Researchers have developed a novel computational method that allows them to explore and design molecules with targeted quantum-mechanical properties. The method, called “freedom of design” principle, could have important implications for the fields of chemistry, biology and materials science.
What is the “freedom of design” principle?
The “freedom of design” principle is based on the idea that most of the quantum-mechanical properties of small molecules are only weakly correlated, meaning that there are very few limitations preventing a molecule from simultaneously exhibiting any pair of properties or for many molecules sharing an array of properties. This implies that there is a high degree of flexibility and diversity in the chemical compound space (CCS), which is the unfathomably vast space populated by all possible atomic compositions and their geometries.
The researchers, from the University of Luxembourg, Cornell University and the Argonne National Laboratory, introduced this principle in a paper published in the journal Chemical Science. They used data-driven approaches to analyse the relationships between the structural signatures of molecules and their physicochemical properties, such as molecular polarisability, electronic gap, dipole moment, ionisation potential and electron affinity.
How does the method work?
The researchers used Pareto multi-property optimisation to search for molecules with simultaneously large molecular polarisability and electronic gap, a design task of relevance for identifying novel molecules for polymeric batteries. They found paths through chemical space consisting of several unexpected molecules connected by structural and/or compositional changes, reflecting the freedom in the rational design and discovery of molecules with targeted property values.
The method also allows for the identification of molecular descriptors that are most relevant for predicting and controlling certain properties. For example, the researchers found that molecular polarisability is mainly determined by the number of valence electrons and the molecular volume, while electronic gap is mainly influenced by the electronegativity difference between atoms and the bond order.
What are the applications and implications of the method?
The method could enable the computational design of molecules with desired properties for various applications, such as drug discovery, catalysis, energy storage and conversion, nanotechnology and biotechnology. The method could also help to understand the fundamental principles governing the structure-property relationships in CCS and to discover new phenomena and materials.
The researchers hope that their work will inspire further developments in the field of computational chemistry and molecular modelling, as well as fruitful collaborations across different disciplines. They also plan to extend their method to larger and more complex systems, such as biomolecules, polymers and crystals.
