Software aided approaches to structure-based metabolite identification in drug discovery and development

Meeting report of the 5th European Biotransformation Workshop

Challenges, strategies and new technologies in the field of biotransformation were presented and discussed at the 5th European Biotransformation Workshop, which was held on March 14, 2024 on the Novartis Campus in Basel, Switzerland.In this meeting report we summarise the presentations and discussions from this workshop.The topics covered are listed below:Advances in understanding drug induced liver injury (DILI) risks of carboxylic acids and targeted covalent inhibitors.Biotransformation of oligonucleotide-based therapeutics including automated software tools for metabolite identification.Recent advances in metabolite synthesisQualification and validation of a new compact Low Energy Accelerator Mass Spectrometry (LEA) system for metabolite profiling.

Comprehensive Metabolite Identification of Genipin in Rats Using Ultra-High-Performance Liquid Chromatography Coupled with High Resolution Mass Spectrometry

Genipin, an aglycone of geniposide, is a rich iridoid component in the fruit of Gardenia jasminoides Ellis and has numerous biological activities. However, its metabolic profiles in vivo and vitro remain unclear. In this study, an effective analytical strategy based on ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) in positive and negative ion modes was developed to analyze and identify genipin metabolites in rat urine, blood, feces, and fecal fermentation in combination with many methods including post-collection data mining methods, high-resolution extracted ion chromatography (HREIC), and multiple mass defect filtering (MMDF). Simultaneously, the metabolites of genipin in vivo were verified by fecal fermentation of SD rats at different times. Finally, based on information such as reference substances, chromatographic retention behavior, and accurate mass determination, a total of 50 metabolites (including prototypes) were identified in vivo. Among them, 7, 31 and 28 metabolites in vivo were identified in blood, urine, and feces, respectively. Our results showed that genipin could generate different metabolites that underwent multiple metabolic reactions in vivo including methylation, hydroxylation, dehydroxylation, hydrogenation, sulfonation, glucuronidation, demethylation, and their superimposed reactions. Forty-six metabolites were verified in vitro. Meanwhile, 2 and 19 metabolites identified in blood and urine were also verified in fecal fermentation at different times. These results demonstrated that metabolites were produced in feces and reabsorbed into the body. In conclusion, the newly discovered metabolites of genipin can provide a new perspective for understanding its pharmacological effects and build the foundation for thee toxicity and safety evaluations of genipin.

Unusual Biotransformation Reactions of Drugs and Drug Candidates

Detailed assessment of the fate of drugs in nonclinical test species and humans is essential to ensure the safety and efficacy of medicines in patients. In this context, biotransformation of drugs and drug candidates has been an area of keen interest over many decades in the pharmaceutical industry as well as academia. Although many of the enzymes and biotransformation pathways involved in the metabolism of xenobiotics and more specifically drugs have been well characterized, each drug molecule is unique and constitutes specific challenges for the biotransformation scientist. In this mini-review written for the special issue on the occasion of the 50th Anniversary celebration of Drug Metabolism and Disposition and to celebrate contributions of F. Peter Guengerich, one of the pioneers of the drug metabolism field, recently reported "unusual" biotransformation reactions are presented. Scientific and technological advances in the "toolbox" of the biotransformation scientists are summarized. As the pharmaceutical industry continues to explore therapeutic modalities different from the traditional small molecule drugs, the new challenges confronting the biotransformation scientist as well as future opportunities are discussed. SIGNIFICANCE STATEMENT: For the biotransformation scientists, it is essential to share and be aware of unexpected biotransformation reactions so that they can increase their confidence in predicting metabolites of drugs in humans to ensure the safety and efficacy of these metabolites before the medicines reach large numbers of patients. The purpose of this review is to highlight recent observations of "unusual" metabolites so that the scientists working in the area of drug metabolism can strengthen their readiness in expecting the unexpected.

Sartan blood pressure regulators in classical and biofilm wastewater treatment - Concentrations and metabolism

Sartans are a group of pharmaceuticals widely used to regulate blood pressure. Their concentration levels were monitored in 80 wastewater treatment plants (WWTP) in the Baltic Sea Region, reached from limit of detection up to 6 µg/L. The concentrations were significantly different in different countries, but consistent within the respective country. The degradation of sartans (losartan, valsartan, irbesartan) in moving bed biofilm reactors (MBBRs) that utilize biofilms grown on mobile carriers to treat wastewater was investigated for the first time, and compared with the degradation in a conventional activated sludge (CAS) treatment plant. The results showed the formation of six microbial transformation products (TPs) of losartan, four of valsartan, and four of irbesartan in biological wastewater treatment. Four of these metabolites have not been described in the literature before. Chemical structures were suggested and selected TPs were verified and quantified depending on availability of true standards. Valsartan acid was a common TP of losartan, valsartan, and irbesartan. Losartan and irbesartan also shared one TP: losartan/irbesartan TP335. Based on the mass balance analysis, losartan carboxylic acid is the main TP of losartan, and valsartan acid is the main TP of valsartan during the biotransformation process. For irbesartan, TP447 is likely to be the main TP, as its peak areas were two orders of magnitude higher than those of all the other detected TPs of this compound. The effects of adapting biofilms to different biological oxygen demand (BOD) loading on the degradation of sartans as well as the formation of their TPs were investigated. Compared to feeding a poor substrate (pure effluent wastewater from a CAS), feeding with richer substrate (1/3 raw and 2/3 effluent wastewater) promoted the metabolism of most compounds (co-metabolization). However, the addition of raw wastewater inhibited some metabolic pathways of other compounds, such as from losartan/irbesartan to TP335 (competitive inhibition). The formation of irbesartan TP447 did not change with or without raw wastewater. Finally, the sartans and their TPs were investigated in a full-scale CAS wastewater treatment plant (WWTP). The removal of losartan, valsartan, and irbesartan ranged from 3.0 % to 72% and some of the transformation products (TPs) from human metabolism were also removed in the WWTP. However, some of the sartan TPs, i.e., valsartan acid, losartan carboxylic acid, irbesartan TP443 and losartan TP453, were formed in the WWTP. Relative high amounts of especially losartan carboxylic acid, which was detected with concentrations up to 2.27 µg/L were found in the effluent.

A Discovery Biotransformation Strategy: Combining In Silico Tools with High-Resolution Mass Spectrometry and Software-Assisted Data Analysis for High-Throughput Metabolism

Understanding compound metabolism in early drug discovery aids medicinal chemistry in designing molecules with improved safety and ADME properties. While advancements in metabolite prediction brings increasedconfidence, structural decisions require experimental data. In vitro metabolism studies using liquid chromatography and high-resolution mass spectrometry (LC-MS) are generally resource intensive and performed on very few compounds, limiting the chemical space that can be examined.Here, we describe a novel metabolism strategy increasing compound throughput using residual in vitro clearance samples conducted at drug concentrations of 0.5 µM. Analysis by robust UHPLC separation and accurate-mass MS detection ensures major metabolites are identified from a single injection. In silico prediction (parent cLogD) tailors chromatographic conditions, with data-dependent MS/MS targeting predicted metabolites. Software-assisted data mining, structure elucidation and automatic reporting are used.Confidence in the globally-aligned workflow is demonstrated with sixteen marketed drugs. The approach is now implemented routinely across our laboratories. To date, the success rate for identification of at least one major metabolite is 85%. The utility of these data has been demonstrated across multiple projects, allowing earlier medicinal chemistry decisions to increase efficiency and impact of the design-make-test cycle; thus improving the translatability of early in vitro metabolism data.

Molecular docking analysis of modified gedunin from neem with snake venom enzymes

Snakebites are a problem due to the increasing number of deaths and permanent disabilities. There is currently a shortage of antidotes for snakebite. The existing antibody antidote, produced from horse/sheep plasma/sera is expensive, species-dependent, and causes fatal side effects. Therefore, it is of interest use of natural flavonoid named gedunin from the Azadirachta indica (Neem) plant species to combat snakebites. Thus, we show the molecular docking analysis of gedunin (C26H31N2O6F) with enzymes (common in snake species) such as 5-nucleotidase, acetyl cholinesterase, L-aao, metalloproteinase, serine, thrombin and phospholipase A2. The modified gedunin in the enzyme pocket showed improved pharmacological properties for further consideration in combating snakebites.

Automatic Identification of Lansoprazole Degradants under Stress Conditions by LC-HRMS with MassChemSite and WebChembase

Stress testing is one of the most important parts of the drug development process, helping to foresee stability problems and to identify degradation products. One of the processes involving stress testing is represented by forced degradation studies, which can predict the impact of certain conditions of pH, moisture, heat, or other negative effects due to transportation or packaging issues on drug potency and purity, ensuring patient safety. Regulatory agencies have been working on a standardization of laboratory procedures since the past two decades. One of the results of those years of intensive research is the International Conference on Harmonization (ICH) guidelines, which clearly define which forced degradation studies should be performed on new drugs, which become a routine work in pharmaceutical laboratories. Since used techniques based on high-performance liquid chromatography coupled with high-resolution mass spectrometry have been developed years ago and are now mastered by pharmaceutical scientists, automation of data analysis, and thus data processing, is becoming a hot topic nowadays. In this work, we present MassChemSite and WebChembase as a tandem to automatize the routine analysis studies without missing information quality, using as a case study the degradation of lansoprazole under acidic, oxidative, basic, and neutral stress conditions.

Metabolite identification using an ion mobility enhanced data-independent acquisition strategy and automated data processing

RATIONALE

Liquid chromatography/mass spectrometry is an essential tool for efficient and reliable quantitative and qualitative analysis and underpins much of contemporary drug metabolism and pharmacokinetics. Data-independent acquisition methods such as MS^E have reduced the potential to miss metabolites, but do not formally generate quadrupole-resolved product ion spectra. The addition of ion mobility separation to these approaches, for example, in High-Definition MS^E (HDMS^E ) has the potential to reduce the time needed to set up an experiment and maximize the chance that all metabolites present can be resolved and characterized. We compared High-Definition Data-Dependent Acquisition (HD-DDA), MS^E and HDMS^E approaches using automated software processing with Mass-MetaSite and WebMetabase.

METHODS

Metabolite identification was performed on incubations of glucagon-like peptide-1 (7-37) (GLP-1) and verapamil hydrochloride. The HD-DDA, MS^E and HDMS^E experiments were conducted on a Waters ACQUITY UPLC I-Class LC system with a VION IMS quadrupole time-of-flight (QTOF) mass spectrometer operating under UNIFI control. All acquired data were processed using MassMetaSite able to read data from UNIFI 1.9.4. WebMetabase was used to review the detected chromatographic peaks and the spectral data interpretations.

RESULTS

A comparison of outcomes obtained for MS^E and HDMS^E data demonstrated that the same structures were proposed for metabolites of both verapamil and GLP-1. The ratio of structurally matched to mismatched product ions found by MassMetaSite was slightly greater for HDMS^E than for MS^E , and HD-DDA, thus improving confidence in the structures proposed through the addition of ion mobility based data acquisitions_. CONCLUSIONS: HDMS^E data acquisition is an effective approach for the elucidation of metabolite structures for both small molecules and peptides, with excellent accuracy and quality, requiring minimal tailoring for the compound under investigation.

A tutorial in small molecule identification via electrospray ionization-mass spectrometry: The practical art of structural elucidation

The identification of unknown molecules has been one of the cornerstone applications of mass spectrometry for decades. This tutorial reviews the basics of the interpretation of electrospray ionization-based MS and MS/MS spectra in order to identify small-molecule analytes (typically below 2000 Da). Most of what is discussed in this tutorial also applies to other atmospheric pressure ionization methods like atmospheric pressure chemical/photoionization. We focus primarily on the fundamental steps of MS-based structural elucidation of individual unknown compounds, rather than describing strategies for large-scale identification in complex samples. We critically discuss topics like the detection of protonated and deprotonated ions ([M + H]+ and [M - H]- ) as well as other adduct ions, the determination of the molecular formula, and provide some basic rules on the interpretation of product ion spectra. Our tutorial focuses primarily on the fundamental steps of MS-based structural elucidation of individual unknown compounds (eg, contaminants in chemical production, pharmacological alteration of drugs), rather than describing strategies for large-scale identification in complex samples. This tutorial also discusses strategies to obtain useful orthogonal information (UV/Vis, H/D exchange, chemical derivatization, etc) and offers an overview of the different informatics tools and approaches that can be used for structural elucidation of small molecules. It is primarily intended for beginning mass spectrometrists and researchers from other mass spectrometry sub-disciplines that want to get acquainted with structural elucidation are interested in some practical tips and tricks.

Software-aided approach to investigate peptide structure and metabolic susceptibility of amide bonds in peptide drugs based on high resolution mass spectrometry

Interest in using peptide molecules as therapeutic agents due to high selectivity and efficacy is increasing within the pharmaceutical industry. However, most peptide-derived drugs cannot be administered orally because of low bioavailability and instability in the gastrointestinal tract due to protease activity. Therefore, structural modifications peptides are required to improve their stability. For this purpose, several in-silico software tools have been developed such as PeptideCutter or PoPS, which aim to predict peptide cleavage sites for different proteases. Moreover, several databases exist where this information is collected and stored from public sources such as MEROPS and ExPASy ENZYME databases. These tools can help design a peptide drug with increased stability against proteolysis, though they are limited to natural amino acids or cannot process cyclic peptides, for example. We worked to develop a new methodology to analyze peptide structure and amide bond metabolic stability based on the peptide structure (linear/cyclic, natural/unnatural amino acids). This approach used liquid chromatography / high resolution, mass spectrometry to obtain the analytical data from in vitro incubations. We collected experimental data for a set (linear/cyclic, natural/unnatural amino acids) of fourteen peptide drugs and four substrate peptides incubated with different proteolytic media: trypsin, chymotrypsin, pepsin, pancreatic elastase, dipeptidyl peptidase-4 and neprilysin. Mass spectrometry data was analyzed to find metabolites and determine their structures, then all the results were stored in a chemically aware manner, which allows us to compute the peptide bond susceptibility by using a frequency analysis of the metabolic-liable bonds. In total 132 metabolites were found from the various in vitro conditions tested resulting in 77 distinct cleavage sites. The most frequent observed cleavage sites agreed with those reported in the literature. The main advantages of the developed approach are the abilities to elucidate metabolite structure of cyclic peptides and those containing unnatural amino acids, store processed information in a searchable format within a database leading to frequency analysis of the labile sites for the analyzed peptides. The presented algorithm may be useful to optimize peptide drug properties with regards to cleavage sites, stability, metabolism and degradation products in drug discovery.

Development, optimization and implementation of a centralized metabolic soft spot assay

AIM

High clearance is a commonly encountered issue in drug discovery. Here we present a centralized metabolic soft spot identification assay with adequate capacity and turnaround time to support the metabolic optimization needs of an entire discovery organization.

METHODOLOGY

An integrated quan/qual approach utilizing both an orthogonal sample-pooling methodology and software-assisted structure elucidation was developed to enable the assay. Major metabolic soft spots in liver microsomes (rodent and human) were generated in a batch mode, along with kinetics of parent disappearance and metabolite formation, typically within 1 week of incubation.

RESULTS & CONCLUSION

A centralized metabolic soft spot identification assay has been developed and has successfully impacted discovery project teams in mitigating instability and establishing potential structure-metabolism relationships.

Enhanced dereplication of fungal cultures via use of mass defect filtering

Effective and rapid dereplication is a hallmark of present-day drug discovery from natural sources. This project strove to both decrease the time and expand the structural diversity associated with dereplication methodologies. A 5 min liquid chromatographic run time employing heated electrospray ionization (HESI) was evaluated to determine whether it could be used as a faster alternative over the 10 min ESI method we reported previously. Results revealed that the 5 min method was as sensitive as the 10 min method and, obviously, was twice as fast. To facilitate dereplication, the retention times, UV absorption maxima, full-scan HRMS and MS/MS were cross-referenced with an in-house database of over 300 fungal secondary metabolites. However, this strategy was dependent upon the makeup of the screening in-house database. Thus, mass defect filtering (MDF) was explored as an additional targeted screening strategy to permit identification of structurally related components. The use of a dereplication platform incorporating the 5 min chromatographic method together with MDF facilitated rapid and effective identification of known compounds and detection of structurally related analogs in extracts of fungal cultures.

In-Depth Proteomic Analysis of the Porcine Retina by Use of a four Step Differential Extraction Bottom up LC MS Platform

The eye of the house swine (Sus scrofa domestica Linnaeus, 1758) represents a promising model for the study of human eye diseases encircling neurodegenerative retina disorders that go along with proteomic changes. To provide an in-depth view into the "normal" (untreated & healthy) porcine retina proteome as an important reference, a proteomic strategy has been developed encircling stepwise/differential extraction, LC MS and peptide de novo sequencing. Accordingly, pooled porcine retina homogenates were processed by stepwise DDM, CHAPS, ASB14 and ACN/TFA extraction. Retinal proteins were fractionated by 1D-SDS PAGE and further analyzed by LC ESI MS following database and de novo sequencing related protein identification and functional analyses. In summary, >2000 retinal proteins (FDR < 1 %) could be identified by use of the highly reproducible and selective extraction procedure. Moreover, an identification surplus of 36 % comparing initial one step extraction to the four step method could be documented. Despite most proteins were identified in the DDM and CHAPS fraction, all extraction steps contributed exclusive proteins with nucleus proteins enriched in the final ACN/TFA fraction. Additionally, for the first time new non-annotated de novo peptides could be documented for the porcine retina. The generated porcine retina proteome reference map contributes importantly to the understanding of the pig eye proteome and the developed workflow has strong translational potential considering retina studies of various species.

Identification and comparative oridonin metabolism in different species liver microsomes by using UPLC-Triple-TOF-MS/MS and PCA

Oridonin (ORI) is an active natural ent-kaurene diterpenoid ingredient with notable anti-cancer and anti-inflammation activities. Currently, a strategy was developed to identify metabolites and to assess the metabolic profiles of ORI in vitro using ultra-high-performance liquid chromatography-Triple/time-of-flight mass spectrometry (UPLC-Triple-TOF-MS/MS). Meanwhile, the metabolism differences of ORI in the liver microsomes of four different species were investigated using a principal component analysis (PCA) based on the metabolite absolute peak area values as the variables. Based on the proposed methods, 27 metabolites were structurally characterized. The results indicate that ORI is universally metabolized in vitro, and the metabolic pathway mainly includes dehydration, hydroxylation, di-hydroxylation, hydrogenation, decarboxylation, and ketone formation. Overall, there are obvious inter-species differences in types and amounts of ORI metabolites in the four species. These results will provide basic data for future pharmacological and toxicological studies of ORI and for other ent-kauranes diterpenoids. Meanwhile, studying the ORI metabolic differences helps to select the proper animal model for further pharmacology and toxicological assessment.

Software-aided cytochrome P450 reaction phenotyping and kinetic analysis in early drug discovery

RATIONALE

Cytochrome P450 (CYP450) reaction phenotyping (CRP) and kinetic studies are essential in early drug discovery to determine which metabolic enzymes react with new drug entities. A new semi-automated computer-assisted workflow for CRP is introduced in this work. This workflow provides not only information regarding parent disappearance, but also metabolite identification and relative metabolite formation rates for kinetic analysis.

METHODS

Time-course experiments based on incubating six probe substrates (dextromethorphan, imipramine, buspirone, midazolam, ethoxyresorufin and diclofenac) with recombinant human enzymes (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) and human liver microsomes (HLM) were performed. Liquid chromatography/high-resolution mass spectrometry (LC/HRMS) analysis was conducted with an internal standard to obtain high-resolution full-scan and MS/MS data. Data were analyzed using Mass-MetaSite software. A server application (WebMetabase) was used for data visualization and review.

RESULTS

CRP experiments were performed, and the data were analyzed using a software-aided approach. This automated-evaluation approach led to (1) the detection of the CYP450 enzymes responsible for both substrate depletion and metabolite formation, (2) the identification of specific biotransformations, (3) the elucidation of metabolite structures based on MS/MS fragment analysis, and (4) the determination of the initial relative formation rates of major metabolites by CYP450 enzymes.

CONCLUSIONS

This largely automated workflow enabled the efficient analysis of HRMS data, allowing rapid evaluation of the involvement of the main CYP450 enzymes in the metabolism of new molecules during drug discovery.

Metabolic activation and drug-induced liver injury: in vitro approaches for the safety risk assessment of new drugs

Drug-induced liver injury (DILI) is a significant leading cause of hepatic dysfunction, drug failure during clinical trials and post-market withdrawal of approved drugs. Many cases of DILI are unexpected reactions of an idiosyncratic nature that occur in a small group of susceptible individuals. Intensive research efforts have been made to understand better the idiosyncratic DILI and to identify potential risk factors. Metabolic bioactivation of drugs to form reactive metabolites is considered an initiation mechanism for idiosyncratic DILI. Reactive species may interact irreversibly with cell macromolecules (covalent binding, oxidative damage), and alter their structure and activity. This review focuses on proposed in vitro screening strategies to predict and reduce idiosyncratic hepatotoxicity associated with drug bioactivation. Compound incubation with metabolically competent biological systems (liver-derived cells, subcellular fractions), in combination with methods to reveal the formation of reactive intermediates (e.g., formation of adducts with liver proteins, metabolite trapping or enzyme inhibition assays), are approaches commonly used to screen the reactivity of new molecules in early drug development. Several cell-based assays have also been proposed for the safety risk assessment of bioactivable compounds. Copyright © 2015 John Wiley & Sons, Ltd.

Software-aided structural elucidation in drug discovery

RATIONALE

Structural information on metabolites obtained in relevant biological systems can have considerable impact on the design of new drug candidates. However, with demanding turnaround times, the amount of available structural information may become rate limiting.

METHODS

The workflow for metabolite identification used in our laboratory was compared to a workflow using a software tool built for computer-assisted metabolite identification. The present study covered the in vitro metabolism of a diverse set of 65 in-house compounds. The compounds were profiled across three liver-based systems, 17 compounds were tested in human liver microsomes (HLM), 12 in rat hepatocytes (RHEP), and 36 in human hepatocytes (HHEP).

RESULTS

For 92% of the metabolites reported, the exact match or Markush representations were in agreement between the two workflows. The major specific biotransformations in hepatocytes which formed the metabolites were aromatic or aliphatic hydroxylations (33%), N-dealkylations (15%) and glucuronidations (12%).

CONCLUSIONS

The software was shown to perform well for structural elucidation of metabolites from both phase I and phase II metabolism where the focus was on quickly understanding the rate-limiting metabolic step(s).