Biology subjects

Mezzasalma, S. A.

Publications and source records attributed to Mezzasalma, S. A..

3 recordsLinked to original sources

bioRxiv2025

Functional Group Composition: The Blueprint for Protein Interactions

Understanding the complex landscape of protein interactions, especially those involving intrinsically disordered proteins (IDPs), is fundamental yet challenging due to their structural heterogeneity and flexibility. Traditional sequence-based homology methods frequently fall short in characterizing IDP functions and interactions. Here, we present a novel approach leveraging supervised and unsupervised machine learning techniques, focusing exclusively on the compositional features of proteins. An Edmond-Ogston-inspired mixing model can reliably predict the degree of survivin (BIRC5) binding as a function of peptide composition alone, revealing a first interesting connection with the composition diagrams of chemical thermodynamics. By representing protein sequences through their functional group compositions, we demonstrate that specific compositions robustly predict binding interactions with survivin, an important human protein in cellular regulation pathways. Experimental validation via peptide microarray confirms the predictive power of our simplified compositional model, independent of exact amino acid sequences. Extending this method across the human proteome, we identified distinct compositional signatures correlating with survivin interactions and revealed fine grained biologically meaningful functional clusters based on compositional similarity. Our findings suggest a compositional blueprint underpinning protein interactions, offering a powerful, simplified framework to decode complex biological networks.

systems biology↗

bioRxiv2024

Femtosecond X-ray snapshots reveal correlated displacements of specific distal atoms in a protein crystal

Protein dynamics is shaped by interactions between thermal fluctuations, external forces, and molecular structures. Thermal fluctuations have high frequencies and are hence very challenging to quantify. We were able to record femtosecond X-ray diffraction snapshots and determine atomic displacements of crystalline bovine trypsin atoms either in the native steady state or in a transient state initiated by a short THz pulse, the results of which were interpreted with numerical simulations. In the absence of THz pulses, specific distal atoms exhibited correlated movements. Under the influence of THz fields, numerical simulations demonstrated a slight enhancement of displacement correlations. The experimental results revealed a contrasting response to short THz pulses, where the measured displacements were not solely determined by the atom position, but also influenced by the atomic type. These findings call for a reinterpretation of the dynamic properties inherent in folded protein structures and the physical principles behind the formation of protein assemblies. To this end, a theoretical model was developed for lattice deformations and local excitations entraining a (squeezed) coherent steady state, explaining the emergence of atom correlations. The model accounts for the magnitudes of atomic displacements and fluctuations through a balance between harmonic and anharmonic coupling forces.

biophysics↗

bioRxiv2024

Deciphering Peptide-Protein Interactions via Composition-Based Prediction: A Case Study with Survivin/BIRC5

In the realm of atomic physics and chemistry, composition emerges as the most powerful means of describing matter. Mendeleevs periodic table and chemical formulas, while not entirely free from ambiguities, provide robust approximations for comprehending the properties of atoms, chemicals, and their collective behaviours, which stem from the dynamic interplay of their constituents. Our study illustrates that protein-protein interactions follow a similar paradigm, wherein the composition of peptides plays a pivotal role in predicting their interactions with the protein survivin, using an elegantly simple model. An analysis of these predictions within the context of the human proteome not only illuminates the known cellular locations of survivin and its interaction partners, but also introduces novel insights into biological functionality. It becomes evident that an electrostatic- and primary structure-based descriptions fall short in predictive power, leading us to speculate that protein interactions are orchestrated by the collective dynamics of functional groups.

bioinformatics↗