Development of a high-throughput dual-stream liquid chromatography-tandem mass spectrometry method to screen for inhibitors of glutamate carboxypeptidase II.

RATIONALE: Glutamate carboxypeptidase II (GCPII) catalyzes the hydrolysis of N-acetylaspartylglutamate (NAAG) to yield glutamate (Glu) and N-acetylaspartate (NAA). Inhibition of GCPII has been shown to remediate the neurotoxicity of excess Glu in a variety of cell and animal disease models. A robust high-throughput liquid chromatography-tandem mass spectrometry (LC/MS/MS) method was needed to quantify GCPII enzymatic activity in a biochemical high-throughput screening assay. METHODS: A dual-stream LC/MS/MS method was developed. Two parallel eluent streams ran identical HILIC gradient methods on BEH-Amide (2 × 30 mm) columns. Each LC channel was run independently, and the cycle time was 2 min per channel. Overall throughput was 1 min per sample for the dual-channel integrated system. Multiply injected acquisition files were split during data review, and batch metadata were automatically paired with raw data during the review process. RESULTS: Two LC sorbents, BEH-Amide and Penta-HILIC, were tested to separate the NAAG cleavage product Glu from isobaric interference and ion suppressants in the bioassay matrix. Early elution of NAAG and NAA on BEH-Amide allowed interfering species to be diverted to waste. The limit of quantification was 0.1 pmol for Glu. The Z-factor of this assay averaged 0.85. Over 36 000 compounds were screened using this method. CONCLUSIONS: A fast gradient dual-stream LC/MS/MS method for Glu quantification in GCPII biochemical screening assay samples was developed and validated. HILIC separation chemistry offers robust performance and unique selectivity for targeted positive mode quantification of Glu, NAA, and NAAG.

Using differential mobility spectrometry to measure ion solvation: an examination of the roles of solvents and ionic structures in separating quinoline-based drugs.

Understanding the mechanisms and energetics of ion solvation is critical in many scientific areas. Here, we present a methodlogy for studying ion solvation using differential mobility spectrometry (DMS) coupled to mass spectrometry. While in the DMS cell, ions experience electric fields established by a high frequency asymmetric waveform in the presence of a desired pressure of water vapor. By observing how a specific ion's behavior changes between the high- and low-field parts of the waveform, we gain knowledge about the aqueous microsolvation of that ion. In this study, we applied DMS to investigate the aqueous microsolvation of protonated quinoline-based drug candidates. Owing to their low binding energies with water, the clustering propensity of 8-substituted quinolinium ions was less than that of the 6- or 7-substituted analogues. We attribute these differences to the steric hinderance presented by subtituents in the 8-position. In addition, these experimental DMS results were complemented by extensive computational studies that determined cluster structures and relative thermodynamic stabilities.

Target Class Profiling of Small-Molecule Methyltransferases.

Target class profiling (TCP) is a chemical biology approach to investigate understudied biological target classes. TCP is achieved by developing a generalizable assay platform and screening curated compound libraries to interrogate the chemical biological space of members of an enzyme family. In this work, we took a TCP approach to investigate inhibitory activity across a set of small-molecule methyltransferases (SMMTases), a subclass of methyltransferase enzymes, with the goal of creating a launchpad to explore this largely understudied target class. Using the representative enzymes nicotinamide N-methyltransferase (NNMT), phenylethanolamine N-methyltransferase (PNMT), histamine N-methyltransferase (HNMT), glycine N-methyltransferase (GNMT), catechol O-methyltransferase (COMT), and guanidinoacetate N-methyltransferase (GAMT), we optimized high-throughput screening (HTS)-amenable assays to screen 27,574 unique small molecules against all targets. From this data set, we identified a novel inhibitor which selectively inhibits the SMMTase HNMT and demonstrated how this platform approach can be leveraged for a targeted drug discovery campaign using the example of HNMT.

Suite of TMPRSS2 Assays for Screening Drug Repurposing Candidates as Potential Treatments of COVID-19.

SARS-CoV-2 is the causative viral pathogen driving the COVID-19 pandemic that prompted an immediate global response to the development of vaccines and antiviral therapeutics. For antiviral therapeutics, drug repurposing allows for rapid movement of the existing clinical candidates and therapies into human clinical trials to be tested as COVID-19 therapies. One effective antiviral treatment strategy used early in symptom onset is to prevent viral entry. SARS-CoV-2 enters ACE2-expressing cells when the receptor-binding domain of the spike protein on the surface of SARS-CoV-2 binds to ACE2 followed by cleavage at two cut sites by TMPRSS2. Therefore, a molecule capable of inhibiting the protease activity of TMPRSS2 could be a valuable antiviral therapy. Initially, we used a fluorogenic high-throughput screening assay for the biochemical screening of 6030 compounds in NCATS annotated libraries. Then, we developed an orthogonal biochemical assay that uses mass spectrometry detection of product formation to ensure that hits from the primary screen are not assay artifacts from the fluorescent detection of product formation. Finally, we assessed the hits from the biochemical screening in a cell-based SARS-CoV-2 pseudotyped particle entry assay. Of the six molecules advanced for further studies, two are approved drugs in Japan (camostat and nafamostat), two have entered clinical trials (PCI-27483 and otamixaban), while the other two molecules are peptidomimetic inhibitors of TMPRSS2 taken from the literature that have not advanced into clinical trials (compounds 92 and 114). This work demonstrates a suite of assays for the discovery and development of new inhibitors of TMPRSS2.

A Suite of TMPRSS2 Assays for Screening Drug Repurposing Candidates as Potential Treatments of COVID-19.

SARS-CoV-2 is the causative viral pathogen driving the COVID-19 pandemic that prompted an immediate global response to the development of vaccines and antiviral therapeutics. For antiviral therapeutics, drug repurposing allowed for rapid movement of existing clinical candidates and therapies into human clinical trials to be tested as COVID-19 therapies. One effective antiviral treatment strategy used early in symptom onset is to prevent viral entry. SARS-CoV-2 enters ACE2-expressing cells when the receptor-binding domain of the spike protein on the surface of SARS-CoV-2 binds to ACE2 followed by cleavage at two cut sites on the spike protein. TMPRSS2 has a protease domain capable of cleaving the two cut sites; therefore, a molecule capable of inhibiting the protease activity of TMPRSS2 could be a valuable antiviral therapy. Initially, we used a fluorogenic high-throughput screening assay for the biochemical screening of 6030 compounds in NCATS annotated libraries. Then, we developed an orthogonal biochemical assay that uses mass spectrometry detection of product formation to ensure that hits from the primary screen are not assay artifacts from the fluorescent detection of product formation. Finally, we assessed the hits from the biochemical screening in a cell-based SARS-CoV-2 pseudotyped particle entry assay. Of the six molecules advanced for further studies, two are approved drugs in Japan (camostat and nafamostat), two have entered clinical trials (PCI-27483 and otamixaban), while the other two molecules are peptidomimetic inhibitors of TMPRSS2 taken from the literature that have not advanced into clinical trials (compounds 92 and 114). This work demonstrates a suite of assays for the discovery and development of new inhibitors of TMPRSS2.

Perspectives on bioanalytical mass spectrometry and automation in drug discovery.

The use of high speed synthesis technologies has resulted in a steady increase in the number of new chemical entities active in the drug discovery research stream. Large organizations can have thousands of chemical entities in various stages of testing and evaluation across numerous projects on a weekly basis. Qualitative and quantitative measurements made using LC/MS are integrated throughout this process from early stage lead generation through candidate nomination. Nearly all analytical processes and procedures in modern research organizations are automated to some degree. This includes both hardware and software automation. In this review we discuss bioanalytical mass spectrometry and automation as components of the analytical chemistry infrastructure in pharma. Analytical chemists are presented as members of distinct groups with similar skillsets that build automated systems, manage test compounds, assays and reagents, and deliver data to project teams. The ADME-screening process in drug discovery is used as a model to highlight the relationships between analytical tasks in drug discovery. Emerging software and process automation tools are described that can potentially address gaps and link analytical chemistry related tasks. The role of analytical chemists and groups in modern 'industrialized' drug discovery is also discussed.

High throughput ADME screening: practical considerations, impact on the portfolio and enabler of in silico ADME models.

Evaluation and optimization of drug metabolism and pharmacokinetic data plays an important role in drug discovery and development and several reliable in vitro ADME models are available. Recently higher throughput in vitro ADME screening facilities have been established in order to be able to evaluate an appreciable fraction of synthesized compounds. The ADME screening process can be dissected in five distinct steps: (1) plate management of compounds in need of in vitro ADME data, (2) optimization of the MS/MS method for the compounds, (3) in vitro ADME experiments and sample clean up, (4) collection and reduction of the raw LC-MS/MS data and (5) archival of the processed ADME data. All steps will be described in detail and the value of the data on drug discovery projects will be discussed as well. Finally, in vitro ADME screening can generate large quantities of data obtained under identical conditions to allow building of reliable in silico models.

In vitro P-glycoprotein assays to predict the in vivo interactions of P-glycoprotein with drugs in the central nervous system.

Thirty-one structurally diverse marketed central nervous system (CNS)-active drugs, one active metabolite, and seven non-CNS-active compounds were tested in three P-glycoprotein (P-gp) in vitro assays: transwell assays using MDCK, human MDR1-MDCK, and mouse Mdr1a-MDCK cells, ATPase, and calcein AM inhibition. Additionally, the permeability for these compounds was measured in two in vitro models: parallel artificial membrane permeation assay and apical-to-basolateral apparent permeability in MDCK. The exposure of the same set of compounds in brain and plasma was measured in P-gp knockout (KO) and wild-type (WT) mice after subcutaneous administration. One drug and its metabolite, risperidone and 9-hydroxyrisperidone, of the 32 CNS compounds, and 6 of the 7 non-CNS drugs were determined to have positive efflux using ratio of ratios in MDR1-MDCK versus MDCK transwell assays. Data from transwell studies correlated well with the brain-to-plasma area under the curve ratios between P-gp KO and WT mice for the 32 CNS compounds. In addition, 3300 Pfizer compounds were tested in MDR1-MDCK and Mdr1a-MDCK transwell assays, with a good correlation (R(2) = 0.92) between the efflux ratios in human MDR1-MDCK and mouse Mdr1a-MDCK cells. Permeability data showed that the majority of the 32 CNS compounds have moderate to high passive permeability. This work has demonstrated that in vitro transporter assays help in understanding the role of P-gp-mediated efflux activity in determining the disposition of CNS drugs in vivo, and the transwell assay is a valuable in vitro assay to evaluate human P-gp interaction with compounds for assessing brain penetration of new chemical entities to treat CNS disorders.

Determining molecular properties with differential mobility spectrometry and machine learning.

The fast and accurate determination of molecular properties is highly desirable for many facets of chemical research, particularly in drug discovery where pre-clinical assays play an important role in paring down large sets of drug candidates. Here, we present the use of supervised machine learning to treat differential mobility spectrometry - mass spectrometry data for ten topological classes of drug candidates. We demonstrate that the gas-phase clustering behavior probed in our experiments can be used to predict the candidates' condensed phase molecular properties, such as cell permeability, solubility, polar surface area, and water/octanol distribution coefficient. All of these measurements are performed in minutes and require mere nanograms of each drug examined. Moreover, by tuning gas temperature within the differential mobility spectrometer, one can fine tune the extent of ion-solvent clustering to separate subtly different molecular geometries and to discriminate molecules of very similar physicochemical properties.

Discovery of Compounds that Positively Modulate the High Affinity Choline Transporter.

Cholinergic hypofunction is associated with decreased attention and cognitive deficits in the central nervous system in addition to compromised motor function. Consequently, stimulation of cholinergic neurotransmission is a rational therapeutic approach for the potential treatment of a variety of neurological conditions. High affinity choline uptake (HACU) into acetylcholine (ACh)-synthesizing neurons is critically mediated by the sodium- and pH-dependent high-affinity choline transporter (CHT, encoded by the SLC5A7 gene). This transporter is comparatively well-characterized but otherwise unexplored as a potential drug target. We therefore sought to identify small molecules that would enable testing of the hypothesis that positive modulation of CHT mediated transport would enhance activity-dependent cholinergic signaling. We utilized existing and novel screening techniques for their ability to reveal both positive and negative modulation of CHT using literature tools. A screening campaign was initiated with a bespoke compound library comprising both the Pfizer Chemogenomic Library (CGL) of 2,753 molecules designed specifically to help enable the elucidation of new mechanisms in phenotypic screens and 887 compounds from a virtual screening campaign to select molecules with field-based similarities to reported negative and positive allosteric modulators. We identified a number of previously unknown active and structurally distinct molecules that could be used as tools to further explore CHT biology or as a starting point for further medicinal chemistry.

Assessing Physicochemical Properties of Drug Molecules via Microsolvation Measurements with Differential Mobility Spectrometry.

The microsolvated state of a molecule, represented by its interactions with only a small number of solvent molecules, can play a key role in determining the observable bulk properties of the molecule. This is especially true in cases where strong local hydrogen bonding exists between the molecule and the solvent. One method that can probe the microsolvated states of charged molecules is differential mobility spectrometry (DMS), which rapidly interrogates an ion's transitions between a solvated and desolvated state in the gas phase (i.e., few solvent molecules present). However, can the results of DMS analyses of a class of molecules reveal information about the bulk physicochemical properties of those species? Our findings presented here show that DMS behaviors correlate strongly with the measured solution phase pKa and pKb values, and cell permeabilities of a set of structurally related drug molecules, even yielding high-resolution discrimination between isomeric forms of these drugs. This is due to DMS's ability to separate species based upon only subtle (yet predictable) changes in structure: the same subtle changes that can influence isomers' different bulk properties. Using 2-methylquinolin-8-ol as the core structure, we demonstrate how DMS shows promise for rapidly and sensitively probing the physicochemical properties of molecules, with particular attention paid to drug candidates at the early stage of drug development. This study serves as a foundation upon which future drug molecules of different structural classes could be examined.

Correction to "Assessing Physicochemical Properties of Drug Molecules via Microsolvation Measurements with Differential Mobility Spectrometry".

[This corrects the article DOI: 10.1021/acscentsci.6b00297.].

Optimizing higher throughput methods to assess drug-drug interactions for CYP1A2, CYP2C9, CYP2C19, CYP2D6, rCYP2D6, and CYP3A4 in vitro using a single point IC(50).

Drug-drug interactions involving cytochrome P(450) (CYP) are an important factor in whether a new chemical entity will survive through to the development stage. Therefore, the identification of this potential as early as possible in vitro could save considerable future unnecessary investment. In vitro CYP interaction screening data generated for CYP2C9, CYP2D6, and CYP3A4 were initially analyzed to determine the correlation of IC(50) from 10- and 3-point determinations. A high correlation (r = 0.99) prompted the further assessment of predicting the IC(50) by a single value of percent inhibition at either 10, 3, or 1 microM. Statistical analysis of the initial proprietary compounds showed that there was a strong linear relationship between log IC(50) and percent inhibition at 3 microM, and that it was possible to predict a compound's IC(50) by the percent inhibition value obtained at 3 microM. Additional data for CYP1A2, CYP2C19, and the recombinant CYP2D6 were later obtained and used together with the initial data to demonstrate that a single statistical model could be applicable across different CYPs and different in vitro microsomal systems. Ultimately, the data for all five CYPs and the recombinant CYP2D6 were used to build a statistical model for predicting the IC(50) with a single point. The 95% prediction boundary for the region of interest was about +/- 0.37 on log(10) scale, comparable to the variability of in vitro determinations for positive control IC(50) data. The use of a single inhibitor concentration would enable determination of more IC(50) values on a 96-well plate and result in more economical use of compounds, human liver or expressed enzyme microsomes, substrates, and reagents. This approach would offer the opportunity to increase screening for CYP-mediated drug-drug interactions, which may be important given the challenges provided by the generation of orders of magnitude more new chemical entities in the field of combinatorial chemistry. In addition, the algorithmic approach we propose would obviously be applicable for other in vitro bioactivity and therapeutic target enzyme and receptor screens.

Software automation tools for increased throughput metabolic soft-spot identification in early drug discovery.

BACKGROUND: The ability to supplement high-throughput metabolic clearance data with structural information defining the site of metabolism should allow design teams to streamline their synthetic decisions. However, broad application of metabolite identification in early drug discovery has been limited, largely due to the time required for data review and structural assignment. The advent of mass defect filtering and its application toward metabolite scouting paved the way for the development of software automation tools capable of rapidly identifying drug-related material in complex biological matrices. Two semi-automated commercial software applications, MetabolitePilot™ and Mass-MetaSite™, were evaluated to assess the relative speed and accuracy of structural assignments using data generated on a high-resolution MS platform. RESULTS/CONCLUSION: Review of these applications has demonstrated their utility in providing accurate results in a time-efficient manner, leading to acceleration of metabolite identification initiatives while highlighting the continued need for biotransformation expertise in the interpretation of more complex metabolic reactions.

Development of a high-speed, multiplexed sample-delivery instrument for LC-MS/MS bioanalysis.

BACKGROUND: The number of new chemical entities and types of in vitro and in vivo samples that require bioanalysis in drug discovery is large and diverse. In addition, method development time is limited as data turnaround is the highest priority. These circumstances require that a well-defined set of bioanalysis options be available in short timeframes to triage samples for analysis. METHOD: The Apricot Designs Dual Arm (ADDA) instrument is an LC-MS/MS sample delivery system that features a flexible hardware design coupled with software automation to enhance throughput in LC-MS/MS bioanalysis drug discovery. The instrument can perform high-throughput LC-MS/MS (8-10 s/sample) for screening and in vitro bioanalysis, as well as multiplexed LC for traditional gradient or isocratic LC approaches. The instrument control software is designed to integrate with DiscoveryQuant™ software (AB Sciex) and a global database of MS/MS conditions. CONCLUSION: Development of the sample delivery platform and its application in high-throughput and gradient LC will be described.

A centralized approach to tandem mass spectrometry method development for high-throughput ADME screening.

A centralized approach to acquisition and dissemination of tandem mass spectrometry (MS/MS) conditions within an ADME-screening bioanalytical mass spectrometry group has been developed. The method development process uses two automated software products (Autoscan and Automaton) specifically designed for mass spectrometers manufactured by MDS Sciex. Both provide the ability to quickly determine selected reaction monitoring (SRM) transitions for hundreds of compounds per day. In addition, Autoscan determines optimal polarity and collision energy (CE). Automaton also determines the optimal declustering potential (DP) as well as the CE. The resulting optimized conditions are loaded into a central database for access by LC/MS/MS bioanalysis workstations in the group. The effect of DP and CE on the sensitivity was investigated. Optimization of DP improved signal response about 27% on average. For approximately 10% of compounds, signal enhancement was greater than 50% compared to the generic setting. A generic setting of DP = 25 V can be used for the majority of ADME-screening applications. Optimization of CE can have a much larger impact on signal intensity and a minimum of three CE settings should be tested. We have determined that CE values of 1, 30 and 45 V provide adequate coverage for most small molecule drug discovery analytes.

Characterization and performance of MALDI on a triple quadrupole mass spectrometer for analysis and quantification of small molecules.

The usefulness of MALDI for small-molecule work has been limited by matrix chemical interference in the mass range of interest, tedious sample preparation, and various crystallization and sample deposition issues. We report instrument characterization and small-molecule quantification performance data from a high repetition rate laser MALDI ion source coupled to a triple quadrupole mass spectrometer. The high repetition rate laser improves sensitivity and precision and allows a proportional increase in sample throughput. Tandem mass spectrometry is used to discriminate the signal from the high chemical background caused by the MALDI matrix. Successful quantification requires use of an internal standard and a means of sample cleanup for typical in vitro sample compositions. This instrument combination and analysis technique is relatively insensitive to sample crystal quality and spot homogeneity. Quantitative performance results are characterized for 53 small-molecule pharmaceutical compounds and compared to those obtained by ESI-MS/MS. Further comparison between MALDI and ESI is examined, and the potential for high-throughput MALDI-MS/MS quantification is demonstrated.