Identifying Protein–Drug Interactions in Cell Lysates Using Histidine Hydrogen Deuterium Exchange

Abstract

Identifying the targets of a drug is critical to understand the mechanism of action and predicts possible side effects. The conventional approach is capturing interacting proteins by affinity purification. However, it requires drugs to be immobilized to a solid support or derivatized with chemical moieties used for pulling down interacting proteins. Such covalent modifications to drugs may mask a critical recognition site for or alter the binding affinity to their targets. To overcome the drawback, several methods that do not require covalent modifications to drugs have been developed. These methods identify targets by detecting proteins whose thermodynamic stability is enhanced in the presence of drugs. Although the utility of these methods has been demonstrated, the difficulty in identifying low abundant targets is the common problem of these methods. We have developed a new target identification method that increases the likelihood of identifying low abundant targets. The method uses histidine-hydrogen deuterium exchange (His-HDX) as a readout technique to probe the changes in protein stability induced by drugs. The workflow involves incubating cell lysates in various concentrations of a protein denaturant in the presence and absence of a drug in D 2 O followed by digestion of the proteins, enrichment of His-containing peptides, and analysis of the enriched His-peptides by liquid chromatography−tandem mass spectrometry (LC−MS/MS). The developed method was successfully applied to identify the interaction between endogenously expressed MAPK14 and its inhibitor in HEK293 cell lysates. The implementation of selective enrichment of histidine-containing peptides in the workflow was a key that enabled identifying the MAPK14−inhibitor interaction.

Advances in Mass Spectrometry‐Based Structural Proteomics: Development of HDX‐MS and XL‐MS Techniques from Recombinant Protein to Cellular Systems

“…Their group tested the inhibitory kinetics of ligands that demonstrate slow binding kinetics versus fast binding kinetics to MAPK14. They were able to detect the protein‐ligand interaction via histidine HDX‐MS both in vitro and in cellulo for either ligand [50] . These identifiable interactions were enhanced by increasing guanidine hydrochloride concentrations in similar fashion to TPP coupled to HDX‐MS described above, since the MAPK14 ligands protected the protein from denaturation.…”

“…They were able to detect the protein-ligand interaction via histidine HDX-MS both in vitro and in cellulo for either ligand. [50] These identifiable interactions were enhanced by increasing guanidine hydrochloride concentrations in similar fashion to TPP coupled to HDX-MS described above, since the MAPK14 ligands protected the protein from denaturation. Lastly, they also implemented an enrichment step via immobilized metal affinity chromatography (IMAC) to select histidine-tagged and histidine-containing proteins, which helped in their overall identification rate as it further reduced sample complexity.…”

“…Lastly, they also implemented an enrichment step via immobilized metal affinity chromatography (IMAC) to select histidine-tagged and histidine-containing proteins, which helped in their overall identification rate as it further reduced sample complexity. [50] This technique provides unique advantages to conventional HDX-MS by increasing the half-life of deuterated peptides, but at the cost of longer protein incubation times to allow sufficient histidine HDX to occur. In terms of moving HDX-MS into an in cellulo system, histidine HDX is a useful tool for measuring native proteinligand or protein-protein dynamics and retaining those interactions for longer LC gradients to reduce back-exchange.…”

“…They were able to show that the stability of histidine HDX could also inform protein‐ligand interactions for the hemoglobin‐haptoglobin complex [49] . Other groups, like the Kishimoto group, leveraged the longer intrinsic exchange rates to assess protein‐drug interactions in mammalian cells [50] . Their group tested the inhibitory kinetics of ligands that demonstrate slow binding kinetics versus fast binding kinetics to MAPK14.…”

Statistical Bioinformatics to Uncover the Underlying Biological Mechanisms That Linked Smoking with Type 2 Diabetes Patients Using Transcritpomic and GWAS Analysis

“…We have used the DESeq2 package [ 28 ] which is frequently used for differential gene expression analysis of RNA-seq count data. We identified commonly dysregulated genes, pathways and Gene Ontology (GO) protein–protein interaction (PPI) [ 28 ], hub-proteins [ 29 ], Transcription Factor Gene Interactions [ 30 ], Gene miRNA Interaction [ 31 ], Protein–Drug Interaction [ 32 ]; that are associated with T2D and smoker using a systems biology approach. Finally, we have analysed common genes, pathways and GO using GWAS datasets [ 33 ]; later, we discuss and compare with transcriptomic analysis.…”