  Nanomaterials possess a wide range of potential applications due to their
novel properties compared to bulk matter, but these same properties may
represent an unknown risk to health. Experimental safety testing cannot keep
pace with the rate at which new nanoparticles are developed and, being lengthy
and expensive, often hinders the development of technology. An economic
alternative to in vitro and in vivo testing is offered by nanoinformatics,
potentially enabling the quantitative relation of the nanomaterial properties
to their crucial biological activities. Recent research efforts have
demonstrated that such activities can be successfully predicted from the
physicochemical characteristics of nanoparticles, especially those related to
the bionano interface, by means of statistical models. In this work, as a step
towards in silico prediction of toxicity of nanomaterials, an advanced
computational characterization of these materials has been proposed and applied
to titanium dioxide nanoparticles. The characteristics of nanoparticles and
bionano interface are computed using a systematic multiscale approach relying
only on information on chemistry and structure of the nanoparticles.
