Scoring, the process of selecting the biologically relevant solution from a pool 
of generated conformations, is one of the major challenges in the field of 
biomolecular docking. A prominent way to cope with this challenge is to 
incorporate information-based terms into the scoring function. Within this 
context, low-resolution shape data obtained from either ion-mobility mass 
spectrometry (IM-MS) or SAXS experiments have been integrated into the 
conventional scoring function of the information-driven docking program HADDOCK. 
Here, the strengths and weaknesses of IM-MS-based and SAXS-based scoring, either 
in isolation or in combination with the HADDOCK score, are systematically 
assessed. The results of an analysis of a large docking decoy set composed of 
dimers generated by running HADDOCK in ab initio mode reveal that the content of 
the IM-MS data is of too low resolution for selecting correct models, while 
scoring with SAXS data leads to a significant improvement in performance. 
However, the effectiveness of SAXS scoring depends on the shape and the 
arrangement of the complex, with prolate and oblate systems showing the best 
performance. It is observed that the highest accuracy is achieved when SAXS 
scoring is combined with the energy-based HADDOCK score.