<p>    </p> <p>DNA-encoded chemical libraries (DELs) are collections of DNA-linked small molecules, where each synthetic small molecule is covalently attached to a unique DNA barcode that encodes its identity. This technology harnesses the power of organic chemistry and genetics, which extends the application of molecular evolution and natural selection to the discovery of specific small molecules binders to protein targets of interest. Rather than discretely screening individual molecules, up to billions of DNA-encoded small molecules can be assessed collectively by a selection assay in a single tube. As a result, the high sensitivity, low cost, and unprecedented level of molecular complexity of DELs allow rapid generation of novel bioactive compounds. While powerful, this approach has its own limitations, including limited target scope and selection strategies. Currently, DEL targets have been largely limited to biochemically purified proteins and used in affinity-based selections assays. In the first area of this work, we address both these limitations by capitalizing on the power of affinity labeling. This allows DELs to be applied to protein targets within and on living cells and expands the power of DNA-encoding to the identification of small molecules with specific biological functions beyond binding. </p> <p>In the second area, we harnessed affinity labeling and DNA sequence analysis to develop multiplexed small molecule ligand binding assays. This method is the initial demonstration of split-and-pool ligand binding assays using DNA-linked small molecule probes. We used this approach in a high-throughput screening campaign to identify selective inhibitors by screening 1000 compounds against 5 bromodomain proteins concurrently. In addition, this approach was utilized to rank order the affinity of a 96-member library of DNA-linked ligands to a protein simultaneously, which significantly increases the throughput of ligand binding assays while keeps the cost low. </p> <p>Lastly, we developed proximity-induced selection assays to enrich ligands from DELs. This approach involves uncaging or installation of a biotin purification tag on the DNA construct either through photo-deprotection of a protected biotin group using a light emitting protein tag or by amine acylation using an engineered biotin ligase. Compared to affinity labeling-based selection approaches, this approach results in improved recovery of ligands and, at the same time, removes the onerous requirement of protein purification. The enzyme-mediated proximity labeling approach should serve as a convenient tool for molecular discovery with DELs. </p>

Advances in genome and proteome research have led to a dramatic increase in the number of macromolecular targets of interest to the life sciences. A solution-phase method to simultaneously reveal all ligand-target binding pairs from a single solution containing libraries of ligands and targets could significantly increase the efficiency and effectiveness of target-oriented screening efforts. Here, we describe interaction-dependent PCR (IDPCR), a solution-phase method to identify binding partners from combined libraries of small-molecule ligands and targets in a single experiment. Binding between DNA-linked targets and DNA-linked ligands induces formation of an extendable duplex. Extension links codes identifying the ligand and target into one selectively amplifiable DNA molecule. In a model selection, IDPCR resulted in the enrichment of DNA encoding all five known protein-ligand pairs out of 67,599 possible sequences.

<p>Protein kinases are essential in cell signaling pathways and are well-validated targets for cancer therapeutics and detection of activity levels. Yet, there remains a critical need for kinase inhibitors with high specificity and potency. The development of DNA-encoded library (DEL) technology dramatically facilitates the discovery of ligands to therapeutically relevant proteins. The preparation of combinatorial libraries followed by stringent selections can be exploited to rapidly generate hit molecules that bind to a large variety of targets.</p> <p>A combinatorial library of peptidomimetics is prepared and subjected to a selection for enriching molecules that can serve as substrates for tyrosine kinase Src. Non-natural substrate molecules are recognized by the anti-phosphotyrosine antibody during the selection. Using biophysical characterization assays including ADP-Glo and NMR, the resulting hits are investigated as novel peptide-substrate competitive inhibitors, as well as specific chemical probes that would benefit kinase activity detection. An ester derivative of the lead compound SrcDEL10 demonstrates cellular activity with inhibition of Src-dependent signaling in cell culture. Subsequently, our effort extends to parallel selections with a highly diverse-scaffold DEL on three cancer-related tyrosine kinases. Several hit molecules are validated with differential phosphotransfer activities among Src, Lyn, and Syk. Studies on the structure activity relationship of hit molecules produce selective kinase substrates with the lowest molecular weights reported to date. Potential bisubstrate inhibitors, showing above 8-fold Src selectivity over Lyn, are designed based on structures of selective substrates.</p> <p>Meanwhile, high sensitivity of DNA sequence analysis enables the development of specific and multiplexed activity assays. Using the substrate selection strategy, we develop a DNA-based kinome activity profiling assay using DNA conjugates of tyrosine kinase peptide substrates. Selective enrichment of phosphorylated probes enables activity detection by either quantitative PCR (qPCR) or parallel DNA sequencing. Results with detecting recombinant kinases demonstrated a low (~50 pM kinase) limit of detection. A library of 96 DNA-substrate conjugates enabled multiplexed tyrosine kinase assays in cell lysates in a manner analogous to peptide microarrays. This DNA-based assay potentially empowers the detection of tumor biomarkers with high specificity, lower detection limit, multiplexing capability, and high cost-effectiveness.</p> <p>Together, this research uses DNA-based technologies to assist developing new therapeutics and diagnostics, drug target validation, unveiling drug mechanisms of action, and understanding the role of protein phosphorylation in disease progression.</p>

Structure and functional study of glycans are highly challenging due to the difficulties in analyzing glycans and limited availability of samples for study. These limitations could be resolved by attaching DNA barcode to the glycan, which virtually represent glycan in further application, by increasing the sensitivity of detection by polymerase chain reaction (PCR), requiring minimal samples for analysis. Assuming bigger arena of DNA Encoded Glycan Libraries (DEGL) in future, we propose here a method for uniquely coding all glycans using computer program that can convert the structural information of glycans to DNA barcode. A unique and universal coding for glycans will benefit both synthesis and analysis of DEGLs. As a proof of principle study, a small DNA Encoded Glycan Library (DEGL) of blood and globo series glycan antigen and its application was demonstrated in detecting blood group and breast cancer from plasma.

DNA-encoded chemical libraries (DEL) allows an exhaustive chemical space sampling with a large-scale data consisting of compounds produced through combinatorial synthesis. This novel technology was utilized in the early drug discovery stages for robust hit identification and lead optimization. In this project, the aim was to build a Machine Learning- based QSAR model with conformal prediction for hit identification on two different target proteins, the DEL was assayed on. An initial investigation was conducted on a pilot project with 1000 compounds and the analyses and the conclusions drawn from this part were later applied to a larger dataset with 1.2 million compounds. With this classification model, the prediction of the compound activity in the DEL as well as in an external dataset was aimed to be analyzed with identification of the top hits to evaluate model’s performance and applicability. Support Vector Machine (SVM) and Random Forest (RF) models were built on both the pilot and the main datasets with different descriptor sets of Signature Fingerprints, RDKIT and CDK. In addition, an Autoencoder was used to supply data-driven descriptors on the pilot data as well. The Libsvm and the Liblinear implementations were explored and compared based on the models’ performances. The comparisons were made by considering the key concepts of conformal prediction such as the trade-off between validity and efficiency, observed fuzziness and the calibration against a range of significance levels. The top hits were determined by two sorting methods, credibility and p-value differences between the binary classes. The assignment of correct single-labels to the true actives over a wide range of significance levels regardless of the similarity of the test compounds to the training set was confirmed for the models. Furthermore, an accumulation of these true actives in the models’ top hit selections was observed according to the latter sorting method and additional investigations on the similarity and the building block enrichments in the top 50 and 100 compounds were conducted. The Tanimoto similarity demonstrated the model’s predictive power in selecting structurally dissimilar compounds while the building block enrichment analysis showed the selectivity of the binding pocket where the target protein B was determined to be more selective. All of these comparison methods enabled an extensive study on the model evaluation and performance. In conclusion, the Liblinear model with the Signature Fingerprints was concluded to give the best model performance for both the pilot and the main datasets with the considerations of the model performances and the computational power requirements. However, an external set prediction was not successful due to the low structural diversity in the DEL which the model was trained on.

<p>Polycomb repressive complex 1 (PRC1) is critical for mediating gene expression during development. Five chromobox (CBX) homolog proteins, CBX2,4,6,7,8, are incorporated into PRC1 complexes, where they mediate targeting to trimethylated lysine 27 of histone H3 (H3K27me3) via the N-terminal chromodomain (ChD). Individual CBX paralogs have been implicated as drug targets in cancer; however, high similarity in sequence and structure among the CBX ChDs provide a major obstacle in developing selective CBX ChD inhibitors. Here a selection of small, focused, DNA-encoded libraries (DELs) against multiple homologous ChDs was reported to identify modifications to a parental ligand that confer both selectivity and potency for the ChD of CBX8. This on-DNA, medicinal chemistry approach enabled the development of SW2_110A, a selective, cell-permeable inhibitor of the CBX8 ChD. SW2_110A binds CBX8 ChD with a Kd of 800 nM, with minimal 5-fold selectivity for CBX8 ChD over all other CBX paralogs in vitro. SW2_110A specifically inhibits the association of CBX8 with chromatin in cells and inhibits the proliferation of THP1 leukemia cells driven by the MLL-AF9 translocation. In THP1 cells, SW2_110A treatment significantly decreases expression of MLL-AF9 target genes, including HOXA9, validating the previously established role for CBX8 in MLL-AF9 transcriptional activation, and defining the ChD as necessary for this function. The success of SW2_110A provides great promise for the development of highly selective and cell permeable probes for the full CBX family. In addition, the approach taken provides a proof-of-principle demonstration of how DELs can be used iteratively for optimization of both ligand potency and selectivity.</p> <p>CBX2 is upregulated in a variety of cancers, particularly in advanced prostate cancers. Using CBX2 inhibitors to understand and target CBX2 in prostate cancer is highly desirable. Here, selections of focused DNA encoded libraries (DELs) were performed for the discovery of a selective CBX2 chromodomain probe, SW2_152F. SW2_152F binds to CBX2 ChD with a Kd of 80 nM and displays 24-1000-fold selectivity for CBX2 ChD over other CBX paralogs <em>in vitro</em>. SW2_152F is cell permeable, selectively inhibits CBX2 chromatin binding in cells, and blocks neuroendocrine differentiation of prostate cancer cell lines in response to androgen deprivation.</p> <p>Targeted covalent inhibitors (TCIs) are rationally designed inhibitors that bind to a target protein and specifically label a non-conserved amino acid on proteins by means of reactive moieties (warheads). TCIs typically function by two steps, in which inhibitors first non-covalently bind to the target protein and then covalent bond formation occurs between the inhibitor- warhead and a proximal nucleophile on protein. Covalent inhibitors or drugs have prolonged target engagement and enhanced pharmacokinetic potency in vivo, compared to non-covalent molecules. Strategies to develop effective warheads of TCIs have been reported for labeling different nucleophilic amino acid residues, of which cysteine and lysine are the most established for covalent labeling. Tyrosine is recently becoming an attractive nucleophile for TCIs as an alternative choice, yet currently developed warheads that label tyrosine do so with modest specificity over other side chains. Here, I report the development of novel Mannich electrophiles and use those electrophiles as covalent warheads on an inhibitor to specifically target tyrosine in protein labeling. To my knowledge, this is first demonstration of the use of Mannich electrophiles in covalent inhibitors. Specifically, I leveraged a previously developed CBX8 chromodomain inhibitor to specifically label a non-conserved tyrosine within CBX8 using cyclic imine derivatives as warheads. This ligand-directed, specific tyrosine conjugation on CBX8 but not on CBX2, significantly improves both the potency and selectivity of inhibition. Biochemical, proteomic, and cellular validation further showed the cyclic imine covalent inhibitors can increase both potency and selectivity to the target protein CBX8 in cells, serving as a robust chemical probe for target function evaluation and modulation. This new type of tyrosine labeling warhead is a useful addition to the toolbox of medicinal chemists for covalent inhibitor development.</p> <p>The following chapters are modified from following publications, with permissions from Sijie Wang, Emily C.Dykhuizen, and Casey J. Krusemark. </p> <p>Wang, S., Denton, K. E., Hobbs, K. F., Weaver, T., McFarlane, J. M., Connelly, K. E., Gignac, M.C., Milosevich, N., Hof, F., Paci, I., Musselman, C. A., Dykhuizen, E.C., Krusemark, C. J. Optimization of Ligands Using Focused DNA-Encoded Libraries To Develop a Selective, Cell-Permeable CBX8 Chromodomain Inhibitor. <em>ACS Chem Biol. </em>2020, 15, 112-131</p> <p>Wang, S., Alpsoy, A., Sood, S., Ordonez-Rubiano, S. C., Dhiman, A., Sun, Y., Krusemark, C. J., Dykhuizen, E. C. A Potent, Selective CBX2 Chromodomain Ligand and its Cellular Activity During Prostate Cancer Neuroendocrine Differentiation. <em>ChemBioChem.</em> 2021, 22, 2335-2344</p> <p>Wang, S., Ordonez-Rubiano, S. C., Dhiman, A., Jiao G., Strohmier B. P., Krusemark, C. J., Dykhuizen, E. C. Polycomb Group proteins in cancer: multifaceted functions and strategies for modulation Modulators. <em>NAR Cancer</em>. 2021, 3, zcab039</p>

The fast development of DNA-encoded chemical libraries (DECL) in the past 10 years has received great attention from pharmaceutical industries. It applies the selection approach for small molecular drug discovery. Because of the limited choices of DNA-compatible chemical reactions, most DNA-encoded chemical libraries have a narrow structural diversity and low synthetic yield. There is also a poor correlation between the ranking of compounds resulted from analyzing the sequencing data and the affinity measured through biochemical assays. By combining DECL with dynamical chemical library, the resulting DNA-encoded dynamic library (EDCCL) explores the thermodynamic equilibrium of reversible reactions as well as the advantages of DNA encoded compounds for manipulation/detection, thus leads to enhanced signal-to-noise ratio of the selection process and higher library quality. However, the library dynamics are caused by the weak interactions between the DNA strands, which also result in relatively low affinity of the bidentate interaction, as compared to a stable DNA duplex. To take advantage of both stably assembled dual-pharmacophore libraries and EDCCLs, we extended the concept of EDCCLs to heat-induced EDCCLs (hi-EDCCLs), in which the heat-induced recombination process of stable DNA duplexes and affinity capture are carried out separately. To replace the extremely laborious and repetitive manual process, a fully automated device will facilitate the use of DECL in drug discovery. Herein we describe a novel lab-on-a-chip platform for high throughput drug discovery with hi-EDCCL. A microfluidic system with integrated actuation was designed which is able to provide a continuous sample circulation by reducing the volume to a minimum. It consists of a cooled and a heated chamber for constant circulation. The system is capable to generate stable temperatures above 75 °C in the heated chamber to melt the double strands of the DNA and less than 15 °C in the cooled chamber, to reanneal the shuffled library. In the binding chamber (the cooled chamber) specific retaining structures are integrated. These hold back beads functionalized with the target protein, while the chamber is continuously flushed with library molecules. Afterwards the whole system can be flushed with buffer to wash out unspecific bound molecules. Finally the protein-loaded beads with attached molecules can be eluted for further investigation