  In computational chemistry, accurately predicting molecular configurations
that exhibit specific properties remains a critical challenge. Its intricacies
become especially evident in the study of molecular aggregates, where the
light-induced functionality is tied to highly structure-dependent electronic
couplings between molecules. Here, we present an efficient strategy for the
targeted screening of the structural space employing a "functionality
optimization" technique, in which a chosen descriptor, constrained by the
ground state energy expression, is optimized. The chosen algorithmic
differentiation (AD) framework allows to automatically obtain gradients without
its tedious implementation. We demonstrate the effectiveness of the approach by
identifying Perylene Bisiimide (PBI) dimer motifs with enhanced SF rate. Our
findings reveal that certain structural modifications of the PBI monomer, such
as helical twisting and bending, as well as slipped-rotated packing
arrangements, can significantly increase the SF rate.
