In recent decades nanoparticles have proved useful for a variety of applications in biology, biotechnology, medicine; including drug delivery. In most cases it is the combination of high surface capacity and tunable biocompatibility that motivates research, but understanding and predicting surface properties and interactions reliably, and with the required sensitivity, remains challenging to those in the field. Much the same as macromolecules, these interactions are selective, and based on subtle (sometimes weak) interactions that depend on the position on the surface. Not all surface atomic sites on the surfaces of nanoparticles are the same, and so the properties as a whole depend on the size shape and structure. This results in a complex configuration space that cannot be represented by a single model structure. Even though inorganic nanoparticles are traditionally modeled using methods established in solid state physics, these concepts are not uncommon to those working in computational biophysics, and there are many lessons to be drawn and applied. In this talk we will briefly examine recent work on diamond nanoparticles used for drug delivery. We will see how a simple exploration of the surface electrostatic potential lead to new understanding of how nanodiamonds interact with bio markers and drugs, and explained the perplexing and persistent aggregation of colloidal samples. Taking further instruction from biophysics we will also examine the distribution of the deprotonation potential and the proton affinity, which present their own unique computational challenges.