Development of an insilico model of eccrine sweat using molecular modelling techniques

P Deshpande and B Ravikumar and S Tallur and D Paul and B Rai, SCIENTIFIC REPORTS, 12, 20263 (2022).

DOI: 10.1038/s41598-022-24440-x

Eccrine sweat is an ideal surrogate diagnostic biofluid for physiological and metabolic biomarkers for wearable biosensor design. Its periodic and non-invasive availability for candidate analytes such as glucose and cortisol along with limited correlation with blood plasma is of significant research interest. An insilico model of eccrine sweat can assist in the development of such wearable biosensors. In this regard, molecular modelling can be employed to observe the most fundamental interactions. Here, we determine a suitable molecular model for building eccrine sweat. The basic components of sweat are water and sodium chloride, in which glucose and other analytes are present in trace quantities. Given the wide range of water models available in the molecular dynamics space, in this study, we first validate the water models. We use three compounds to represent the base to build bulk sweat fluid and validate the force fields. We compare the self-diffusivity of water, glucose, sodium, and chloride ions as well as bulk viscosity values and present the results which are > 90% accurate as compared with the available literature. This validated insilico eccrine sweat model can serve as an aid to expedite the development de novo biosensors by addition of other analytes of interest e.g. cortisol, uric acid etc., simulate various temperatures and salt concentrations, expand search space for screening candidate target receptors by their binding affinity and assess the interference between competing species via simulations.

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