Bruce K. Hua

Diversity-oriented synthesis (DOS) is a powerful strategy to prepare molecules with underrepresented features in commercial screening collections, resulting in the elucidation of novel biological mechanisms. In parallel to the development of DOS, DNA-encoded libraries (DELs) have emerged as an effective, efficient screening strategy to identify protein binders. Despite recent advancements in this field, most DEL syntheses are limited by the presence of sensitive DNA-based constructs. Here, we describe the design, synthesis, and validation experiments performed for a 3.7 million-member DEL, generated using diverse skeleton architectures with varying exit vectors and derived from DOS, to achieve structural diversity beyond what is possible by varying appendages alone. We also show screening results for three diverse protein targets. We will make this DEL available to the academic scientific community to increase access to novel structural features and accelerate early-phase drug discovery.

The hallmark of a molecular glue is its ability to induce cooperative protein–protein interactions, leading to the formation of a ternary complex, despite weaker binding towards one or both individual proteins. Notably, the extent of cooperativity distinguishes molecular glues from bifunctional compounds, a second class of inducers of protein–protein interactions. However, apart from serendipitous discovery, there have been limited rational screening strategies for the high cooperativity exhibited by molecular glues. Here, we propose a binding-based screen of DNA-barcoded compounds on a target protein in the presence and absence of a presenter protein, using the “presenter ratio”, the ratio of ternary enrichment to binary enrichment, as a predictive measure of cooperativity. Through this approach, we identified a range of cooperative, noncooperative, and uncooperative compounds in a single DNA-encoded library screen with bromodomain (BRD)9 and the VHL–elongin C–elongin B (VCB) complex. Our most cooperative hit compound, 13-7 , exhibits micromolar binding affinity to BRD9 but nanomolar affinity for the ternary complex with BRD9 and VCB, with cooperativity comparable to classical molecular glues. This approach may enable the discovery of molecular glues for pre-selected proteins and thus facilitate the transition to a new paradigm of molecular therapeutics.

Robust, generalizable approaches to identify compounds efficiently with undesirable mechanisms of action in complex cellular assays remain elusive. Such a process would be useful for hit triage during high-throughput screening and, ultimately, predictive toxicology during drug development. Here we generate cell painting and cellular health profiles for 218 prototypical cytotoxic and nuisance compounds in U-2 OS cells in a concentration-response format. A diversity of compounds that cause cellular damage produces bioactive cell painting morphologies, including cytoskeletal poisons, genotoxins, nonspecific electrophiles, and redox-active compounds. Further, we show that lower quality lysine acetyltransferase inhibitors and nonspecific electrophiles can be distinguished from more selective counterparts. We propose that the purposeful inclusion of cytotoxic and nuisance reference compounds such as those profiled in this resource will help with assay optimization and compound prioritization in complex cellular assays like cell painting.

Diversity-oriented synthesis (DOS)is a powerful strategy to prepare molecules with underrepresented features in commercial screening collections, resulting in the elucidation of novel biological mechanisms. In parallel to the development of DOS, DNA-encoded libraries (DELs) have emerged as an effective, efficient screening strategy to identify protein binders. Despite recent advancements in this field, most DEL syntheses are limited by the presence of sensitive DNA-based constructs. Here, we describe the design, synthesis, and validation experiments performed for a 3.7 million-member DEL, generated using diverse skeleton architectures with varying exit vectors, derived from DOS, to achieve structural diversity beyond what is possible by varying appendages alone. We will make this DEL available to the academic scientific community to increase access to novel structural features and accelerate early-phase drug discovery.

DNA-encoded library (DEL) screening and quantitative structure-activity relationship (QSAR) modeling are two techniques used in drug discovery to find novel small molecules that bind a protein target. Applying QSAR modeling to DEL selection data can facilitate the selection of compounds for off-DNA synthesis and evaluation. Such a combined approach has been done recently by training binary classifiers to learn DEL enrichments of aggregated "disynthons" in order to accommodate the sparse and noisy nature of DEL data. However, a binary classification model cannot distinguish between different levels of enrichment, and information is potentially lost during disynthon aggregation. Here, we demonstrate a regression approach to learning DEL enrichments of individual molecules, using a custom negative-log-likelihood loss function that effectively denoises DEL data and introduces opportunities for visualization of learned structure-activity relationships. Our approach explicitly models the Poisson statistics of the sequencing process used in the DEL experimental workflow under a frequentist view. We illustrate this approach on a DEL dataset of 108,528 compounds screened against carbonic anhydrase (CAIX), and a dataset of 5,655,000 compounds screened against soluble epoxide hydrolase (sEH) and SIRT2. Due to the treatment of uncertainty in the data through the negative-log-likelihood loss used during training, the models can ignore low-confidence outliers. While our approach does not demonstrate a benefit for extrapolation to novel structures, we expect our denoising and visualization pipeline to be useful in identifying structure-activity trends and highly enriched pharmacophores in DEL data. Further, this approach to uncertainty-aware regression modeling is applicable to other sparse or noisy datasets where the nature of stochasticity is known or can be modeled; in particular, the Poisson enrichment ratio metric we use can apply to other settings that compare sequencing count data between two experimental conditions.

Organic chemists are able to synthesize molecules in greater number and chemical complexity than ever before. Yet, a majority of these compounds go untested in biological systems, and those that do are often tested long after the chemist can incorporate the results into synthetic planning. We propose the use of high-dimensional “multiplex” assays, which are capable of measuring thousands of cellular features in one experiment, to annotate rapidly and inexpensively the biological activities of newly synthesized compounds. This readily accessible and inexpensive “real-time” profiling method can be used in a prospective manner to facilitate, for example, the efficient construction of performance-diverse small-molecule libraries that are enriched in bioactives. Here, we demonstrate this concept by synthesizing ten triads of constitutionally isomeric compounds via complexity-generating photochemical and thermal rearrangements and measuring compound-induced changes in cellular morphology via an imaging-based “cell painting” assay. Our results indicate that real-time biological annotation can inform optimization efforts and library syntheses by illuminating trends relating to biological activity that would be difficult to predict if only chemical structure were considered. We anticipate that probe and drug discovery will benefit from the use of optimization efforts and libraries that implement this approach.

Actinophyllic acid is a biologically active indole alkaloid with a unique structural framework that incorporates five contiguous stereocenters. A total synthesis of (±)-actinophyllic acid has been completed that proceeds in only 10 steps from readily available, known compounds and with the isolation of nine intermediates. The synthesis features a novel cascade of reactions of N-stabilized carbocations with π-nucleophiles to create the tetracyclic core of actinophyllic acid in a single chemical operation. This pivotal cascade sequence generates substructures of the actinophyllic acid core that are not otherwise accessible, and one key intermediate was modified to furnish several novel compounds having potentially promising anticancer activity, one of which induces cell death in a wide range of cancer cell lines.