In CASP12, two types of data-assisted protein structure modeling were experimented. Either SAXS experimental data or cross-linking experimental data was provided for a selected number of CASP12 targets, so that the CASP12 predictor can utilize the given data for better protein structure modeling. We devised two separate energy terms for SAXS data and cross-linking data to drive model structures into more native-like structures that satisfy the given experimental data as much as possible. In CASP11, we successfully performed protein structure modeling using simulated sparse and ambiguously-assigned NOE data and/or correct residue-residue contact information, where the only energy term that folded the protein into its native structure was the term which was originated from the given experimental data. However, the two types of experimental data provided in CASP12 was far from being sufficient enough to fold the target protein into its native structure simply because SAXS data provides only the overall shape of the molecule and the cross-linking contact information provides only very low resolution distance information. For this reason, we combined the SAXS or cross-linking energy term with our regular modeling energy function that includes both the template energy term and de novo energy terms. By optimizing the newly formulated energy function, we obtained protein models that fit better with provided SAXS data than the X-ray structure of the target. However, the improvement of the model relative to the one modeled without the SAXS data, was not significant. Consistent structural improvement was achieved by incorporating cross-linking data into protein structure modeling. This article is protected by copyright. All rights reserved.