ABSTRACT
Targeted protein degradation (TPD) is a promising approach in drug discovery for degrading proteins implicated in diseases. A key step in this process is the formation of a ternary complex where a heterobifunctional molecule induces proximity of an E3 ligase to a protein of interest (POI), thus facilitating ubiquitin transfer to the POI. In this work, we characterize 3 steps in the TPD process. (1) We simulate the ternary complex formation of SMARCA2 bromodomain and VHL E3 ligase by combining hydrogen-deuterium exchange mass spectrometry with weighted ensemble molecular dynamics (MD). (2) We characterize the conformational heterogeneity of the ternary complex using Hamiltonian replica exchange simulations and small-angle X-ray scattering. (3) We assess the ubiquitination of the POI in the context of the full Cullin-RING Ligase, confirming experimental ubiquitinomics results. Differences in degradation efficiency can be explained by the proximity of lysine residues on the POI relative to ubiquitin.
Subject(s)
Cullin Proteins , Molecular Dynamics Simulation , Cullin Proteins/metabolism , Deuterium , Lysine/metabolism , Mass Spectrometry , Proteolysis , Ubiquitin/metabolism , Ubiquitin-Protein Ligases/metabolism , UbiquitinationABSTRACT
BACKGROUND/AIM: NEAT is a validated prognostic model that calculates survival estimates based on the number of active tumors, ECOG performance status, albumin, and primary tumor site. Since models are imperfect, we hypothesized that experienced clinicians could predict the survival of patients with metastatic cancer better than a validated prognostic model alone, thereby quantifying the previously unmeasured value of clinical judgment. PATIENTS AND METHODS: This prospective, single-institution cohort study conducted at a large community hospital recruited 73 patients with metastatic cancer referred to radiation oncology between October 2016 and December 2017. The consulting nurse and physician were prospectively surveyed on whether the patient would survive a longer or shorter duration than the calculated NEAT survival estimates. The accuracy of predictions between groups was assessed using the McNemar's chi-squared test. RESULTS: The median survival for enrolled patients was 9.2 months. Nursing and physician predictions were similarly accurate (61.6% vs. 60.3%, p=0.85). The accuracy of confident clinical predictions was similar to less confident predictions (64.2% vs. 58.2%, p=0.46). Radiation dose intensity was informed by predicted survival, and median survival was significantly higher in patients receiving an EQD2≥40 (17 months vs. 2 months, p<0.001). CONCLUSION: Experienced clinicians, both nurses and oncologists, have insight that modestly supplements the accuracy of a validated model to predict survival in patients with advanced cancer.
