Platform for Identifying Cellular Targets of Covalent Drugs by Amino Acid Substitution Using Prime Editing
Background
In recent years, research on covalent ligands that form permanent bonds with specific amino acids in proteins has been actively conducted in the fields of biopharmaceuticals and drug development. In particular, with the advancement of chemical proteomics technology, hundreds of cysteine residues in human proteins capable of forming covalent bonds have been identified on a large scale. However, even when the amino acid sites where drugs can bind are identified, it is extremely difficult to confirm, on a large scale, what physiological changes are induced when the binding occurs inside the cell. This is because it is challenging to distinguish whether the binding site is a real target involved in disease treatment or cell death, or merely an irrelevant site that does not affect biological activity. In the past, this required complex and inefficient methods such as individually genetically modifying proteins and injecting them into cells, leading to a bottleneck in drug development research, as many covalent drug candidates were discovered without elucidating their mechanisms of interaction with actual targets.
Key Findings
To overcome these limitations, the research team developed a new platform called ESCAPE (Endogenous Site-specific Competition Assays using Prime Editors) by integrating prime editing technology. This platform utilizes prime editing to precisely edit amino acid sequences at the genomic level, replacing specific cysteine residues in cells with serine residues. When the amino acid is changed to serine, the covalent ligand cannot bind to the protein. The research team then analyzed the survival rates and genotype distributions of each cell population after drug administration to precisely determine resistance scores based on allele frequencies. The team conducted experiments on more than 50 target proteins identified using activity-based protein profiling (ABPP), focusing on cysteine binding sites. The study successfully selected multiple covalent interactions that inhibit cancer cell growth. A representative validation case was a specific cysteine residue in the RNA helicase DDX49 protein. This amino acid was located in a non-orthosteric binding site, not the active site, making it difficult to detect in previous studies. However, the research confirmed that when the drug binds, it sequentially blocks 18S ribosomal RNA (18S rRNA) processing and 40S ribosome assembly, ultimately inhibiting overall protein synthesis.
Significance and Outlook
This research achievement opens a path for rapid validation of drug candidates at the cellular level. In particular, it is evaluated as narrowing the gap between identifying binding sites and verifying actual efficacy, a limitation of previous chemical proteomics studies. With the ability to screen hundreds of target candidates simultaneously at high speed, it is expected to significantly shorten the development period for next-generation targeted therapies. However, challenges remain for full adoption in clinical and industrial settings. Since the correction efficiency of prime editing varies by cell line, it is difficult to apply uniformly to all genes. Additionally, to ensure the precision of the platform, side effects such as off-target editing must be overcome. Further validation through animal experiments to confirm whether drug candidates activate similarly in environments similar to the human body is also a key task.
Chemical proteomics has identified covalent ligands targeting cysteine residues across many hundreds of human proteins. The functional effects of these liganding events, however, remain challenging to assign at scale. Here we describe ESCAPE (Endogenous Site-specific Competition Assays using Prime Editors), a platform for the site-resolved functional analysis of covalent ligands in cells. In this method, cysteine-to-serine substitutions are generated by prime editing to abrogate covalent ligand-protein interactions, and the impact of these edits on ligand-induced cellular phenotypes is quantified through allele frequency-based resistance scores. Applied to ligandable cysteines mapped by activity-based protein profiling in 50+ proteins, ESCAPE identified multiple covalent ligand-protein interactions that impair cancer cell growth, including azetidine butynamides that target a non-orthosteric cysteine in the RNA helicase DDX49 to disrupt 18S rRNA processing, 40S ribosome assembly, and protein synthesis. ESCAPE thus provides a scalable framework for the functional characterization of covalent ligands targeting structurally and mechanistically diverse proteins.
The ESCAPE technology developed in this study can serve as a key tool for reducing drug attrition rates in the early stages of drug development. For example, consider a scenario for developing a new anticancer drug targeting specific proteins in cancer cells. Even if a new drug candidate inhibits cancer cell growth, it is necessary to determine whether this is due to genuine binding with the DDX49 protein or an off-target effect with other similar proteins. In this case, the method involves using ESCAPE to create a cell line with a precise mutation in the binding amino acid of DDX49 in cancer cells. If the drug fails to show anticancer effects in the mutated cell line but is effective in normal cell lines, it directly proves that the drug is a highly precise candidate targeting only DDX49. This allows researchers to significantly skip unnecessary screening steps in the development process and focus resources on promising candidates, thereby increasing the success rate of drug approval.