Translating the Genome into Drugs

Agonist Discovery for Membrane Proteins on Live Cells by Using DNA-encoded Libraries

Identifying biologically active ligands for membrane proteins is an important task in chemical biology. We report an approach to directly identify small molecule agonists against membrane proteins by selecting DNA-encoded libraries (DELs) on live cells. This method connects extracellular ligand binding with intracellular biochemical transformation, thereby biasing the selection toward agonist identification. We have demonstrated the methodology with three membrane proteins: epidermal growth factor receptor (EGFR), thrombopoietin receptor (TPOR), and insulin receptor (INSR). A ∼30 million and a 1.033 billion-compound DEL were selected against these targets, and novel agonists with subnanomolar affinity and low micromolar cellular activities have been discovered. The INSR agonists activated the receptor by possibly binding to an allosteric site, exhibited clear synergistic effects with insulin, and activated the downstream signaling pathways. Notably, the agonists did not activate the insulin-like growth factor 1 receptor (IGF-1R), a highly homologous receptor whose activation may lead to tumor progression. Collectively, this work has developed an approach toward "functional" DEL selections on the cell surface and may provide a widely applicable method for agonist discovery for membrane proteins.

Controlled enzymatic synthesis of oligonucleotides

Oligonucleotides are advancing as essential materials for the development of new therapeutics, artificial genes, or in storage of information applications. Hitherto, our capacity to write (i.e., synthesize) oligonucleotides is not as efficient as that to read (i.e., sequencing) DNA/RNA. Alternative, biocatalytic methods for the de novo synthesis of natural or modified oligonucleotides are in dire need to circumvent the limitations of traditional synthetic approaches. This Perspective article summarizes recent progress made in controlled enzymatic synthesis, where temporary blocked nucleotides are incorporated into immobilized primers by polymerases. While robust protocols have been established for DNA, RNA or XNA synthesis is more challenging. Nevertheless, using a suitable combination of protected nucleotides and polymerase has shown promises to produce RNA oligonucleotides even though the production of long DNA/RNA/XNA sequences (>1000 nt) remains challenging. We surmise that merging ligase- and polymerase-based synthesis would help to circumvent the current shortcomings of controlled enzymatic synthesis.

Synthesis of Diacylhydrazine Derivatives Based on Tetrazole-Focused DNA-Encoded Library

Utilizing already existing DNA-encoded libraries (DELs) for the generation of a distinct DEL represents an expedited strategy for expanding the chemical space. Herein, we leverage the unique photoreactivity of tetrazoles to synthesize diacylhydrazines on DNA. Widely available carboxylic acids serving as building blocks were employed under the mild photomediated reaction conditions, affording diverse DNA-conjugated diacylhydrazines. This methodology also demonstrates robustness in DEL-compatible synthesis and facilitates the preparation of oligonucleotide-based chemical probes.

Evolution of chemistry and selection technology for DNA-encoded library

DNA-encoded chemical library (DEL) links the power of amplifiable genetics and the non-self-replicating chemical phenotypes, generating a diverse chemical world. In analogy with the biological world, the DEL world can evolve by using a chemical central dogma, wherein DNA replicates using the PCR reactions to amplify the genetic codes, DNA sequencing transcripts the genetic information, and DNA-compatible synthesis translates into chemical phenotypes. Importantly, DNA-compatible synthesis is the key to expanding the DEL chemical space. Besides, the evolution-driven selection system pushes the chemicals to evolve under the selective pressure, i.e., desired selection strategies. In this perspective, we summarized recent advances in expanding DEL synthetic toolbox and panning strategies, which will shed light on the drug discovery harnessing in vitro evolution of chemicals via DEL.

Unexpected Cyclization Product Discovery from the Photoinduced Bioconjugation Chemistry between Tetrazole and Amine

Bioconjugation chemistry has emerged as a powerful tool for the modification of diverse biomolecules under mild conditions. Tetrazole, initially proposed as a bioorthogonal photoclick handle for 1,3-dipolar cyclization with alkenes, was later demonstrated to possess broader photoreactivity with carboxylic acids, serving as a versatile bioconjugation and photoaffinity labeling probe. In this study, we unexpectedly discovered and validated the photoreactivity between tetrazole and primary amine to afford a new 1,2,4-triazole cyclization product. Given the significance of functionalized N-heterocycles in medicinal chemistry, we successfully harnessed the serendipitously discovered reaction to synthesize both pharmacologically relevant DNA-encoded chemical libraries (DELs) and small molecule compounds bearing 1,2,4-triazole scaffolds. Furthermore, the mild reaction conditions and stable 1,2,4-triazole linkage found broad application in photoinduced bioconjugation scenarios, spanning from intramolecular peptide macrocyclization and templated DNA reaction cross-linking to intermolecular photoaffinity labeling of proteins. Triazole cross-linking products on lysine side chains were identified in tetrazole-labeled proteins, refining the comprehensive understanding of the photo-cross-linking profiles of tetrazole-based probes. Altogether, this tetrazole-amine bioconjugation expands the current bioconjugation toolbox and creates new possibilities at the interface of medicinal chemistry and chemical biology.

Building Block-Based Binding Predictions for DNA-Encoded Libraries

DNA-encoded libraries (DELs) provide the means to make and screen millions of diverse compounds against a target of interest in a single experiment. However, despite producing large volumes of binding data at a relatively low cost, the DEL selection process is susceptible to noise, necessitating computational follow-up to increase signal-to-noise ratios. In this work, we present a set of informatics tools to employ data from prior DEL screen(s) to gain information about which building blocks are most likely to be productive when designing new DELs for the same target. We demonstrate that similar building blocks have similar probabilities of forming compounds that bind. We then build a model from the inference that the combined behavior of individual building blocks is predictive of whether an overall compound binds. We illustrate our approach on a set of three-cycle OpenDEL libraries screened against soluble epoxide hydrolase (sEH) and report performance of more than an order of magnitude greater than random guessing on a holdout set, demonstrating that our model can serve as a baseline for comparison against other machine learning models on DEL data. Lastly, we provide a discussion on how we believe this informatics workflow could be applied to benefit researchers in their specific DEL campaigns.