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

Understanding the Metabolism of Proteolysis Targeting Chimeras (PROTACs): The Next Step toward Pharmaceutical Applications

Hetero-bifunctional PROteolysis TArgeting Chimeras (PROTACs) represent a new emerging class of small molecules designed to induce polyubiquitylation and proteasomal-dependent degradation of a target protein. Despite the increasing number of publications about the synthesis, biological evaluation, and mechanism of action of PROTACs, the characterization of the pharmacokinetic properties of this class of compounds is still minimal. Here, we report a study on the metabolism of a series of 40 PROTACs in cryopreserved human hepatocytes at multiple time points. Our results indicated that the metabolism of PROTACs could not be predicted from that of their constituent ligands. Their linkers' chemical nature and length resulted in playing a major role in the PROTACs' liability. A subset of compounds was also tested for metabolism by human cytochrome P450 3A4 (CYP3A4) and human aldehyde oxidase (hAOX) for more in-depth data interpretation, and both enzymes resulted in active PROTAC metabolism.

Drug metabolite identification using ultrahigh-performance liquid chromatography-ultraviolet spectroscopy and parallelized scans on a tribrid Orbitrap mass spectrometer

RATIONALE

To capture all metabolites in metabolite identification studies, MS/MS information is required in both positive and negative ionization mode, usually involving several sample injections to gain all information about samples. A high-resolution and high mass accuracy quadrupole/linear trap/Orbitrap tribrid instrument was used to gain this information in a novel single injection 'capture-all' approach to metabolite identification.

METHODS

Diclofenac, a model compound, was incubated in human and rat hepatocytes. These incubated samples were run using an ultrahigh-performance liquid chromatography/ultraviolet (UHPLC-UV) system coupled to a Thermo Fusion tribrid mass spectrometer. Five parallel scans were used: positive and negative ion full scan, data-dependent MS/MS, both high energy dissociation and collision-induced dissociation, and data-independent all ion fragmentation (AIF) spectra were collected in positive and negative ion mode.

RESULTS

Nine metabolites were identified; a metabolite observed in the UV trace, but not positive ion full scan MS, was detected in the same sample injection by negative ion full scan MS. This was identified as a sulphate metabolite, and the corresponding negative ion AIF allowed for some structural elucidation. The use of a photo-diode array (PDA) detector allowed for spectral assessment in case of changes in absorbance spectra, and the subsequent semi-quantification of metabolites.

CONCLUSIONS

This method provided good-quality MS/MS data across the m/z range in both positive and negative ion mode. The addition of both negative ion full scan MS and negative ion MS/MS allowed for the detection and structural elucidation of metabolites not observed in positive ion mode. The use of the PDA detector allowed for the semi-quantification of metabolites.

COMPLEX ASSESSMENT OF EFFICACY OF STATINS PRESCRIBED AT MOST BY CLINICIANS

Aim. To evaluate a complex clinical efficacy, tolerability and safety of statin drugs — simvastatin, atorvastatin, rosuvastatin in patients with hyperlipidemia (HL).

Material and methods. The assessment of clinical efficacy was done in 90 patients with HL and arterial hypertension of the grades 1 and 2, age 40-75 y.o.; some of them had coronary heart disease.

Results. In 90 patients with cardiac pathology and HL, selected to 3 groups by 30 persons, the clinical efficacy of the listed statins was assessed. A significant hypolipidemic effect was noted as a decline of atherogenicity of the blood, with slight more prominent effect of rosuvastatin.

Conclusion. The data makes it to conclude the simvastatin, atorvastatin and rosuvastatin are equally effective hypolipidemic drugs in HL type IIA and IIB patients. The time frame, type and grade of positive changes in lipid profile are almost the same, and in rosuvastatin just slightly more prominent.

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.

A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). The Pearson correlation coefficient between experimental data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47 (k-ecoli457 is available for download at http://www.maranasgroup.com).

Recent developments in software tools for high-throughput in vitro ADME support with high-resolution MS

The last several years have seen the rapid adoption of the high-resolution MS (HRMS) for bioanalytical support of high throughput in vitro ADME profiling. Many capable software tools have been developed and refined to process quantitative HRMS bioanalysis data for ADME samples with excellent performance. Additionally, new software applications specifically designed for quan/qual soft spot identification workflows using HRMS have greatly enhanced the quality and efficiency of the structure elucidation process for high throughput metabolite ID in early in vitro ADME profiling. Finally, novel approaches in data acquisition and compression, as well as tools for transferring, archiving and retrieving HRMS data, are being continuously refined to tackle the issue of large data file size typical for HRMS analyses.

High-resolution mass spectrometry in toxicology: current status and future perspectives

This paper reviews high-resolution mass spectrometry (HRMS) approaches using time-of-flight or Orbitrap techniques for research and application in various toxicology fields, particularly in clinical toxicology and forensic toxicology published since 2013 and referenced in PubMed. In the introduction, an overview on applications of HRMS in various toxicology fields is given with reference to current review articles. Papers concerning HRMS in metabolism, screening, and quantification of pharmaceuticals, drugs of abuse, and toxins in human body samples are critically reviewed. Finally, a discussion on advantages as well as limitations and future perspectives of these methods is included.