Human readability and, consequently, interpretability is often considered a key advantage of grammatical descriptors. Beyond the natural language, this is also true in analyzing biological sequences of RNA, typically modeled by grammars of at least context-free level of expressiveness. However, in protein sequence analysis, the explanatory power of grammatical descriptors beyond regular has never been thoroughly assessed. Since the biological meaning of a protein molecule is directly related to its spatial structure, it is justified to expect that the parse tree of a protein sequence reflects the spatial structure of the protein. In this piece of research, we propose and assess quantitative measures for comparing topology of the parse tree of a context-free grammar with topology of the protein structure succinctly represented by a contact map. Our results are potentially interesting beyond its bioinformatic context wherever a reference matrix of dependencies between sequence constituents is available.