The History of DNA-Encoded Chemical Libraries: How Encoding Changed Ligand Discovery

In the last few decades, ligand discovery has moved from “screen what you can physically test” to “explore chemical space at a scale that used to be impossible.” One of the most important steps in that journey is the rise of DNA-encoded chemical libraries often called DELs. By attaching a DNA barcode to each molecule, scientists gained a powerful way to track and amplify information about binding molecules after selection against protein targets.

Before DEL: the early era of chemical libraries in drug discovery

Modern chemical libraries started as physical collections: bottles and plates of compounds assembled over time by medicinal chemists and screening groups. For many years, the dominant paradigm was straightforward:

• Build or buy a library of compounds
• Screen them experimentally in biochemical or cellular assays
• Confirm activity and optimize the best hits

This approach works well but it is limited by the cost and logistics of handling individual compounds. Even high-throughput screening (HTS), with robots and miniaturized assays, faces practical constraints when libraries scale into the millions.

As drug discovery matured, teams began asking a more ambitious question:

The core idea that changed everything: encoding chemistry with DNA

The key DEL insight is beautifully simple:

1. Synthesize a small molecule
2. Attach a DNA tag that records its identity or synthesis path
3. Pool the library (millions to billions of compounds in one tube)
4. Expose the pool to a target protein
5. Recover and sequence the DNA tags from enriched binders

Because DNA can be amplified (PCR) and read cheaply (sequencing), DEL transformed the economics of library size. Instead of buying time and space for millions of individual wells, you screen an enormous chemical universe by selection.

This enabled a new style of ligand discovery where the “readout” is sequencing counts, and the first product is a ranked list of candidates for follow-up testing.

Milestones in the history of DNA Encoded Chemical Libraries (high-level timeline)

DEL history spans multiple innovations, but the most important milestones can be described in a few phases.

Phase 1: Proof of concept: Can DNA survive chemistry and still be readable?

Early DEL development required chemistries compatible with DNA. This motivated:

• Mild reaction conditions
• A focus on robust coupling steps
• Careful purification and handling protocols

The success of these early experiments established that DNA could act as a stable information carrier during library creation.

Phase 2: Library growth combinatorial synthesis goes “encoded”

Once the concept proved effective, DEL designers began building libraries using split-and-pool methods. This effectively brought combinatorial library philosophy into a DNA-readable format:

• Round-based synthesis with a DNA “record” at each step
• Massive expansions in library size
• Families of related compounds that revealed early SAR patterns

Phase 3: Target expansion to more protein targets, better selection formats

DEL moved from “toy targets” to real drug targets as selection techniques matured:

• Improved target immobilization and presentation
• Counter-selections to reduce nonspecific binders
• Selection conditions that supported a wider range of proteins

This phase is where DEL became strongly associated with mainstream drug discovery programs.

Phase 4: Industrialization platforms, analytics, and reliable hit follow-up

As DEL matured, the major bottleneck shifted from “can we screen?” to “can we translate selection signals into chemistry that works off-DNA?”

To solve that, the field invested in:

• Standardized analytics and hit identification funnels
• Better data normalization across conditions
• n- Broader sets of DNA-compatible reactions
• Faster off-DNA resynthesis and validation pathways

This phase turned DEL from an interesting tool into a reliable lead-generation engine.

Why DEL became central to ligand discovery

DELs are now widely used because they solve a practical constraint: the screening scale.

1) Scale unlocks new binding possibilities

Ultra-large encoded libraries explore chemical libraries on a scale that can reveal:

• Novel scaffolds
• Unexpected binding motifs
• Alternative binding geometries and site hypotheses

2) Selection can enrich for “real” binders

When well-designed, selections can favor compounds that bind with high affinity (or at least show strong enrichment). Even when potency is unknown, selection often identifies families worth pursuing.

3) Family-level output helps learn SAR early

Because DEL outputs often include multiple related binding molecules, teams can infer which structural features are important before deep medicinal chemistry begins.

How DEL fits with virtual libraries and classic screening

DEL did not replace other methods; it expanded the toolkit.

DEL vs Virtual library screening

A Virtual library is computational: docking, scoring, or machine-learning ranking to prioritize what to test. DEL is an experimental selection at a massive scale. A productive way to combine them is:

• Use virtual screening to prioritize targets, binding sites, or scaffolds
• Use DEL to discover novel chemotypes and enrichment families
• Use in silico models again to guide analog design after hits are confirmed

DEL vs HTS

HTS tests discrete compounds directly in functional assays. DEL is selection-based and usually starts with binding.

Many teams use both:

• DEL for breadth and scaffold discovery
• HTS for functional validation and modality flexibility

Together, they can speed hit identification and improve confidence.

High-affinity binding: what DEL can suggest (and what it can’t)

DEL enrichment is often associated with strong binding, but it’s not the same as a measured KD/IC50. The relationship is real but not perfect.

To confirm high-affinity binding, researchers typically:

• Resynthesize compounds off-DNA
• Validate with orthogonal methods (SPR/BLI/ITC/DSF)
• Check selectivity against related protein targets

The positive news: when DEL campaigns are well controlled, confirmed binders often arrive in series, which makes optimization faster and more reliable.

Hit identification after DEL: the disciplined funnel.

DEL produces hypotheses. Hit identification turns those hypotheses into decision-quality hits. A practical funnel looks like:

1. Rank enriched families (not just singletons)
2. Filter nuisance motifs and common nonspecific patterns
3. Choose multiple representatives per family
4. Off-DNA resynthesis
5. Orthogonal binding confirmation
6. Selectivity and counter-screening
7. Early developability checks (solubility, aggregation)

This funnel increases confidence and keeps programs moving forward with optimism and clarity.

truemeds collection pages that support DEL-enabled drug discovery programs

DEL workflows don’t end at selection, they accelerate when you can quickly obtain analogs, reference compounds, and supporting reagents for validation and expansion. truemeds is structured around discovery needs, making it useful in the post-DEL stage.

Core discovery collections (hit follow-up and series expansion)

• Drug Discovery
• Small Molecules
• Compound Libraries

Modality and advanced chemistry collections (when your target strategy broadens)

• PROTAC (for targeted protein degradation programs)
• Isotope Labeled Compounds (for mechanistic and ADME tracking)
• APIs and Impurities (reference and quality workflows)

Target and biology support collections (useful for validation workflows)

• Drug Target Proteins (for assay development and binding validation setups)
• Test Kits (when pathway readouts or validation assays are needed)

Pathway-focused collections (helpful to build focused sub-libraries)

• Epigenetics
• Cell Cycle
• GPCR / G Protein
• Protein Tyrosine Kinase / RTK
• PI3K/Akt/mTOR

These collection groupings help teams translate DEL outputs into follow-up experiments with fewer delays supporting the momentum that matters in real drug discovery programs.

What the future looks like: where encoded libraries keep evolving

DEL technology continues to evolve in ways that make ligand discovery more efficient and more informative:

• Improved DNA-compatible chemistry expands accessible chemical space
• Better analytics strengthen hit ranking and reduce false positives
• Selection formats keep improving for membrane proteins and complex targets
• Integration with computational models makes the design test loop faster

The trend is encouraging: DEL is becoming not just larger, but smarter helping teams learn more per experiment.

Conclusion:

DEL enabled ligand discovery at an ultra-large scale, practical for mainstream drug discovery programs.Sequencing enrichment suggests promising binding molecules, but hit identification requires off-DNA confirmation.DEL complements HTS and Virtual library screening rather than replacing them.truemeds discovery-oriented collections support the follow-up phase where validated hits become lead series.