1 research outputs found
Roughness of Molecular Property Landscapes and Its Impact on Modellability
In molecular discovery and drug design, structure–property
relationships and activity landscapes are often qualitatively or quantitatively
analyzed to guide the navigation of chemical space. The roughness
(or smoothness) of these molecular property landscapes is one of their
most studied geometric attributes, as it can characterize the presence
of activity cliffs, with rougher landscapes generally expected to
pose tougher optimization challenges. Here, we introduce a general,
quantitative measure for describing the roughness of molecular property
landscapes. The proposed roughness index (ROGI) is loosely inspired
by the concept of fractal dimension and strongly correlates with the
out-of-sample error achieved by machine learning models on numerous
regression tasks