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Fulco, U. L.

Publications and source records attributed to Fulco, U. L..

2 recordsLinked to original sources

SlytheRINs: using graph parameters and residue interaction networks to analyze protein dynamics and structural ensembles

Establishing the relationship between protein structure and functional behavior remains a significant challenge. The recognition that proteins are inherently dynamic, with functions often dependent on conformational changes, is increasingly accepted. Among computational approaches for elucidating protein properties, Residue Interaction Network (RIN) analysis has emerged as a powerful tool. However, conventional RIN analysis is constrained by its reliance on single, static protein structures, which fail to capture the flexibility inherent in dynamic protein folding transitions. To address these limitations, SlytheRINs is introduced as an interactive tool designed for comparative analysis of protein conformations via RINs. SlytheRINs enables dynamic ensemble analysis by decomposing interaction network data across multiple conformations of a single protein and providing detailed residue-interaction mapping across conformational changes via graph parameters in comparative plots. Applying these principles, the conformational variations of the wild-type and a pathogenic variant (G188R) of the human Glucose-6-Phosphatase (G6PC1) catalytic subunit were compared to identify fluctuations in both chemical interactions and graph features associated with conformational changes induced by the residue modification. The analyses identified key shifts in dynamic residue interactions in the protein variant that compromise substrate binding and the catalytic site, thereby elucidating the impact on G6PC1s dynamic behavior and the resulting activity loss. AvailabilityThe source code for SlytheRINs is available on GitHub (https://github.com/evomol-lab/SlytheRINs), while the web tool and documentation are available at https://slytherins.streamlit.app.

bioinformatics↗

Immunoinformatics Approach to Engineer a Multi-Epitope Vaccine Against SdrG in Skin Commensal Staphylococcus epidermidis

The human skin serves as a dynamic ecosystem for beneficial commensal bacteria such as Staphylococcus epidermidis, which play a crucial role in maintaining skin barrier integrity and modulating immune responses. Remarkably, recent research has demonstrated that the skin can function as a natural vaccination site, producing specific antibodies against commensal microbes without inducing inflammation. However, S. epidermidis can transition into an opportunistic pathogen in clinical settings, forming resilient biofilms on medical implants and exhibiting increasing resistance to antibiotics (MRSE), posing a significant healthcare challenge. To address this challenge, advanced immunoinformatics strategies were leveraged to design a novel multi-epitope vaccine targeting the SdrG protein, a key mediator of S. epidermidis biofilm formation. The vaccines binding dynamics with Toll-like receptor 4 (TLR4) were evaluated through computational analyses, including molecular docking and 500-nanosecond molecular dynamics (MD) simulations. Stability assessments via Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and Radius of Gyration (Rg) confirmed that the vaccine-TLR4 complex achieved structural equilibrium, with TLR4 maintaining rigidity while the vaccine exhibited adaptive flexibility for optimal binding. The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method revealed a strong binding affinity, with a peak free energy of -52.73 kcal/mol and an average of -24.72 {+/-} 9.5989 kcal/mol over the last 50 ns, indicating a thermodynamically favorable interaction. Furthermore, in silico cloning validated the vaccines expressibility, with successful integration into the pET-Sangamo-His vector (8560 bp) for optimal E. coli production. These findings underscore the vaccines potential to elicit a robust immune response by stably engaging TLR4, a critical step in innate immune activation. By combining computational precision with immunological insights, this study lays a foundation for developing an effective prophylactic strategy against S. epidermidis biofilm-associated infections.

immunology↗