A chemical probe to modulate human GID4 Pro/N-degron interactions.

The C-terminal to LisH (CTLH) complex is a ubiquitin ligase complex that recognizes substrates with Pro/N-degrons via its substrate receptor Glucose-Induced Degradation 4 (GID4), but its function and substrates in humans remain unclear. Here, we report PFI-7, a potent, selective and cell-active chemical probe that antagonizes Pro/N-degron binding to human GID4. Use of PFI-7 in proximity-dependent biotinylation and quantitative proteomics enabled the identification of GID4 interactors and GID4-regulated proteins. GID4 interactors are enriched for nucleolar proteins, including the Pro/N-degron-containing RNA helicases DDX21 and DDX50. We also identified a distinct subset of proteins whose cellular levels are regulated by GID4 including HMGCS1, a Pro/N-degron-containing metabolic enzyme. These data reveal human GID4 Pro/N-degron targets regulated through a combination of degradative and nondegradative functions. Going forward, PFI-7 will be a valuable research tool for investigating CTLH complex biology and facilitating development of targeted protein degradation strategies that highjack CTLH E3 ligase activity.

Chemical tools for the Gid4 subunit of the human E3 ligase C-terminal to LisH (CTLH) degradation complex.

We have developed a novel chemical handle (PFI-E3H1) and a chemical probe (PFI-7) as ligands for the Gid4 subunit of the human E3 ligase CTLH degradation complex. Through an efficient initial hit-ID campaign, structure-based drug design (SBDD) and leveraging the sizeable Pfizer compound library, we identified a 500 nM ligand for this E3 ligase through file screening alone. Further exploration identified a vector that is tolerant to addition of a linker for future chimeric molecule design. The chemotype was subsequently optimized to sub-100 nM Gid4 binding affinity for a chemical probe. These novel tools, alongside the suitable negative control also identified, should enable the interrogation of this complex human E3 ligase macromolecular assembly.

A data science roadmap for open science organizations engaged in early-stage drug discovery.

The Structural Genomics Consortium is an international open science research organization with a focus on accelerating early-stage drug discovery, namely hit discovery and optimization. We, as many others, believe that artificial intelligence (AI) is poised to be a main accelerator in the field. The question is then how to best benefit from recent advances in AI and how to generate, format and disseminate data to enable future breakthroughs in AI-guided drug discovery. We present here the recommendations of a working group composed of experts from both the public and private sectors. Robust data management requires precise ontologies and standardized vocabulary while a centralized database architecture across laboratories facilitates data integration into high-value datasets. Lab automation and opening electronic lab notebooks to data mining push the boundaries of data sharing and data modeling. Important considerations for building robust machine-learning models include transparent and reproducible data processing, choosing the most relevant data representation, defining the right training and test sets, and estimating prediction uncertainty. Beyond data-sharing, cloud-based computing can be harnessed to build and disseminate machine-learning models. Important vectors of acceleration for hit and chemical probe discovery will be (1) the real-time integration of experimental data generation and modeling workflows within design-make-test-analyze (DMTA) cycles openly, and at scale and (2) the adoption of a mindset where data scientists and experimentalists work as a unified team, and where data science is incorporated into the experimental design.

A Second-Generation Oral SARS-CoV-2 Main Protease Inhibitor Clinical Candidate for the Treatment of COVID-19.

Despite the record-breaking discovery, development and approval of vaccines and antiviral therapeutics such as Paxlovid, coronavirus disease 2019 (COVID-19) remained the fourth leading cause of death in the world and third highest in the United States in 2022. Here, we report the discovery and characterization of PF-07817883, a second-generation, orally bioavailable, SARS-CoV-2 main protease inhibitor with improved metabolic stability versus nirmatrelvir, the antiviral component of the ritonavir-boosted therapy Paxlovid. We demonstrate the in vitro pan-human coronavirus antiviral activity and off-target selectivity profile of PF-07817883. PF-07817883 also demonstrated oral efficacy in a mouse-adapted SARS-CoV-2 model at plasma concentrations equivalent to nirmatrelvir. The preclinical in vivo pharmacokinetics and metabolism studies in human matrices are suggestive of improved oral pharmacokinetics for PF-07817883 in humans, relative to nirmatrelvir. In vitro inhibition/induction studies against major human drug metabolizing enzymes/transporters suggest a low potential for perpetrator drug-drug interactions upon single-agent use of PF-07817883.