The c‑Myc/Max heterodimer is a basic helix–loop–helix leucine zipper (bHLHZip) transcription factor complex that regulates fundamental cellular processes, including growth, differentiation, metabolism, and programmed cell death. Dysregulation of c‑Myc expression is one of the most characteristic oncogenic events in human biology: c‑Myc is constitutively and aberrantly overexpressed in more than half of all human cancers. Its persistent activity promotes uncontrolled proliferation, maintains stem‑cell‑like self‑renewal, and suppresses senescence and differentiation pathways.

Despite its central role in tumorigenesis and decades of research, no clinically approved therapies currently exist that directly target the c‑Myc/Max complex. This gap keeps c‑Myc among the most compelling but challenging targets in modern drug discovery, with relevance spanning oncology, proliferative diseases, and metabolic disorders.

We assembled a curated c‑Myc‑focused library designed to provide high‑quality, mechanism‑relevant starting points for developing novel c‑Myc modulators and chemical probes.

Library design

To build a rationally designed compound library against c‑Myc‑related mechanisms, we focused on three complementary strategies:

1. Direct Modulation of the c‑Myc/Max Complex

Although a liganded structure of the c‑Myc/Max complex is still unavailable, several studies have reported small molecules capable of perturbing its function. Leveraging published models and experimentally validated active compounds, we designed two docking models for direct inhibition:

Model 1: Restriction of c‑Myc/Max flexibility near the E‑box binding pocket. Based on the paper J.Med.Chem., we used structural insights surrounding the compound 4DA (JKY‑2‑169), which binds near the c‑Myc/Max–DNA interface and reduces transcriptional activity by limiting conformational dynamics required for DNA recognition.

Model 2: Direct engagement within the E‑box binding interface. Using the concepts reported in Heliyon and Cell Commun Signal, we incorporated the binding mode of XYA1353, a ligand reported to occupy the DNA‑interaction surface of the c‑Myc/Max heterodimer, thereby preventing formation of the transcriptionally active protein–DNA complex.

These two models represent distinct but complementary approaches for identifying modulators that destabilize or prevent c‑Myc/Max engagement with genomic E‑box sequences.

2. Targeting the c‑Myc Promoter G‑Quadruplex

Given the difficulty of drugging intrinsically disordered transcription factors, promoter‑level regulation has emerged as an alternative strategy. A well‑characterized G‑quadruplex structure within the guanine‑rich region of the MYC promoter can repress transcription when sufficiently stabilized. Therefore, small molecules that bind to or stabilize this G‑quadruplex may indirectly suppress c‑Myc activity.

We incorporated major structural features of known modulators: macrocycle–quadruplex complexes, four- and three-fused aromatic rings, and ligands with two linked aromatic rings.

By mapping these structural features, we sought to capture molecules capable of stabilizing the G‑quadruplex and thereby suppressing c‑Myc transcription.

3. Indirect Inhibition Through Epigenetic and Co‑Regulatory Targets

Because c‑Myc/Max relies heavily on chromatin‑associated partners and epigenetic modifiers, indirect inhibition is another promising therapeutic strategy. We focused on targeting key proteins implicated in c‑Myc‑dependent transcriptional regulation: EZH2, HDAC2, KDM4A, KDM4B, KDM4D. These targets are functionally linked to chromatin environments that facilitate c‑Myc–driven gene expression. Modulation of their activity has been shown to alter c‑Myc transcriptional output, making them relevant secondary targets for targeting c‑Myc.

Through these three mechanistic approaches — direct inhibition, promoter G‑quadruplex stabilization, and modulation of c‑Myc‑associated epigenetic regulators — we constructed a diverse and biologically relevant compound library, designed to explore multiple intervention points of c‑Myc regulatory. This multifaceted approach increases the likelihood of identifying promising modulators of the most important oncogenic drivers in human disease.

All protein-ligand complexes were evaluated for stability using a 100 ns MD simulation. The optimized and stable complexes were then used for molecular docking calculations. The following PDB structures have been used for optimization and further simulations – direct binding to c-Myc/Max: 1nkp and 5i50, c-Myc/Max G-quadruplex: 7n7e, 7png, 6jj0, 5w77, and 2a5r, indirect inhibition: 5ls6, 8bpc, 7mos, 7ltk, 7kbh, 6xeb, 6g3o, 8a0b, 7zzw, 7zzt, 5ix0, 3max, 6h4w, 6h4u, 6hgt, 5fpv, 5f3i, 5f3c, 3pdq, 6cg2, 6cg1, 5vmp, 5a7w, 5a7s, 5f5i, 5f39, 3rvh, 6h8p, 7jm5, 5f5c, 5fp4, 5fp8, 6etg, 6ete, 6f5s, 6h0y, and 6h11.

MD simulation result

Model 1

Binding models between c-Myc/Max and 4DA (“JKY-2-169”). DNA in orange, Myc in yellow, Max in cyan.

Model 2

Binding models between c-Myc/Max and XYA1353. DNA in orange, Myc in yellow, Max in cyan.

Examples of molecular docking simulation, and used pharmacophore models, c-Myc/Max protein, direct interaction

Example 1 (PDB ID 1nkp, c-Myc/Max)

Example 2 (PDB ID 1nkp, c-Myc/Max)

Example 1: According to the pharmacophore model, the ligand's acceptor interacts with Arg 519, and the aromatic ring fills the sub-pocket created by Lys 536 and the nucleotide environment of DNA.
Example 2: Key feature – ligand should contain 3 aromatic rings to create stacking interaction with nearby amino acids.
DNA is in orange, Myc in yellow, Max in cyan, native ligand in grey, docked example in green.

Examples of molecular docking simulation, and used pharmacophore models, c-Myc/Max G-quadruplexes

Example 1 (PDB ID 6jj0, c-MYC G-quadruplex)

Example 2 (PDB ID 2a5r, c-MYC G-quadruplex)

Example 1: Ligand should contain 3 aromatic rings to create a stacking interaction with the nucleotides.
Example 2: The model contains 8 binding points, including 4 aromatic and mixed aromatic or N+ feature. According to this model, a potential ligand must occupy at least 3 out of 8 binding points to be selected.
DNA in orange, native ligand in grey, docked ligand in yellow.

Examples of molecular docking simulation, and used pharmacophore models, Indirect inhibition strategies

Example 1 (PDB ID 8a0b, HDAC2)

Example 2 (PDB ID 7jm5, KDM4B)

Example 1: A potential ligand requires two aromatics to create π-stacking interaction with Phe155, Phe210, and Tyr308 in one part, and Arg39 and Met35 on the other part of the pocket. Key features: acceptor, ring and donor near the metal atom.
Example 2: Two acceptor features interacting with Lys207, Tyr133, and a metal. Any ring or aromatic ring to fill the binding pockets and create interaction with Lys242.
In both cases, the protein and native ligand are in yellow, and the docked structure in grey.

In collaboration with leading experts from top Pharma companies and the Structural Genomics Consortium (SGC), we carefully designed, experimentally characterized, and validated — through numerous screening campaigns — the first edition of our Enantio‑ASMS Library (E‑ASMS).

Library Design

E-ASMS Library has been developed to accelerate the early stages of drug discovery by providing a diverse and well-characterized set of small molecules. Each compound has been selected to have only one chiral atom and be a mixture of only two enantiomers, which can be easily separated by using one of four standard and described in the paper conditions.

Additionally, the library is designed to maximize chemical space coverage, maintain drug‑like properties, and support efficient hit identification across diverse therapeutic areas. Rigorous quality control and SFC chiral separation of each compound ensures reproducibility and reliability, making this library a robust resource for screening campaigns.

UMap projection to the entire enamine stock collection of 4.6 million compounds and PMI plot.

Each compound in the library is supported with pre-calculated analogs from stock and from REAL Space. Links to the files with calculated analogs are available from SD file in a separate column.

Analogs calculation and search in REAL Space

1. Reaction guided search of analogs

2. Synthon-based sub-structure search

We invite medicinal chemists, biologists, and drug hunters to integrate the E-ASMS Library into their discovery pipelines. By leveraging this curated library, researchers can rapidly identify novel scaffolds, explore structure activity relationships, and generate data that informs lead optimization process. Contact us today to access the library and accelerate your next breakthrough.

Support

We offer comprehensive support in developing your hit compounds. Naturally such programs are realised most efficiently when biological actives originate from our screening collection. However, even if the hit compounds are from the collections of other vendors lead identification and optimization projects can proceed most productively in our hands. Sometimes for this we only need to synthesize first examples of the given chemical series and validate synthesis route.

The concept of Halogen-Enriched Fragment Libraries (HEF) has gained significant traction in medicinal chemistry, supported by multiple successful screening campaigns.^[1,2] These libraries are designed to explore halogen-mediated interactions, which can play a critical role in molecular recognition and binding affinity. Halogen bonding, the key interaction exploited by HEF, has been extensively studied since its initial discovery via X-ray crystallography.^[3] Its electrostatic nature is now well understood, and it has been shown to significantly influence both selectivity and efficacy in drug-target interactions.^[4,5,6]

Halogen bonding through σ-hole interactions

A major factor in halogen bonding is the σ-hole, whose characteristics can be “tuned” by varying (hetero)aromatic ring systems and their substitution patterns. This tunability allows for precise control over interaction strength and directionality.

Enamine, a global leader in heterocyclic chemistry, has synthesized thousands of novel halogenated scaffolds, creating the most diverse collection of halogenated core heterocycles available. Our carefully designed Halogen-Enriched Fragment Library comprises the most relevant fragments for exploring affinity towards binding via these non-covalent halogen-mediated interactions.

Key features

• Diverse (hetero)aromatic fragments set for probing halogen bonds
• All compounds include at least one non-fluorine halogen atom
• No PAINS, only MedChem friendly compounds
• Express follow-up from stock and from Enamine REAL

Examples of compounds from HEF Library

Library design

The fragment library was constructed from a curated database of over 250,000 compounds, all strictly compliant with the Rule of Three (Ro3) and filtered using medicinal chemistry criteria. Each compound includes at least one heavy halogen atom (Cl, Br, or I), with 95% containing only one. The distribution is as follows: 183 iodides (9.5%), 963 bromides (50.1%), and 684 chlorides (35.6%). The remaining 4.8% are dichloro derivatives. Additionally, the library includes 194 fluorinated compounds (10.1%). Fragments were selected with heavy atom counts (HA) ranging from 6 to 19, with a majority (1,206 fragments) falling within the 12–16 HA range. Each fragment contains between one and three rings, with 97% featuring one or two. We also included 154 fragments from 200 originally described as HEFLib by Frank M. Boeckler. Scaffold analysis revealed the most frequently occurring (hetero)aromatic ring systems.

Most Frequently Used Heteroaromatic Ring Systems in the HEF Library

Nuisance compounds are commonly known for their interference with bioassay readouts in high-throughput screening (HTS), causing false positives that are inapplicable to the hit-finding process. Recently, Jonathan Baell provided a description of nuisance compound classes, including colloidal aggregates, PAINS (Pan-Assay Interference Compounds), electrophiles and redox cyclers, chelators, as well as optical and phenotypic assay interference compounds.

We provide a curated list of more than 80 nuisance chemicals known to obstruct assay readouts in target-based and phenotypic screenings. Conveniently available in an assay-ready screening plate, this nuisance compound set is expected to be of great interest to the research community, helping to develop high-quality HTS assays that yield promising, optimizable hits. Hits arising from this small set of nuisance compounds would be highly informative in screening campaigns, assisting target-owners in identifying the types of interference compounds that their assays might be susceptible to.

Key features

1. Enhances HTS assay reliability by addressing potential interference
2. Over 40 different modes of action
3. Readily accessible in an assay-ready screening plate
4. References for compounds are available

Library design

The global literature overview and data analysis served as the foundation for the design. Over 80 compounds are categorized based on their specific targets, structural elements, and types of interactions. The collection includes compounds widely recognized and validated as promiscuous across a range of independent and distinct screening methodologies.

Example of structures