Reaction Tracking and High-Throughput Screening of Active Compounds in Combinatorial Chemistry by Tandem Mass Spectrometry Molecular Networking

Combinatorial synthesis has been widely used as an efficient strategy to screen for active compounds. Mass spectrometry is the method of choice in the identification of hits resulting from high-throughput screenings due to its high sensitivity, specificity, and speed. However, manual data processing of mass spectrometry data, especially for structurally diverse products in combinatorial chemistry, is extremely time-consuming and one of the bottlenecks in this process. In this study, we demonstrated the effectiveness of a tandem mass spectrometry molecular networking-based strategy for product identification, reaction dynamics monitoring, and active compound targeting in combinatorial synthesis. Molecular networking connects compounds with similar tandem mass spectra into a cluster and has been widely used in natural products analysis. We show that both the expected and side products can be readily characterized using molecular networking based on their mass spectrometry fragmentation patterns. Additionally, time-dependent molecular networking was integrated to track reaction dynamics to determine the optimal reaction time to maximize target product yields. We also present a proof-of-concept experiment that successfully identified and isolated active molecules from a dynamic combinatorial library. These results demonstrated the potential of using molecular networking for identifying, tracking, and high-throughput screening of active compounds in combinatorial synthesis.

Automated summary

In this study, a tandem mass spectrometry molecular networking-based strategy was demonstrated to be effective for product identification, reaction dynamics monitoring, and active compound targeting in combinatorial synthesis. Both expected and side products can be characterized using molecular networking based on their mass spectrometry fragmentation patterns. Time-dependent molecular networking was also integrated to track reaction dynamics for optimizing target product yields in high-throughput screening of active compounds.