Measuring Molecular Complexity Opens Up New Avenues for Drug Discovery

Spectroscopic techniques can be used to measure molecular complexity, according to a recent study published in ACS Central Science (1).

The study, led by Professor Leroy Cronin of the University of Glasgow, examined using spectroscopy techniques including nuclear magnetic resonance (NMR), tandem mass spectrometry (MS/MS), and infrared (IR) spectroscopy to measure molecular complexity. Traditional methods in evaluating molecular complexity largely rely on algorithmic complexity, which is a concept normally seen in computer science applications (1). However, algorithmic complexity does not work in molecular analysis because it cannot be directly measured through experiments (1). As a result, the research team explored using a technique with assembly theory as the framework for their method.

Nucleotide in flat design side view molecular biology. Generated with AI. | Image Credit: © chayantorn - stock.adobe.com

Assembly theory is a theoretical framework that has not only been used in computer science, but also in physics and biological analysis (2). In this study, Cronin’s team used assembly theory to describe a framework in which they could quantify the complexity of a molecule by determining the shortest path required to construct it from basic building blocks (1). This measure, known as the molecular assembly index (MA), offered a quantifiable and experimentally verifiable metric of molecular complexity (1).

Cronin and his team relied on three independent spectroscopic techniques, including NMR, MS/MS, and IR spectroscopy, to experimentally measure the MA (1). By identifying and analyzing the number of absorbances in IR spectra, carbon resonances in NMR, or molecular fragments in tandem MS, they could reliably estimate the MA of an unknown molecule (1).

The research has potential positive ramifications for drug discovery applications. Because drug discovery approaches are currently expensive and involve a significant amount of trial and error, researchers are interested in exploring new ways to improve these processes. Cronin's method allows for the rapid assessment of a molecule's complexity, which is crucial for identifying promising drug candidates early in the development process (1). This could lead to more efficient drug discovery, reducing both time and costs associated with bringing new drugs to market.

The ability to measure molecular complexity also offers profound insights into the origins of life, which is another avenue Cronin and his team explored in the study. Understanding how complex molecules form and evolve is fundamental to the study of abiogenesis, which is defined as the process by which life arises naturally from non-living matter (1). Through assembly theory, scientists can explore the evolution of complex molecules (1).

Understanding molecular complexity can also open routes for the creation of synthetic life forms. By manipulating the MA of molecules, researchers can direct the assembly of complex molecules, potentially leading to the creation of entirely new forms of artificial life (1).

By developing a method to experimentally measure molecular complexity, Cronin and his team introduced new research in drug discovery, the origins of life, and artificial life. The ability to quantify the complexity of molecules through assembly theory represents a step forward, providing a tool for scientists to explore and understand the intricate world of molecular structures (1).

References

(1) Jirasek, M.; Sharma, A.; Bame, J. R.; et al. Investigating and Quantifying Molecular Complexity Using Assembly Theory and Spectroscopy. ACS Cent. Sci. 2024, 10 (5), 1054–1064. DOI: 10.1021/acscentsci.4c00120

(2) Sharma, A.; Czegel, D.; Lachmann, M.; et al. Assembly Theory Explains and Quantifies Selection and Evolution. Nature 2023, 622, 321–328. DOI: 10.1038/s41586-023-06600-9