Our paper “Barcode-free hit discovery from massive libraries enabled by automated small molecule structure annotation” has finally been published in Nature Communications. This first publication from our joint project with Sebastian Pomplun (Leiden University and Oncode Institute) presents a barcode-free self-encoded library (SEL) platform that enables the screening of over half a million small molecules in a single experiment. Kudos to Sebastian Pomplun and his PhD student Edith van der Nol, and of course to all co-authors!
In general, discovering new pharmacologically active molecules that bind to a certain drug target is a tedious process as it requires the screening of very large compound libraries. In contrast to traditional high-throughput methods, affinity selection (AS) represents a powerful approach that allows the rapid screening of millions of molecules in just a single experiment. Here, the compound library is incubated with the receptor of interest, and in a following step, binders are separated from non-binders. This results in a final sample containing ideally only the binders which are called hits.
At this stage of the workflow, we know that this sample represents a subset of our initial screening library, but we do not know which molecules are actually in there. Therefore, the challenge remains in the identification of these hit compounds. This is most commonly done by initially attaching unique DNA barcodes to the molecules of the screening library, which can then be sequenced to identify the isolated hits. However, one of the fundamental drawbacks of these DNA-encoded libraries (DELs) is the potential interference of the attached tag during the affinity selection. This limitation becomes particularly problematic when the target protein has nucleic acid binding sites, making the screening against targets like transcription factors extremely difficult.
Consequently, an approach that does not require any tag while still allowing the simultaneous screening of a vast number of compounds is highly desirable. That is why our proposed screening platform is based on affinity selection-mass spectrometry (AS-MS), which relies solely on MS to identify the selected hit compounds, eliminating the need for any tags. Thus, the name self-encoded libraries (SELs). As our platform also features the use of split-&-pool libraries, containing potentially millions or even billions of combinatorially synthesized molecules, tandem mass spectrometry (MS/MS) has to be utilized as the monoisotopic mass will most likely be insufficient for the identification step. Therefore, we present COMET for analyzing the acquired LC-MS/MS data and enabling the identification of the isolated hit compounds.