Supramolecular Biomaterials: Data-Driven Design of Function

Biological systems achieve sophisticated functions through dynamic networks of weak, reversible, and highly selective interactions. Translating these principles into synthetic, hybrid, and bioengineered systems can create new opportunities to design supramolecular biomaterials and nanostructures with programmable properties for biomedical, environmental, energy, and sustainability applications.This Research Topic focuses on the data-driven design of function in supramolecular biomaterials, including relevant nanostructures, with particular emphasis on how molecular recognition, reversible interactions, self-assembly, and structural dynamics can be measured, modelled, predicted, and ultimately harnessed to engineer function. We welcome studies that connect molecular-level organisation and dynamics with emergent properties such as responsiveness, adaptability, selective recognition, transport, signalling, adhesion, catalysis, molecular capture, energy transfer, and therapeutic activity.One approach is the integration of experiment, computation, and artificial intelligence in the study of supramolecular biomaterials. Quantitative experimental measurements can generate high-quality datasets that constrain molecular simulations, reveal structure–dynamics–function relationships, and support machine-learning approaches for predicting self-assembly, materials properties, and functional performance. Iterative workflows combining experimental characterisation, molecular modelling, multivariate analysis, and AI can accelerate the discovery and optimisation of supramolecular systems. AI and machine-learning studies should be directly connected to experimental data or validation in a supramolecular biomaterial system; work on AI methods without this connection is outside the scope.The scope includes:• Supramolecular assemblies• Peptide-, lipid-, nucleotide-, carbohydrate-, and protein-based materials• Host–guest systems• Adaptive polymers• Dynamic hydrogels• Nanostructured biomaterials• Biohybrid architectures• Enzyme- or microorganism-integrated systemsApplications may span drug delivery, regenerative medicine, biomaterial–cell interactions, environmental sensing, pollutant capture, air, water, and soil purification, bioremediation, carbon capture, resource recovery, sustainable materials, and biohybrid energy conversion.By bringing together supramolecular chemistry, biomaterials, nanoscience, biotechnology, bioengineering, biophysics, environmental science, computational modelling, and AI, this Research Topic aims to advance the predictive and data-informed engineering of function in dynamic supramolecular materials. Topic editors: Radoslav Z. Pavlovic, Khan Sharun, Nevena Jeremic, Ljubica Tasic, Folorunsho Bright Omage Source: https://www.frontiersin.org/research-topics/86538/supramolecular-biomaterials-data-driven-design-of-function