Our results show that, indeed, a model's learned representations can be leveraged to reverse-engineer new MOF structures, consolidating the tasks of structure optimisation and property prediction within a single unified framework. This approach provides valuable insights into the MOF structure-property relationship at an early stage, paving the way for more refined optimisation techniques and further investigative efforts in MOF research.