Corrigendum: Targeting the N-terminus domain of the coronavirus nucleocapsid protein induces abnormal oligomerization via allosteric modulation.

[This corrects the article DOI: 10.3389/fmolb.2022.871499.].

Targeting the N-Terminus Domain of the Coronavirus Nucleocapsid Protein Induces Abnormal Oligomerization via Allosteric Modulation.

Epidemics caused by coronaviruses (CoVs), namely the severe acute respiratory syndrome (SARS) (2003), Middle East respiratory syndrome (MERS) (2012), and coronavirus disease 2019 (COVID-19) (2019), have triggered a global public health emergency. Drug development against CoVs is inherently arduous. The nucleocapsid (N) protein forms an oligomer and facilitates binding with the viral RNA genome, which is critical in the life cycle of the virus. In the current study, we found a potential allosteric site (Site 1) using PARS, an online allosteric site predictor, in the CoV N-N-terminal RNA-binding domain (NTD) to modulate the N protein conformation. We identified 5-hydroxyindole as the lead via molecular docking to target Site 1. We designed and synthesized four 5-hydroxyindole derivatives, named P4-1 to P4-4, based on the pose of 5-hydroxyindole in the docking model complex. Small-angle X-ray scattering (SAXS) data indicate that two 5-hydroxyindole compounds with higher hydrophobic R-groups mediate the binding between N-NTD and N-C-terminal dimerization domain (CTD) and elicit high-order oligomerization of the whole N protein. Furthermore, the crystal structures suggested that these two compounds act on this novel cavity and create a flat surface with higher hydrophobicity, which may mediate the interaction between N-NTD and N-CTD. Taken together, we discovered an allosteric binding pocket targeting small molecules that induces abnormal aggregation of the CoV N protein. These novel concepts will facilitate protein-protein interaction (PPI)-based drug design against various CoVs.

Breast cancer surgery volume-cost associations: hierarchical linear regression and propensity score matching analysis in a nationwide Taiwan population.

BACKGROUND: No outcome studies have longitudinally and systematically compared the effects of hospital and surgeon volume on breast cancer surgery costs in an Asian population. This study purposed to evaluate the use of hospital and surgeon volume for predicting breast cancer surgery costs. METHODS: This cohort study retrospectively analyzed 97,215 breast cancer surgeries performed from 1996 to 2010. Relationships between volumes and costs were analyzed by propensity score matching and by hierarchical linear regression. RESULTS: The mean breast cancer surgery costs for all breast cancer surgeries performed during the study period was $1485.3 dollars. The average breast cancer surgery costs for high-volume hospitals and surgeons were 12% and 26% lower, respectively, than those for low-volume hospitals and surgeons. Propensity score matching analysis showed that the average breast cancer surgery costs for breast cancer surgery procedures performed by high-volume hospitals ($1428.6 dollars) significantly differed from the average breast cancer surgery costs of those performed by low-/medium-volume hospitals ($1514.0 dollars) and that the average breast cancer surgery costs of procedures performed by high-volume surgeons ($1359.0 dollars) significantly differed from the average breast cancer surgery costs of those performed by low-/medium-volume surgeons ($1550.3 dollars) (P < 0.001). CONCLUSIONS: The factors significantly associated with hospital resource utilization for this procedure included age, surgical type, Charlson co-morbidity index score, hospital type, hospital volume, and surgeon volume. The data indicate that analyzing and emulating the treatment strategies used by high-volume hospitals and by high-volume surgeons may reduce overall breast cancer surgery costs.