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Olabisi-Adeniyi, E.

Publications and source records attributed to Olabisi-Adeniyi, E..

2 recordsLinked to original sources

A structure-guided pipeline yields peptide inhibitors that disarm fungal peptidase-driven virulence and resistance

Fungal infections are a major global health challenge, with current antifungal therapies limited by toxicity, cost, and resistance. For Cryptococcus neoformans, key virulence factors that initiate and sustain infection are regulated by fungal peptidases to produce a polysaccharide capsule, promote immune evasion, and support antifungal resistance. These peptidases represent promising targets for antivirulent therapeutic strategies. Here, we developed a computational pipeline to predict and design peptide- and protein-based inhibitors against cryptococcal peptidases. Specifically, we targeted three virulence-associated peptidases: Rim13 (cysteine), May1 (aspartic), and CnMpr1 (metallo). Cysteine peptidase inhibition decreased capsule/cell size ratios without impeding fungal growth and reduced fungal survival within macrophages. Similarly, aspartic peptidase inhibition enhanced fungal clearance within alveolar macrophages and disrupted biofilm formation with additive effects towards fluconazole susceptibility in resistant strains. Additionally, metallopeptidase inhibition through catalytic zinc chelation and blocked substrate binding led to enhanced enzymatic inhibition and reduced in vitro blood-brain barrier crossing. Moreover, an in vivo larval model assessing inhibitor efficacy produced additive effects with fluconazole and lacked host cell cytotoxicity and fungicidal properties, reinforcing anti-virulence mechanisms and therapeutic potential while limiting the evolution of resistance. Further, global proteome profiling of inhibitor treated cells defined a mechanism of cell wall disruption, impeding fungal virulence. Taken together, the designed peptidase inhibitors exhibited potent antifungal activity without harming mammalian cells, establishing a predictive framework for rational scaffold design of next-generation antifungals that disarm the pathogen enabling immune-mediated clearance.

microbiology↗

ProteoPlotter: an executable proteomics visualization tool compatible with Perseus

Mass spectrometry-based proteomics experiments produce complex datasets requiring robust statistical testing and effective visualization tools to ensure meaningful conclusions are drawn. The publicly-available proteomics data analysis platform, Perseus, is extensively used to perform such tasks, but opportunities to enhance visualization tools and promote accessibility of the data exist. In this study, we developed ProteoPlotter, a user-friendly, executable tool to complement Perseus for visualization of proteomics datasets. ProteoPlotter is built on the Shiny framework for R programming and enables illustration of multi-dimensional proteomics data. ProteoPlotter provides mapping of one-dimensional enrichment analyses, enhanced adaptability of volcano plots through incorporation of Gene Ontology terminology, visualization of 95% confidence intervals in principal component analysis plots using data ellipses, and customizable features. ProteoPlotter is designed for intuitive use by biological and computational researchers alike, providing descriptive instructions (i.e., Help Guide) for preparing and uploading Perseus output files. Herein, we demonstrate the application of ProteoPlotter towards microbial proteome remodeling under altered nutrient conditions and highlight the diversity of visualizations enabled with the platform for improved biological characterization. Through its comprehensive data visualization capabilities, linked to the power of Perseus data handling and statistical analyses, ProteoPlotter facilitates a deeper understanding of proteomics data to drive new biological discoveries.

bioinformatics↗