Biology subjects

Scaramozzino, D.

Publications and source records attributed to Scaramozzino, D..

4 recordsLinked to original sources

bioRxiv2026

Leveraging elastic networks in a coarse-grained brownian simulation framework for protein conformational dynamics

Protein dynamics is fundamental to understand mechanisms. Although atomistic Molecular Dynamics (MD) remains the gold standard for predicting protein motions, its computational cost limits applications at large scales. Here, we present a coarse-grained (CG) simulation framework that combines Elastic Network Models (ENMs) with implicit-solvent Brownian Dynamics (BD) to efficiently generate protein conformational ensembles from native states. Benchmarking the method on more than 8,500 proteins against large datasets of atomistic MD trajectories and multi-state ensembles from Nucleic Magnetic Resonance (NMR), we show that short ENM-BD simulations can reproduce the residue fluctuation profiles and the dominant protein motions with remarkable accuracy. Correlations of residue fluctuations often exceeded 80%, with many proteins showing agreements above 90%, while Principal Component Analysis (PCA) revealed strong correspondences between the essential motions in the ENM-BD simulations and those observed in MD and NMR ensembles. Following CG-to-all-atom reconstruction and short energy minimization, the ENM-BD conformers also achieve high stereochemical quality, which enables their usage in downstream atomistic applications. Finally, we show that the stochastic dynamics emerging from BD trajectories closely aligns with the normal modes encoded in the underlying elastic network, highlighting that most of the intrinsic dynamics of proteins is already embedded in their native 3D topology.

biophysics↗

bioRxiv2026

Mutation-induced reshaping of protein conformational dynamics revealed by a coarse-grained modeling framework

Disease-related missense mutations reshape protein conformational energy landscapes, thereby altering biological function. However, mechanistically linking sequence variation to changes in conformational dynamics remains challenging for both experimental and computational approaches. Here, we introduce an internal-coordinate-based, essential-dynamics-refined elastic network model (ICed-ENM) that improves the physical fidelity of normal modes while capturing subtle mutation-induced side-chain effects and preserving computational efficiency. By constraining bond-length and bond-angle fluctuations and refining mode subspaces against experimentally observed collective motions, ICed-ENM provides a stable, structure-encoded description of intrinsic protein dynamics. Building on this framework, we developed a systematic mutation-scanning analysis that quantifies mutation impact as changes in vibrational entropy, providing a dynamic measure of mutation-induced redistribution within conformational energy landscapes. Validation against all-atom molecular dynamics simulations demonstrates that residues predicted as mutation hot spots induce substantial reshaping of free-energy landscapes, consistent with altered intrinsic conformational dynamics. Extending this analysis across a curated protein structure dataset reveals global patterns of mutation sensitivity across diverse structural and physicochemical contexts. Notably, these trends align with large-scale public mutation datasets, suggesting that our framework captures features relevant to pathogenic variation. Together, ICed-ENM and the associated mutation-scanning pipeline provide a scalable and mechanistically interpretable strategy to identify mutation-sensitive regions and substitutions, offering deeper insight into how sequence variation reshapes functional conformational landscapes.

biophysics↗

bioRxiv2026

An essential dynamics-based elastic network model to unravel the conformational dynamics of DNA, RNA, and protein-nucleic acid complexes

The flexibility of DNA and RNA is known to play a central role in numerous biological processes, including chromatin organization and gene regulation. While a wide range of computational approaches have been developed to investigate the conformational dynamics and flexibility of proteins, analogous methods for nucleic acids remain comparatively underexplored. Elastic Network Models (ENMs) - coarse-grained mechanical representations in which macromolecules are modeled as networks of nodes connected by elastic springs - have been successfully applied to proteins, often allowing to capture experimentally observed conformational changes through a small number of harmonic normal modes. Building on a previously validated three-bead ENM for RNA, here we introduce edENM, an essential dynamics-refined ENM for DNA, RNA, and protein-nucleic acid complexes, parametrized using a diverse set of Molecular Dynamics simulations. The vibrational modes of the new edENM show good agreement with NMR data and experimental ensembles, while avoiding the unrealistic and localized deformability of previous ENM parametrizations. Additionally, we integrated this new edENM into eBDIMS, a Brownian Dynamics-based framework that enables the simulation of large-scale and anharmonic conformational transitions in protein assemblies. In this way, we are now able to explore functional motions in large protein-nucleic acid complexes such as chromatin subunits and ribosomes.

biophysics↗

bioRxiv2025

Uniaxial tensile tests and Digital Image Correlation analysis for the mechanical characterization of human Fascia Lata under different decellularization treatments

Fascia Lata (FL) is frequently employed as a graft source in reconstructive surgery. To minimize unwanted responses from the host immune system, several decellularization treatments have been proposed. Effective treatments should aim at avoiding the deterioration of the physical and mechanical properties of the implanted tissue. In this work, we carried out a mechanical characterization of FL specimens from human dead donors, both in their native-physiological condition and upon decellularization with three commonly used detergents, t-octyl-phenoxypolyethoxyethanol (Triton X-100), sodium dodecyl sulfate (SDS), and tri-n-butyl phosphate (TnBP). Uniaxial tensile tests were used to characterize the elastic stiffness and ultimate stresses of the tissue, and Digital Image Correlation (DIC) was applied to monitor the strain evolutions and meso-mechanical deformation responses. None of the investigated decellularization protocols was found to lead to a significant deterioration of the FL mechanical properties, suggesting the applicability of these chemical treatments for graft preparation and usage in the clinical practice. The application of DIC also allowed us to get a first estimate of the FL Poisson ratio as well as to draw the attention on the inhomogeneity of strain distributions, suggesting that the use of average engineering strains can lead to an oversimplification of the actual deformation field.

bioengineering↗