  The efficient exploration of chemical space to design molecules with intended
properties enables the accelerated discovery of drugs, materials, and
catalysts, and is one of the most important outstanding challenges in
chemistry. Encouraged by the recent surge in computer power and artificial
intelligence development, many algorithms have been developed to tackle this
problem. However, despite the emergence of many new approaches in recent years,
comparatively little progress has been made in developing realistic benchmarks
that reflect the complexity of molecular design for real-world applications. In
this work, we develop a set of practical benchmark tasks relying on physical
simulation of molecular systems mimicking real-life molecular design problems
for materials, drugs, and chemical reactions. Additionally, we demonstrate the
utility and ease of use of our new benchmark set by demonstrating how to
compare the performance of several well-established families of algorithms.
Surprisingly, we find that model performance can strongly depend on the
benchmark domain. We believe that our benchmark suite will help move the field
towards more realistic molecular design benchmarks, and move the development of
inverse molecular design algorithms closer to designing molecules that solve
existing problems in both academia and industry alike.
