The third direction of the proposed research program concerns the study of biomolecular systems with important applications in biotechnology, which nowadays is a very active and intense research field. In the SimEA project we plan to work on:

  • Bio-based films and surfaces: The development of protein-based films and coatings with the desired properties can have strong technological impact within the circular economy era. For example, such films could be used to replace existing synthetic oxygen barrier polymers and increase the recyclability of packaging products. Thus, the study of functionalized biodegradable monolayer films with different functional (barrier, mechanical, optical, etc.) and active properties at the molecular level is a very exciting but also challenging research field.

The prediction of structure-property relations of bio-based complex materials is directly connected to their study at the molecular level. In this aspect, a synergy of multi-scale simulation techniques and AI technologies could be an important factor for the design of functional bio-based materials. Our main goal is to pursue such a fundamental (molecular-level) understanding of structure-processing-functionalization-property relationships in bio-based materials via large-scale simulation methodologies and machine learning methods. 

We will apply molecular simulation tools such as molecular dynamics (MD) and Monte Carlo (MC) to get a microscopic understanding of structural, conformational and dynamical properties of biomolecules (peptides, proteins, carbohydrates, lipids) in different environments, substrates and conditions. We aim to use these results in order to provide: (a) a detailed characterisation of functionalized bio-based interfaces for targeted applications, and (b) a molecular understanding of properties of bio-based thin films to guide their design.

  • Abiotic-biotic interactions of bio-derived surfaces and their environment: Furthermore, we plan to use the above-described methodology for the development of materials with anti-bacterial properties. For this, we will study interactions, at the molecular level, between nanostructured materials (inorganic and bio-based) and peptides, and quantify the strength of binding of peptides to specific minerals/ materials. Our goal is the identification of the structural features in the peptides and of surface chemistry on biomolecule binding that lead to enhanced antibacterial behaviour, and in the long-term, to develop rules to predict binding behaviour for different materials.

Due to the high complexity of the effect of surface chemistry and topology on biomolecule binding we propose: (a) many large-scale simulations of specific systems, and (b) Data analytics approaches for analysing simulation and experimental data. Molecular simulations will be used in both atomic-resolution and simplified coarse-grained (CG) representations to study the influence of amino acid sequence and functionality on the binding process of the peptides of interest onto selected surfaces.

Examples of expected results from the above methodology include: 1) Molecular-level understanding of the effect of important environmental parameters (solvent, temperature, pH) and structural factors (composition, chain length, backbone flexibility, etc.) on peptide or protein self-organization, microstructure, adhesion, packing on substrate, and antimicrobial activity; 2) Better understanding of cooperative effects during binding (such as configurational re-arrangements followed by strong adsorption on the substrate), and of the equilibrium state after binding; 3) Based on the above, alongside peptide conformation data, propose design rules for optimized coating-substrate interactions, possessing the desired antimicrobial activity for specific applications.

  • Nanocomposites of biomolecules and nanoparticles (NPs): We also plan to extend the above methods to examine interactions of biomolecules with inorganic nanoparticles. Our goal is to provide quantitative information for the structure of organic molecules and proteins through multi-scale dynamic simulation approaches, involving detailed all-atom models and proper coarse-graining strategies (as described in Theme 2).

We will predict structure, conformations, and dynamics of biopolymers/NPs model systems, such as PLA/silica, as a function of polymer/NP interaction, temperature, concentration etc. In addition, the above computational scheme will allow us to:  1) Perform large-scale all-atom MD simulations to study proteins/nanoparticles interface at atomistic scale, 2) Develop effective potentials for complex protein structures for use in coarse-grained (CG) simulations of these systems, to get simulation predictions for the relevant properties in a more efficient manner, and 3) Provide quantitative predictions about microstructure and dynamics of biomolecules interacting with nanoparticles.