MS methods to study macromolecule-ligand interaction: Applications in drug discovery

Investigating the Metabolic Mechanisms of Butaselen, An Ebselen Analog

BACKGROUND

Butaselen is an ebselen analog that is under clinical trials for treating hepatic and pulmonary fibrosis. Our previous studies showed that butaselen is mainly present in human plasma in the form of M2, a free Se-methylated metabolite.

OBJECTIVE

This study aimed to investigate the metabolic mechanisms of butaselen.

METHODS AND RESULTS

Butaselen was incubated with human plasma. Butaselen immediately disappeared, and the butaselen-HSA (human serum albumin) adduct was detected by HPLC-HRMS, showing that butaselen covalently binds to HSA. The butaselen-HSA adduct was precipitated using acetonitrile and then incubated with PBS, Cys, and GSH for 1 hour. The product was M1, a reduced form of butaselen. The results indicated that HSA, Cys, and GSH can reduce the butaselen-HSA covalent bond. The binding site for butaselen could be the cysteine-34 residue of HSA through pronase and trypsin hydrolysis. Incubating butaselen with cysteine, butaselen-Cys, butaselen-2Cys, and M1 were generated, indicating the covalent binding and reduction of butaselen by cysteine. We incubated liver microsomes and cytosol with butaselen, 6.22 and 246 nM M2 were generated, respectively. The results demonstrated that cytosolic enzymes are mainly involved in M2 production. The amount of M2 in the liver cytosol decreased from 246 nM to 2.21 nM when 10 mM m-anisic acid (a specific TPMT enzyme inhibitor) was added, showing that TPMT is responsible for M2 formation.

CONCLUSION

Butaselen was covalently bound to HSA, and the binding site was the cysteine-34 residue of HSA. The butaselen-HSA adduct was reduced by free thiol compounds to generate M1. M1 was further metabolized to M2 by cytosolic TPMT. This study provides a basis for studying the pharmacokinetics of selenium-containing drugs.

Efficient discovery of potential inhibitors for SARS-CoV-2 3C-like protease from herbal extracts using a native MS-based affinity-selection method

The 3C-like protease (3CLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential to the virus life cycle and is supposed to be a potential target for the treatment of coronaviral infection. Traditional Chinese medicines (TCMs) have played an impressive role in the treatment of COVID-19 in China. The effectiveness of TCM formulations prompts scientists to take continuous effort on searching for bioactive small molecules from the ancient resources. Herein, we developed a native mass spectrometry-based affinity-selection method for rapid screening of active small molecules from crude herbal extracts applied for COVID-19 therapy. Six common herbs named Lonicera japonica, Scutellaria baicalensis, Forsythia suspensa, Glycyrrhiza uralensis, Cirsium japonicum, and Andrographis paniculata were investigated. After preliminary separation of the crude extracts, the fractions were incubated with 3CLpro. A native MS-based affinity screening assay was then conducted to search for the protein-ligand complexes. A UHPLC-Q/TOF-MS with UNIFI data acquisition and data processing software was applied to identify the hit compounds. Standard compounds were used to verify the outcomes. Among the 16 hits, three flavonoids, baicalein, scutellarein and ganhuangenin, were identified as potential noncovalent inhibitors against 3CLpro with IC₅₀ values of 0.94, 3.02, and 0.84 μM, respectively. Their binding affinities were further characterized by native MS, with K_d values being 1.43, 3.85, and 1.09 μM, respectively. Overall, we established an efficient native MS-based strategy for discovering 3CLpro ligands from crude mixtures, which supplies a potential strategy of small molecule lead discovery from TCMs.

Target-Directed Approaches for Screening Small Molecules against RNA Targets

RNA molecules have a variety of cellular functions that can drive disease pathologies. They are without a doubt one of the most intriguing yet controversial small-molecule drug targets. The ability to widely target RNA with small molecules could be revolutionary, once the right tools, assays, and targets are selected, thereby defining which biomolecules are targetable and what constitutes drug-like small molecules. Indeed, approaches developed over the past 5-10 years have changed the face of small molecule-RNA targeting by addressing historic concerns regarding affinity, selectivity, and structural dynamics. Presently, selective RNA-protein complex stabilizing drugs such as branaplam and risdiplam are in clinical trials for the modulation of SMN2 splicing, compounds identified from phenotypic screens with serendipitous outcomes. Fully developing RNA as a druggable target will require a target engagement-driven approach, and evolving chemical collections will be important for the industrial development of this class of target. In this review we discuss target-directed approaches that can be used to identify RNA-binding compounds and the chemical knowledge we have today of small-molecule RNA binders.

Synergistic Structural Information from Covalent Labeling and Hydrogen-Deuterium Exchange Mass Spectrometry for Protein-Ligand Interactions

Hydrogen-deuterium exchange (HDX) mass spectrometry (MS) and covalent labeling (CL) MS are typically considered to be complementary methods for protein structural analysis, because one probes the protein backbone, while the other probes side chains. For protein-ligand interactions, we demonstrate in this work that the two labeling techniques can provide synergistic structural information about protein-ligand binding when reagents like diethylpyrocarbonate (DEPC) are used for CL because of the differences in the reaction rates of DEPC and HDX. Using three model protein-ligand systems, we show that the slower time scale for DEPC labeling makes it only sensitive to changes in solvent accessibility and insensitive to changes in protein structural fluctuations, whereas HDX is sensitive to changes in both solvent accessibility and structural fluctuations. When used together, the two methods more clearly reveal binding sites and ligand-induced changes to structural fluctuations that are distant from the binding site, which is more comprehensive information than either technique alone can provide. We predict that these two methods will find widespread usage together for more deeply understanding protein-ligand interactions.