  Shape-similarity between molecules is a tool used by chemists for virtual
screening, with the goal of reducing the cost and duration of drug discovery
campaigns. This paper reports an entirely novel shape descriptor as an
alternative to the previously described RGMolSA descriptors
\cite{cole2022riemannian}, derived from the theory of Riemannian geometry and
K\"ahler quantization (KQMolSA). The treatment of a molecule as a series of
intersecting spheres allows us to obtain the explicit \textit{Riemannian
metric} which captures the geometry of the surface, which can in turn be used
to calculate a Hermitian matrix $\mathbb{M}$ as a directly comparable surface
representation. The potential utility of this method is demonstrated using a
series of PDE5 inhibitors considered to have similar shape. The method shows
promise in its capability to handle different conformers, and compares well to
existing shape similarity methods. The code and data used to produce the
results are available at: \url{https://github.com/RPirie96/KQMolSA}.
