Biology subjects

Alfonso, S.

Publications and source records attributed to Alfonso, S..

2 recordsLinked to original sources

bioRxiv2026

The NanoBridge system for targeted post-translational modification of challenging proteins

The ability to edit posttranslational modifications (PTMs) of endogenous proteins within cells is essential for precisely delineating the biological roles of PTMs and for developing targeted therapeutics. While the paradigm of chemically induced proximity (CIP) has advanced this field by enabling the recruitment of PTM enzymes to the proximity of proteins of interest (POIs), CIP requires small-molecule binders that are difficult to obtain for proteins without well-defined binding pockets. In principle, the use of biomolecular ligands that target disordered proteins should overcome this limitation. In this work, we developed the NanoBridge as a modular and generalizable platform to enable PTM editing of challenging POIs in live cells. The NanoBridge employs biologic binders to transiently direct the small protein tag FKBP12F36V to unmodified target proteins, thereby enabling multiplex PTM editing upon use of heterobifunctional small molecules that recruit endogenous PTM enzymes. Compared with existing approaches, the NanoBridge offers greater flexibility to induce multiple types of PTMs on the same POI while providing precise temporal control and avoiding the introduction of exogenous PTM writers. Using eight protein binders targeting three structurally diverse and largely unstructured proteins - BCL11A (a hemoglobin regulator), KRAS (a cancer driver), and p53 (a tumor suppressor) - the NanoBridge mediated targeted degradation, phosphorylation, and acetylation in a rapid, reversible, and temporally controlled manner. As such, the NanoBridge represents a versatile strategy for the targeted modulation of endogenous proteins, particularly those lacking accessible small molecule ligands, and presents new opportunities for investigating the physiology of PTMs on challenging proteins.

biochemistry↗

bioRxiv2021

COVID-19 virtual patient cohort reveals immune mechanisms driving disease outcomes

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results indicate that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation that was mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings identify biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation. Author summaryUnderstanding of how the immune system responds to SARS-CoV-2 infections is critical for improving diagnostic and treatment approaches. Identifying which immune mechanisms lead to divergent outcomes can be clinically difficult, and experimental models and longitudinal data are only beginning to emerge. In response, we developed a mechanistic, mathematical and computational model of the immunopathology of COVID-19 calibrated to and validated against a broad set of experimental and clinical immunological data. To study the drivers of severe COVID-19, we used our model to expand a cohort of virtual patients, each with realistic disease dynamics. Our results identify key processes that regulate the immune response to SARS-CoV-2 infection in virtual patients and suggest viable therapeutic targets, underlining the importance of a rational approach to studying novel pathogens using intra-host models.

immunology↗