**5. Conclusions**

Chromatin structural biology is an equally important as demanding field. This is not only clear from the tremendous efforts necessary for the first nucleosome structure but also from the limited number of structures for nucleosome-protein complexes. While crystallography and cryo-EM resulted in various high-resolution structures, not every interaction is accessible this way due to either of many experimental limitations, such as the need for crystallization, the fleeting nature of some complexes or the pervasive role of highly dynamic protein regions. Here, an increasing number of studies shift towards a combined approach utilizing various sources of interaction data to direct sophisticated data-driven docking. This way all knowledge on a nucleosome-interacting system can be integrated into a structural model that is otherwise inaccessible. These models strongly depend on the quality and quantity of data and contain an inherent ambiguity. However, as in the case of linker histone H1, structural models can point to alternative binding modes and thus result in new, testable hypotheses. Additionally, crucial residues for nucleosome binding can be identified, allowing design of, for example, loss of function or loss of binding mutants to silence specific pathways. It also offers the possibility to drive the design of competing small molecule or peptide structures as potential candidates for epigenetic drugs interfering with specific effector binding. Remarkably, these developments might be otherwise lost due to the lack of a structure. However, as for now, a database for such structural models, akin to the RCSB protein databank, remains to be established. This might however be essential to advance the study of chromatin effector proteins. Publicly available structures including their data-based restraints could be used for further refinements upon availability of new, additional datasets from an array of techniques. It also would offer the possibility of negative results, otherwise rarely reported, to contribute to drive or score the quality of already reported models. Datadriven modeling of nucleosome-protein complexes has the potential to yield unique fundamental insights into nucleosome-binding dynamics and enable advances in modulation of chromatin effector proteins, which would be otherwise inaccessible.

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