B1b with its major substrates, indicating the affinity trend pregnenolone>DHEA>cholesterol, for both the phospho-mimetic and wild-type SULT2B1b forms. The novel DESI-MS assay developed here is likely generalizable to other drug discovery efforts and is particularly promising for identification of SULT2B1b inhibitors with potential as prostate cancer therapeutics.

Spontaneous Water Radical Cation Oxidation at Double Bonds in Microdroplets

Spontaneous oxidation of compounds containing diverse X=Y moieties (e.g., sulfonamides, ketones, esters, sulfones) occurs readily in organic-solvent microdroplets. This surprising phenomenon is proposed to be driven by the generation of an intermediate species [M+H₂O]^+·: a covalent adduct of water radical cation (H₂O^+·) with the reactant molecule (M). The adduct is observed in the positive ion mass spectrum while its formation in the interfacial region of the microdroplet (i.e., at the air-droplet interface) is indicated by the strong dependence of the oxidation product formation on the spray distance (which reflects the droplet size and consequently the surface-to-volume ratio) and the solvent composition. Importantly, based on the screening of a ca. 21,000-compound library and the detailed consideration of six functional groups, the formation of a molecular adduct with the water radical cation is a significant route to ionization in positive ion mode electrospray, where it is favored in those compounds with X=Y moieties which lack basic groups. A set of model monofunctional systems was studied and in one case, benzyl benzoate, evidence was found for oxidation driven by hydroxyl radical adduct formation followed by protonation in addition to the dominant water radical cation addition process. Significant implications of molecular ionization by water radical cations for oxidation processes in atmospheric aerosols, analytical mass spectrometry and small-scale synthesis are noted.

Applications of ambient ionization mass spectrometry in 2021: An annual review

Ambient ionization mass spectrometry (AIMS) has revolutionized the field of analytical chemistry, enabling the rapid, direct analysis of samples in their native state. Since the inception of AIMS almost 20 years ago, the analytical community has driven the further development of this suite of techniques, motivated by the plentiful advantages offered in addition to traditional mass spectrometry. Workflows can be simplified through the elimination of sample preparation, analysis times can be significantly reduced and analysis remote from the traditional laboratory space has become a real possibility. As such, the interest in AIMS has rapidly spread through analytical communities worldwide, and AIMS techniques are increasingly being integrated with standard laboratory operations. This annual review covers applications of AIMS techniques throughout 2021, with a specific focus on AIMS applications in a number of key fields of research including disease diagnostics, forensics and security, food safety testing and environmental sciences. While some new techniques are introduced, the focus in AIMS research is increasingly shifting from the development of novel techniques toward efforts to improve existing AIMS techniques, particularly in terms of reproducibility, quantification and ease-of-use.

Rapid analysis of quinones in complex matrices by derivatization-based wooden-tip electrospray ionization mass spectrometry

Quinones are important components participating in various biological processes as well as hazardous substances to human health. Rapid determination of quinones in environmental samples and biofluids is the basis for assessing their health effect. Here, we presented a rapid, straightforward, highly sensitive and environmental-friendly wooden-tip electrospray ionization mass spectrometry (ESI-MS) method for the determination of quinones in PM2.5, urine and serum. An amine group "tag" was introduced to the quinone structure through in situ derivatization with cysteamine to improve ionization efficiency of quinones in wooden-tip ESI-MS. The toothpicks were treated by sharpening and acidification with HNO₃. Experimental parameters, including sample volume, spray voltage, and spray solvent composition were optimized to be 1 μL, 3.5 kV, and ACN/CH₃COOC₂H₅ (v/v, 9:1), respectively. The limits of detection for the determination of 1,4-benzoquinone, methyl-p-benzoquinone, 1,4-naphthoquinone and 1,4-anthraquinone in ACN under the optimal conditions were 1.00, 0.96, 0.13, 0.16 ng (1.00, 0.96, 0.13, 0.16 μg/mL, sample volume, 1 μL), respectively. This approach was successfully applied to the determination of 1,4-naphthoquinone and 1,4-anthraquinone in complex matrices, including PM2.5, urine and serum without or with minimal sample preparation (LOD range: 0.22-1.48 ng).

A Deep-Learning Proteomic-Scale Approach for Drug Design

Computational approaches have accelerated novel therapeutic discovery in recent decades. The Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget therapeutic discovery, repurposing, and design aims to improve their efficacy and safety by employing a holistic approach that computes interaction signatures between every drug/compound and a large library of non-redundant protein structures corresponding to the human proteome fold space. These signatures are compared and analyzed to determine if a given drug/compound is efficacious and safe for a given indication/disease. In this study, we used a deep learning-based autoencoder to first reduce the dimensionality of CANDO-computed drug-proteome interaction signatures. We then employed a reduced conditional variational autoencoder to generate novel drug-like compounds when given a target encoded "objective" signature. Using this approach, we designed compounds to recreate the interaction signatures for twenty approved and experimental drugs and showed that 16/20 designed compounds were predicted to be significantly (p-value ≤ 0.05) more behaviorally similar relative to all corresponding controls, and 20/20 were predicted to be more behaviorally similar relative to a random control. We further observed that redesigns of objectives developed via rational drug design performed significantly better than those derived from natural sources (p-value ≤ 0.05), suggesting that the model learned an abstraction of rational drug design. We also show that the designed compounds are structurally diverse and synthetically feasible when compared to their respective objective drugs despite consistently high predicted behavioral similarity. Finally, we generated new designs that enhanced thirteen drugs/compounds associated with non-small cell lung cancer and anti-aging properties using their predicted proteomic interaction signatures. his study represents a significant step forward in automating holistic therapeutic design with machine learning, enabling the rapid generation of novel, effective, and safe drug leads for any indication.

Automated High-Throughput System Combining Small-Scale Synthesis with Bioassays and Reaction Screening

The Purdue Make It system is a unique automated platform capable of small-scale in situ synthesis, screening small-molecule reactions, and performing direct label-free bioassays. The platform is based on desorption electrospray ionization (DESI), an ambient ionization method that allows for minimal sample workup and is capable of accelerating reactions in secondary droplets, thus conferring unique advantages compared with other high-throughput screening technologies. By combining DESI with liquid handling robotics, the system achieves throughputs of more than 1 sample/s, handling up to 6144 samples in a single run. As little as 100 fmol/spot of analyte is required to perform both initial analysis by mass spectrometry (MS) and further MSⁿ structural characterization. The data obtained are processed using custom software so that results are easily visualized as interactive heatmaps of reaction plates based on the peak intensities of m/z values of interest. In this paper, we review the system's capabilities as described in previous publications and demonstrate its utilization in two new high-throughput campaigns: (1) the screening of 188 unique combinatorial reactions (24 reaction types, 188 unique reaction mixtures) to determine reactivity trends and (2) label-free studies of the nicotinamide N-methyltransferase enzyme directly from the bioassay buffer. The system's versatility holds promise for several future directions, including the collection of secondary droplets containing the products from successful reaction screening measurements, the development of machine learning algorithms using data collected from compound library screening, and the adaption of a variety of relevant bioassays to high-throughput MS.