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

Abstract

In the realm of atomic physics and chemistry, composition emerges as the most powerful means of describing matter. Mendeleev’s 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 description falls short in predictive power, leading us to speculate that protein interactions are orchestrated by the collective dynamics of the functional groups of the peptides involved.

Survivin in Synergy With Baf/Swi Complex Binds Bivalent Chromatin Regions and Activates Dna Damage Response in Cd4+ T Cells

“…To investigate in detail the interaction between survivin and the BAF complex, we applied the compositional analysis of proteins comprising the conventional (c)BAF and polybromo(P)BAF complexes aiming to predict their interaction with survivin. For this purpose, we utilized the peptide model based on the functional group composition of each protein of the complex (Jensen et al, 2023; Anindya et al, 2024). We identified that SMARCD1, SMARCA2, SMARCA4, SMARCC1, and BRD7 exhibit comparable ratios between the predicted binding peptides to the total number of generated peptides (R bind ) values in the range of 0.39-0.43.…”

“…Based on the functional composition of the protein, defined by the presence of atomic groups (C, CH, CH 2 , CH 3 , hydroxyl, phenyl, carboxyl, amide, sulfhydryl, etc.) rather than the sequence of amino acids, we develop a strategy for predicting fitness of a given protein/peptide to survivin in biological and a chemical context (Jensen et al, 2023; Anindya et al, 2024) with the following adjustments. The multilayer perceptron classifier comprised two intermediate layer neurons, and C-Pos encoding was employed to interpret 15 amino acid-long peptides.…”

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

“…Concerning the biological function of these groups, there has been speculation about which properties of peptides are crucial in determining their interaction with promiscuous proteins such as survivin. In this example, it appears that the sequence does not provide substantially more deterministic power compared to composition 62,63 . However, for an effective model, the composition must include a detailed description of functional groups in the amino acids, rather than simply considering the number of hydrophobic and hydrophilic amino acids, net charge, and charge density.…”