Scientists have recently developed a new method for exploring chemical space that could immensely help in drug design and drug discovery. This new method is based on assembly theory that permits scientists to transform molecules into molecular trees, which is similar to forming a family tree that helps identify the parents and offspring. This technique has been validated both experimentally and computationally.
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Put simply, assembly theory is used to investigate chemical space, or in other words, this method provides evolutionary information from the structure. The term chemical space is used to refer to a vast pool of potential combinations of chemical molecules. Every chemical has a specific position in chemical space. Scientists explained that chemical space comprises every possible compound, i.e., all known drugs and materials as well as unknown molecules that could be discovered in the future. Thereby, chemical space constitutes an infinite number of molecules.
As many of the chemicals could be unstable or synthetically inaccessible, it is essential to investigate thoroughly before determining novel biologically functional molecules and this process could be an extremely vast and challenging task. Scientists are optimistic that the new method based on assembly theory could help researchers to expedite the process of effective drug discovery significantly.
What is Assembly Theory?
In the past, many studies have explained the concept of molecular complexity theoretically, and many of the metrics have been based on topographical, structural, or graph theoretical complexity. All these metrics have varied algorithms. The newly developed assembly theory deals with describing molecular complexity. This method provides possibilities for creating compounds with favorable properties in a minimum number of steps based on evolution.
According to Lee Cronin from the University of Glasgow, who was associated with developing this theory, this theory could be used to follow the molecular evolution of natural compounds which are effective drugs. This theory predicts how a particular product will evolve rather than going one step at a time, by means of a trial-and-error method.
The most important feature of assembly theory is that it has the ability to break molecules down into their constituent parts, and also assist in finding novel ways to combine these molecules with others bearing similar parts. Scientists have compared this process with breaking words down into letters and then shuffling them to form new words. This approach offers chemists a more structured strategy to discover new molecules which could be otherwise extremely time-consuming.
Scientists revealed that although constructing an assembly tree to analyze molecular complexity is a promising approach, the molecular tree for bigger molecules could be a complex mathematical problem. To overcome this problem, they developed a Monte Carlo algorithm that provides the shortest, non-trivial pathways of assembly for given molecules.
Researchers are able to develop assembly graphs by investigating these pathways, which are associated with families of molecules, and these aid in exploring the chemical space.
Assembly Theory and Drug Discovery
A team of researchers has used the assembly theory to investigate a class of drugs known as opiates. Previous studies have indicated that this drug is a powerful addictive painkiller and could be deadly if misused. Assembly theory has helped researchers to develop new forms of opiates that possess the same efficacy as the original pain medicine used for treating pain but are potentially less harmful. This drug could provide doctors with a new approach for treating patients.
Using the assembly tree method scientists generated 1000 opiate-like compounds and 1000 random compounds that comprise bonds similar to opiates. Interestingly, they observed that the molecules obtained from the assembly pools possessed higher similarities with opiates compared to random compounds. The compound developed using the molecules obtained from the assembly tree exhibited similar levels of drug-likeness to opiates.
After running the assembly theory algorithm on the computer, researchers were able to group nine natural and synthetic opiates. This method primarily broke the molecules into smaller parts which are known as assembly pools and, subsequently, studied various combinations of the pools until they found a route that could construct all opiates in the group. These opiate assembly tree routes enabled researchers to discover new opiates.
This was possible by marginally modifying some parts, that were found to be common in all the opiate tree routes, in a manner such that the overall shape of the molecule remains the same but with a minor architectural difference. This method helped researchers to discover new potential drugs by restoring some of the key features to keep the drug active. In the future, this method could help the development of a new type of painkillers that would be less addictive and equally effective.
Professor Cronin explained the chemical space in a very interesting way. He said that the chemical space is incredibly vast, where many potential drugs remained to be explored, similar to stars in the universe.
Assembly theory has provided researchers with a navigating tool to study compounds in chemical space. This process includes breaking down the drug compound into its constituent parts, elucidating how they were created, and studying how these components could be combined to form new compounds. Scientists are optimistic that assembly theory will help improve drug design and discovery, significantly.
- Assembly theory could spell good news for drug discovery. University of Glasgow. (2021) [Online] Available at: https://www.gla.ac.uk/news/headline_812517_en.html
- Welter, K. (2021) Exploiting evolution to explore chemical space shows promise for drug discovery. [Online] Available at: https://www.chemistryworld.com/news/exploiting-evolution-to-explore-chemical-space-shows-promise-for-drug-discovery/4014561.article
- Liu, Y. et al. (2021) Exploring and mapping chemical space with molecular assembly trees. Science Advances. 7(39). DOI: 10.1126/sciadv.abj2465