Ubiquitination controls the stability of most cellular proteins, and its deregulation contributes to human diseases including cancer. Deubiquitinases remove ubiquitin from proteins, and their inhibition can induce the degradation of selected proteins, potentially including otherwise 'undruggable' targets. For example, the inhibition of ubiquitin-specific protease 7 (USP7) results in the degradation of the oncogenic E3 ligase MDM2, and leads to re-activation of the tumour suppressor p53 in various cancers. Here we report that two compounds, FT671 and FT827, inhibit USP7 with high affinity and specificity in vitro and within human cells. Co-crystal structures reveal that both compounds target a dynamic pocket near the catalytic centre of the auto-inhibited apo form of USP7, which differs from other USP deubiquitinases. Consistent with USP7 target engagement in cells, FT671 destabilizes USP7 substrates including MDM2, increases levels of p53, and results in the transcription of p53 target genes, induction of the tumour suppressor p21, and inhibition of tumour growth in mice.

The transcription factor BCL6 is a known driver of oncogenesis in lymphoid malignancies, including diffuse large B cell lymphoma (DLBCL). Disruption of its interaction with transcriptional repressors interferes with the oncogenic effects of BCL6. We used a structure-based drug design to develop highly potent compounds that block this interaction. A subset of these inhibitors also causes rapid ubiquitylation and degradation of BCL6 in cells. These compounds display significantly stronger induction of expression of BCL6-repressed genes and anti-proliferative effects than compounds that merely inhibit co-repressor interactions. This work establishes the BTB domain as a highly druggable structure, paving the way for the use of other members of this protein family as drug targets. The magnitude of effects elicited by this class of BCL6-degrading compounds exceeds that of our equipotent non-degrading inhibitors, suggesting opportunities for the development of BCL6-based lymphoma therapeutics.

Here we apply the computational solvent mapping (CS-Map) algorithm toward the in silico identification of hot spots, that is, regions of protein binding sites that are major contributors to the binding energy and, hence, are prime targets in drug design. The CS-Map algorithm, developed for binding site characterization, moves small organic functional groups around the protein surface and determines their most energetically favorable binding positions. The utility of CS-Map algorithm toward the prediction of hot spot regions in druggable binding pockets is illustrated by three test systems: (1) renin aspartic protease, (2) a set of previously characterized druggable proteins, and (3) E. coli ketopantoate reductase. In each of the three studies, existing literature was used to verify our results. Based on our analyses, we conclude that the information provided by CS-Map can contribute substantially to the identification of hot spots, a necessary predecessor of fragment-based drug discovery efforts.

DNA-encoded chemical libraries (DELs) provide a high-throughput and cost-effective route for screening billions of unique molecules for binding affinity for diverse protein targets. Identifying candidate compounds from these libraries involves affinity selection, DNA sequencing, and measuring enrichment in a sample pool of DNA barcodes. Successful detection of potent binders is affected by many factors, including selection parameters, chemical yields, library amplification, sequencing depth, sequencing errors, library sizes, and the chosen enrichment metric. To date, there has not been a clear consensus about how enrichment from DEL selections should be measured or reported. We propose a normalized z-score enrichment metric using a binomial distribution model that satisfies important criteria that are relevant for analysis of DEL selection data. The introduced metric is robust with respect to library diversity and sampling and allows for quantitative comparisons of enrichment of n-synthons from parallel DEL selections. These features enable a comparative enrichment analysis strategy that can provide valuable information about hit compounds in early stage drug discovery.

Mutations at the arginine residue (R132) in isocitrate dehydrogenase 1 (IDH1) are frequently identified in various human cancers. Inhibition of mutant IDH1 (mIDH1) with small molecules has been clinically validated as a promising therapeutic treatment for acute myeloid leukemia and multiple solid tumors. Herein, we report the discovery and optimization of a series of quinolinones to provide potent and orally bioavailable mIDH1 inhibitors with selectivity over wild-type IDH1. The X-ray structure of an early lead 24 in complex with mIDH1-R132H shows that the inhibitor unexpectedly binds to an allosteric site. Efforts to improve the in vitro and in vivo absorption, distribution, metabolism, and excretion (ADME) properties of 24 yielded a preclinical candidate 63. The detailed preclinical ADME and pharmacology studies of 63 support further development of quinolinone-based mIDH1 inhibitors as therapeutic agents in human trials.