The objective of this exploratory workshop is to develop collaborative proposals between molecular simulators, bio-informaticians, food scientists and industry, with a focus on questions where nanoscale mechanisms play important roles. This entails combining bio-informatics/machine learning, biased free energy sampling methods and mesoscale methods, with biological/food science insight. A diverse set of topics will be considered:
- Bioactive/drug discovery (examples to include development of agonist milk based peptides ligands for type 2 diabetes)
- Taste perception (examples to include development of food structures and encapsulation systems to alter taste perception, taste masking agents, etc)
- Milk drying, re-hydration, protein denaturation and solubility, and the role of salt/pH (example application infant milk formula)
While the above applications are very different, the computational methods that they demand are similar, and can only realistically be broached using a combined perspective. For instance, molecular simulation while immensely powerful at a nano-level, requires for these sorts of complex biological problems a good initial condition, which can be provided by bio-informatics. Bio-informatics can search vast libraries of structures using machine learning based approaches (and databases built on experimental scattering data), but has difficulty in describing precise nano-scale mechanisms, free energy properties, and dynamical effects. Food science can say a lot on macroscopic scales, but has difficulty going below sub-micron scales, where important biological features take place, not to mention at the nano-scale relevant to small molecules (drugs/ flavours /perfumes/etc ), de-naturation of proteins etc. These sort of questions are important to the food and health industry, as the 3 topics above illustrate.