Accelerating multiplexed profiling of protein-ligand interactions: High-throughput plate-based reactive cysteine profiling with minimal input

Abstract

Chemoproteomics has made significant progress in investigating small-molecule-protein interactions. However, the proteome-wide profiling of cysteine ligandability remains challenging to adapt for high-throughput applications, primarily due to a lack of platforms capable of achieving the desired depth using low input in 96- or 384-well plates. Here, we introduce a revamped, plate-based platform which enables routine interrogation of either ∼18,000 or ∼24,000 reactive cysteines based on starting amounts of 10 or 20 μg, respectively. This represents a 5-10X reduction in input and 2-3X improved coverage. We applied the platform to screen 192 electrophiles in the native HEK293T proteome, mapping the ligandability of 38,450 reactive cysteines from 8,274 human proteins. We further applied the platform to characterize new cellular targets of established drugs, uncovering that ARS-1620, a KRAS^G12C inhibitor, binds to and inhibits an off-target adenosine kinase ADK. The platform represents a major step forward to high-throughput proteome-wide evaluation of reactive cysteines.

Keywords: ABPP; TMT; chemoproteomics; covalent electrophile; cysteine; high throughput.

Figure 1.. TMT-ABPP for high-throughput sample multiplexing-based cysteinome profiling in 96 well plates.

A) Optimized workflow for TMT-ABPP integrating high-throughput sample preparation with TMT18plex-based sample multiplexing in 96-well plates. Steps performed in 96-well plates include treatment of lysate with compounds (green star), treatment with DBIA probe (red hexagon), trypsin digestion, and TMT labeling. After combing TMT-labeled samples into 18-plexes, biotinylated cysteine-containing peptides are enriched using streptavidin-agarose followed by mass spectrometry analysis. Competition ratios (CR) between DMSO control and compound treatment samples are measured for each cysteine. B) TMT-ABPP significantly reduces instrument time for large-scale compound profiling (~11 min per compound). C) TMT-ABPP achieves routine assessment of more than 18K or 24K reactive cysteines using as little as 10 or 20 μg of soluble cell lysate. D) TMT-ABPP measures the competition ratio between vehicle and electrophile-treated samples to identify cystine-ligand interaction.

Figure 2.. Benchmarking low input TMT-ABPP with scout fragments.

A) Scout fragments KB02, KB03, and KB05 were used to profile cysteine ligandability in native HEK293T lysate. 10 μg of cell lysate was treated with each compound with concentration ranging from 10 μM to 200 μM for 1 hour and then processed using TMT-ABPP. Two replicates (2 ×18-plexes) were generated and analyzed. B) Number of cysteines and proteins quantified in each replicate. C) Overlap of cysteines and proteins between two replicates. D) Among 6,393 proteins profiled with TMT-ABPP, 505 (7.9%) are considered as drug targets by DrugBank and have cysteines ligandable (CR>2) by one of the scout fragments, while the other 547 (8.6%) DrugBank target proteins have reactive cysteines, but they are not ligandable by scout fragments. E) Heatmap of competition ratios (CRs) across all cysteines quantified in two replicates (n=22,492). F) Scouts show selectivity to different cysteines on GSTO1. Points represent mean CRs from duplicate measurements. G) Examples of newly identified and ligandable cysteines. These three cysteines were not identified in previous datasets profiling the fragments^,,. COL6A3 and ATP5MK have not been identified as containing reactive cysteines previously. Fragments have different binding potencies and selectivities to the three cysteines. Points represent mean CRs of duplicate measurements.

Figure 3.. Screening of a library of 192 electrophiles in 96-well plates.

A) 192 electrophiles (128 chloroacetamides and 64 acrylamides) were screened using HEK293T cell lysate (20 μg lysate per compound) in 96-well plates. 12 × 18-plexes were generated. B) On average, 24,205 reactive cysteines in 6,871 proteins were profiled in each 18-plex, resulting in a total of 5,228,402 measurements in 8,274 proteins. C) Data completeness across 12 × 18-plexes. In total, 38,450 cysteines were quantified in at least one 18-plex, and 13,354 were quantified without any missing values. D) Data completeness is correlated with protein copy number in HEK293T. Cysteines with higher data completeness are primarily on proteins with higher copy numbers, whereas cysteines showing lower data completeness are generally on low abundance proteins. HEK293T protein copy numbers were obtained from the OpenCell database. E) Many enzymatic active cysteines can be liganded by covalent electrophiles. These enzymes belong to various families including glutathione transferase (e.g., GSTO1), dehydrogenase (e.g., ALDH1B1), E3 ubiquitin ligases (e.g., HERC2), and hydrolyses (e.g., BLMH). F) Examples of ligandable enzymatic cysteines in HERC2, BLMH, ALDH6A1, and ALDH1B1. Color corresponds to competition ratio. G) Three cyclic sulfone-containing chloroacetamides (CL41, CL71, and CL74) bind to C57 and C113 in PIN1. H) Dose response of PIN1 C57 and C113 when treated with various concentrations of CL41, CL71, CL74, and Sulfopin. C113 is favored by these compounds and shows higher CR values.

Figure 4.. Electrophiles and protein structural environments.

A) Prediction-aware part-sphere exposure (pPSE) of all the cysteines with confident AlphaFold2 prediction quality (AlphaFold2 pLDDT>70) in the human proteome, reactive cysteines identified in the screening, and ligandable cysteines (CR>2). The pPSE value for cysteines is calculated by White et al. using StructureMap as described in Bludau et al.. B) Total and ligandable cysteines in representative protein domains. C) CR values of cysteines treated with AC19 in EGF-domains are higher on average than cysteines not in the domain, suggesting AC19’s preference to cysteines in EGF-like domains. D) AC19 and four analogs were used to study structure-activity relationship (SAR). The heatmap represents pairwise maximum common substructure-based Tanimoto coefficients. E) CR values of cysteines in EGF-like domains treated with 5 structural analogs. These cysteines are almost exclusively ligandable by AC19, suggesting the azepanyl group plays an important role in SAR. F) Examples of cysteines in the EGF-like domain that are only ligandable by AC19, but not any analogs. Bars represent mean CR ± s.d. (n=3).

Figure 5.. Profiling of five model compounds using low input TMT-ABPP identifies new off-targets.

A) Five covalent compounds, including experimental molecules (ARS-1620, THZ1, Sulfopin) and FDA-approved drugs (Ibrutinib, dimethyl fumarate [DMF]), were used to profile their on- and off-targets in HCC44, HEK293T and SH-SY5Y lysates. 10 μg of cell lysate was treated with each compound (n=3 for each cell line) at a concentration of 100 μM (DMF) or 50 μM (other compounds) for 1 hour and then processed using TMT-ABPP. Control samples (n=3 for each cell line) were treated with DMSO. Three TMT18-plexes were generated and analyzed. B) The overlap of cysteines and proteins quantified among experiments using different cell lysates. In total, 33,341 cysteines from 8,328 proteins were quantified. C) Average CRs (n=3) of 22,251 quantified cysteines in HCC44 treated with 50 μM ARS-1620. Cysteines with CR values >2 are labeled. In addition to its designed target KRAS^G12C, ADK C140 and SETD1B C1007 also respond to ARS1620 treatment in HCC44. D) The engagement of ADK C140 by ARS-1620 was reproduced in all three cell lines. Bars represent mean CR ± s.d. (n=3 for each cell line). **p ≤ 0.01, ***p ≤ 0.001. E) ARS-1620 inhibits ADK activity and substrate conversion. Points represent mean absorbance intensity± s.d. (n=4), corresponding to ADK activity. A-134974 is a selective ADK inhibitor and was used as the positive control (n=3), and DMSO was used as a negative control (n=3). F) Covalent docking prediction of ARS-1620 interactions to ADK (PDB ID: 2I6B). ADK residues shown in gray, ARS-1620 shown in teal, hydrogen bonds shown as yellow dashes and π-π interactions shown as black dashes. G) Overlay of docked poses for ARS-1620 (teal), positive control A-134974 (purple) and crystal structure of 5’-deoxy-5iodotubercidin (gold, PDB ID: 2I6A). Cys140 of ADK shown as gray sticks. H) The engagement of LYN C381 by Ibrutinib was reproduced in all three cell lines. Bars represent mean CR ± s.d. (n=3). I) Ibrutinib inhibiting LYN kinase activity and ATP conversion with a IC₅₀ of 1 μM. Points represent average ATP conversion ± s.d. (n=3). Staurosporine (IC₅₀=69 nM) was used as the positive control.