Using data-driven methodologies and machine learning, researchers have made a groundbreaking discovery in the field of molecular design. They have found that there is a “freedom of design” in molecular structures due to weak correlations in quantum-mechanical properties. This finding has the potential to revolutionize drug discovery and open up new possibilities in the field.
In the past, researchers have focused on exploring the relationships between the structural signatures of molecules and their physicochemical properties. While there has been progress in this area, there was still a lack of comprehensive understanding. However, the recent discovery of weak correlations in quantum-mechanical properties suggests that there is a flexibility or “freedom of design” in chemical compound space (CCS). This means that molecules can simultaneously exhibit any pair of properties or share an array of properties.
To explore the implications of this discovery, the researchers used Pareto multi-property optimization to search for molecules with specific properties. They found that there are paths through chemical space consisting of unexpected molecules connected by structural or compositional changes. This reflects the flexibility in the design and discovery of molecules with targeted property values.
The researchers suggest that combining their insights with advanced machine learning approaches could lead to the development of effective strategies for high-throughput screening of novel molecules. This new approach could greatly improve the drug discovery process and open up new avenues for the design of molecules with specific properties.
Overall, this research has important implications for the fields of rational molecular design and computational drug discovery. It challenges the current paradigm and offers new possibilities for designing molecules with targeted properties. With further advancements in machine learning, the future of drug discovery looks promising.
– “Freedom of design’ in chemical compound space: towards rational in silico design of molecules with targeted quantum-mechanical properties” – Leonardo Medrano Sandonas, Johannes Hoja, Brian G. Ernst, Álvaro Vázquez-Mayagoitia, Robert A. DiStasio, Jr and Alexandre Tkatchenko, Chemical Science, 18 August 2023.