In 2018, our group was awarded a prestigious “ERC Starting Grant” worth € 1.5 million. The project began in July 2019 and has a duration of 5 years. Please follow this link for accompanying press release.
Over the past two decades, a branch of organic chemistry has emerged that breaks with the paradigm of synthesizing pure compounds and focusses instead on complex (macro)molecular networks akin to those found in nature. In this proposed project, we aim to address unmet challenges in supramolecular chemistry and systems chemistry by developing original dynamic reaction networks whose building blocks are capable of supramolecular (self-)recognition.
The first two objectives of SUPRANET focus on the use of dynamic covalent orthoester networks for the discovery of anion, cation and ion pair receptors, whose unique properties may pave the way towards the utilization of inorganic ions as drugs. For instance, we will develop self-assembled ion pair cages for the electro-neutral transport of medicinally relevant anions across phospholipid membranes. Our network approach will also allow us to “imprison” ionic guests for the first time in self-assembled receptors that could be used for the transport and controlled release of ions, even against osmotic pressure.
Objectives three and four of SUPRANET go beyond the equilibrium state and, as such, are relevant to the chemistry of life, in which key processes depend on dissipative steady states. The proposed reaction networks will feature biologically relevant ribose building blocks that are continuously assembled and disassembled by two different irreversible reactions, resulting in steady state mixtures of either RNA oligomers or ribose-derived vesicles. It is our hope that these studies will provide insights into open questions regarding the molecular origins of life, such as the non-enzymatic formation of RNA oligomers capable of self-recognition and the simultaneous emergence of compartmentalization and self-replication.
SUPRANET thus seeks to break new ground in both equilibrium and far-from-equilibrium dynamic networks and is equally motivated by applied and fundamental challenges.