The Advantages of Using DNA-Encoded Libraries (DELs) in Hit Identification Compared to Traditional High-Throughput Screening (HTS)
Abstract
Hit identification remains a bottleneck in early drug discovery. Traditional high-throughput screening (HTS), while established and effective, is constrained by cost, throughput, and chemical space limitations. DNA-encoded libraries (DELs) have emerged as a transformative platform, enabling the screening of billions of compounds simultaneously through DNA barcoding and affinity selection. This article compares DEL Screening to HTS, detailing their advantages in terms of library diversity, efficiency, cost-effectiveness, and their suitability for difficult targets. It also discusses the technological advancements of platforms like Vipergen’s DEL YoctoReactor technology and the development of in-cell screening. These innovations underscore DELs’ growing role in next-generation drug discovery workflows.
1. Introduction
High-throughput screening (HTS) has long served as a cornerstone in early-stage drug discovery, enabling the systematic testing of chemical libraries against biological targets. While powerful, HTS is limited by the number of compounds that can be screened, infrastructure costs, and assay development complexity. DNA-encoded libraries (DELs), first proposed by Brenner and Lerner in 1992 [1], provide a radically different approach, using DNA barcodes to track compound identity and enabling the screening of up to 10¹² compounds in a single tube.
DELs have since evolved into a widely adopted technology for identifying ligands against a broad range of targets, including those deemed “undruggable” [2–5]. Recent innovations, such as in-cell screening [2] and industry-specific platforms like Vipergen’s YoctoReactor® [6,11], have further expanded their utility, bridging the gap between biochemical binding and cellular relevance.
2. Overview of HTS and DEL Technologies
2.1 Traditional High-Throughput Screening
HTS involves testing libraries of compounds—typically ranging from 10⁴ to 10⁶ unique molecules—against a biological assay in miniaturized formats using automated robotic systems. Hits are identified based on activity readouts such as fluorescence, luminescence, or phenotypic changes [7]. While effective, HTS requires substantial investment in infrastructure, compound management, and assay development, especially when multiple screening campaigns are required.
2.2 DNA-Encoded Libraries
In DELs, small molecules are synthesized with covalently attached DNA tags that encode their synthetic history [1-5]. Libraries are generated using split-and-pool combinatorial methods and screened in pooled format by affinity selection against purified proteins. After selection, retained DNA tags are amplified and sequenced, with bioinformatic analysis revealing enriched sequences indicative of binding [2,3].
3. Comparative Advantages of DELs Over HTS
3.1 Chemical Space and Library Size
3.2 Screening Throughput and Efficiency
DELs achieve ultra-high throughput by screening all library members in a single tube using target affinity as the selection mechanism. This reduces assay time to days and requires only nanogram-scale protein quantities [2,3]. In contrast, HTS is constrained by physical compound handling, reagent use, and labor-intensive data collection [8].
3.3 Cost Considerations
Once a DEL is synthesized, it can be reused for many targets with minimal incremental cost. The primary expenses relate to sequencing and initial library generation, both of which continue to decrease [4,5]. HTS, by comparison, involves ongoing costs for compound management, assay reagents, and maintenance of high-throughput infrastructure [8].
3.4 Binding-Based vs. Functional Readouts
DELs identify binders rather than functional modulators. This distinction can be advantageous when the goal is to target protein–protein interactions or identify scaffolds for further optimization [9]. HTS, on the other hand, selects compounds based on biological activity, which may be influenced by assay artifacts or off-target effects [8].
4. Advances in DEL Technologies
4.1 Vipergen’s DEL YoctoReactor® Platform
4.2 In-Cell DEL Screening
5. Limitations of DELs
Despite their advantages, DELs have limitations:
- DNA-Compatible Chemistry: Reactions used in DEL synthesis must be mild and aqueous-compatible, which limits synthetic diversity [2-5].
- Target Format Constraints: DELs are most effective with soluble, purified proteins, which excludes many membrane-bound or multi-protein complexes unless novel approaches like those from Vipergen are used [4,5].
- False Positives: Nonspecific binders, including DNA-binding molecules, may be enriched. Counter-selection and orthogonal validation are essential [9].
Lack of Functional Insight: Hits identified through binding may not translate to functional activity, requiring follow-up biochemical or cell-based assays [9].
6. Integration with Other Platforms
DELs can be synergistically combined with HTS, fragment-based drug discovery (FBDD), and artificial intelligence. DEL-derived hits are often validated with HTS assays to confirm activity [4,5,9]. Furthermore, DELs incorporating fragment-like scaffolds can benefit from structure-guided optimization. Emerging machine learning tools are being developed to analyze DEL enrichment data and predict SAR trends [7].
7. Conclusion and Outlook
DNA-encoded libraries offer unprecedented advantages in chemical diversity, screening throughput, and cost-efficiency. With innovations like intracellular DEL screening [2] and advanced platforms from Vipergen [6], DELs are closing the gap between in vitro binding and in vivo relevance. While HTS remains indispensable for functional assays, DELs are now a central pillar in early hit discovery—especially for difficult targets and novel mechanisms of action.
As new DNA-compatible chemistries, in vivo screening techniques, and integrated data analysis tools emerge, DELs are poised to lead a new era of rapid, efficient, and target-tailored drug discovery [10].
References
- Brenner, S., & Lerner, R. A. (1992). Encoded combinatorial chemistry. Proceedings of the National Academy of Sciences, 89(12), 5381–5383. https://doi.org/10.1073/pnas.89.12.5381
- Petersen, L. K., Christensen, A. B., Andersen, J., Folkesson, C. G., Kristensen, O., Andersen, C., Alzu, A., Sløk, F. A., Blakskjær, P., Madsen, D., Azevedo, C., Micco, I., & Hansen, N. J. V. (2021). Screening of DNA-encoded small molecule libraries inside a living cell. Journal of the American Chemical Society, 143(7), 2751–2756. https://doi.org/10.1021/jacs.0c09213
- Clark, M. A., Acharya, R. A., Arico-Muendel, C. C., Belyanskaya, S. L., Benjamin, D. R., Carlson, N. R., Centrella, P. A., Chiu, C. H., Creaser, S. P., Cuozzo, J. W., Davie, C. P., Ding, Y., Franklin, G. J., Franzen, K. D., Gefter, M. L., Hale, S. P., Hansen, N. J. V., Israel, D. I., Jiang, J., … Morgan, B. A. (2009). Design, synthesis and selection of DNA-encoded small-molecule libraries. Nature Chemical Biology, 5, 647–654. https://doi.org/10.1038/nchembio.211
- Favalli, N., Bassi, G., Scheuermann, J., & Neri, D. (2018). DNA-encoded chemical libraries—Achievements and remaining challenges. FEBS Letters, 592(12), 2168–2180. https://doi.org/10.1002/1873-3468.13068
- Gironda-Martínez, A., Donckele, E. J., Samain, F., & Neri, D. (2021). DNA-encoded chemical libraries: A comprehensive review with successful stories and future challenges. ACS Pharmacology & Translational Science, 4(4), 1265–1279. https://doi.org/10.1021/acsptsci.1c00118
- Vipergen A/S. (2023). Technology overview. https://www.vipergen.com
- Iqbal, S., Jiang, W., Hansen, E., Ghosh, A., Hou, Y., Wang, X., & Li, J. (2025). Evaluation of DNA encoded library and machine learning model combinations for hit discovery. NPJ Drug Discovery, 2, 5. http://dx.doi.org/10.1038/s44386-025-00007-4
- Macarron, R., Banks, M. N., Bojanic, D., Burns, D. J., Cirovic, D. A., Garyantes, T., Green, D. V. S., Hertzberg, R. P., Janzen, W. P., Paslay, J. W., Schopfer, U., & Sittampalam, G. S. (2011). Impact of high-throughput screening in biomedical research. Nature Reviews Drug Discovery, 10, 188–195. https://doi.org/10.1038/nrd3368
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