High-Throughput Identification Of Covalent Drug Targets

Objective Covalent drugs are those chemical drugs that form a covalent attachment to their biological target,which offer advantages over non-covalent drugs with respect to increased biochemical potency through covalency and increased duration of action.In the last decade,with the approvement of many targeted covalent inhibitors（TCIs）like afatinib,ibrutinib and zanubrutinib for anti-cancer treatment,the pursuit of TCIs as drug candidates has gained renewed impetus in the pharmaceutical industry.Therefore,proteome-wide identification of proteins that can be specifically targeted by small molecules is crucial for the discovery of novel therapeutic targets,and large-scale smallmolecule libraries have been constructed.Chemical proteomics,especially ActivityBased Protein Profiling（ABPP）and its derivatives,is one of the mainstream methods for screening small molecule libraries.However,without exception,these methods are difficult to achieve truly efficient identification and generally only at the expense of ease of operation and time,e.g.,by large-scale fractionation to improve the yields.Another common problem is that the throughput is limited,and both sample pre-treatment and subsequent data analysis and target screening rely on manual operation,making it difficult to achieve the scale and automation required by industry.Therefore,how to establish a fully automated process on the basis of shortening the experimental time and increasing the identified IDs is the urgent technical bottleneck currently.This project aims to improve the identification and throughput of chemoproteomic technology based on the existing platform QTRP（Quantitative Thiol Reactivity Profiling）,and to help the pharmaceutical industry to screen small molecule library on a large scale,so as to identify potential drug targets efficiently and precisely.Methods Based on ABPP,we have developed a chemical proteomic platform ‘QTRP’that relies on a commercially available thiol-reactive probe IPM to covalently label the reactive cysteinome.This approach could measure the response of thousands of cysteines to electrophilic compounds.Based on QTRP,firstly,this work simplified the most tedious steps in order to improve the efficiency.Second,the sample pre-treatment protocol was significantly optimized by systematically evaluating five commercially available cleavable biotin reagents,the key reagents that "carry the day" in the chemoproteomic workflow,in combination with the other two techniques commonly used in the field.Finally,with the utilization of multi-channel equipment and pre-introducing the isotopic information,the efficiency of sample processing was further improved.In addition,the quantitative accuracy of six leading proteomics software for chemically modified peptides was evaluated to determine the supporting analytical software,and a batch processing was developed to improve the efficiency of data analysis.Results 1.Simplification of QTRP: By removing the cumbersome Strong Cation Exchange（SCX）step,the sample preparation time was reduced from 4 days to 3 days without compromising the number of identification（thousands of cysteine sites）in a single run.2.Comprehensive optimization of QTRP: By applying the cleavable linker DADPS into Workflow B（click chemistry at the protein level,streptavidin enrichment at the peptide level）,more than 10,000 cysteine sites can be quantified in a single run and the time of sample preparation was reduced from 3 days to 2 days.3.High throughput of QTRP: With the utilization of multi-channel equipment and the pre-introduction of isotopic tags from CUAAC reaction to IPM labeling,the time of sample preparation was reduced from 2 days to 1 day and at least 48 samples can be processed at once.Simultaneously,p Quant（new）software was selected for quantitative analysis and a batch processing was developed to convert 36 mass spectrometry data into quantitative information at the site level automatically in one day.4.Application of the high throughput QTRP: The workflow was successfully applied to identify protein targets of292 small molecule compounds.Conclusions A high-throughput covalent drug target identification system has been established.The efficiency of sample processing has been improved by 20 times,and the reactivity of tens of thousands of cysteine residues can be quantified in a single run.Simultaneously,the time of data processing has been compressed by a third by introducing a batch processing.Ultimately,this high-throughput chemoproteomic platform has been successfully applied to large-scale drug target identification.