Complex networks are powerful mechanisms one can use to model real-world networks as topological spaces. The beauty of these structures is provided by the infinite degree of analysis one is allowed to do using them. Biologically it is almost impossible for the human mind to comprehend the behaviour of these systems, but when modelled as complex networks different properties of the network topology can reveal precious information. Starting from the two key properties of the participants n a complex network and the relations between them, one can derive further properties that reflect specific behaviours for entities or groups of entities. Examples of these further remarkable properties include entities which create unique bridges between two or more communities (known as Articulation Points) or the appearance of patterns of interconnections between entities (known as Network Motifs). Our paper performs a study on the co-existence of these two properties, Articulation Points and Network Motifs, and how their appearance is correlated, by using results obtained in analysing a variety of real-world networks.