DELT occupies an outstanding position in modern early drug discovery toolkit, being both rapid and relatively inexpensive group of methods that allows generating big chemical spaces of druglike compounds. It is noteworthy, that actual size of the libraries generated using DELT sometimes exceed size of the combinatorial libraries generated by traditional HTS approaches by several orders of magnitude, which is a significant advantage of DELT. The increased size of such libraries brings to the front line the factor of availability of sufficient numbers of eligible monofunctional building blocks (also common as modifiers, or capping agents). Therefore, a discussion on the properties, requirements, and diversity of capping agents that are currently available, and may be used for the construction of DNA-encoded libraries is on point. Currently, the landscape of the market of these most widespread molecules in the world stock is determined by the demands of HTS. Despite the dominating opinion that most of the existing molecules designed for HTS could be used for DELT, there are criteria that significantly limit the number of DELT-compatible blocks. Ability to react in aqueous, non-acidic medium, at temperatures below 90oC with high conversion and selectivity is the main hallmark for the DEL-compatible capping agents. In this study, we will discuss broad spectrum of applicability criteria for the available pool of building blocks, in terms of “DELT incompatibility” and “likely DELT compatibility”, using E-molecules, and Chemspace databases and Enamine database as case study.
In the current work, we will discuss our in house chemoinformatical filters that allow extracting “likely DELT compatible” building blocks from the general pool, using criteria that account molecular weight, substituents compatibility, Fsp3, possible reactivity, water solubility, and chirality. We will disclose the statistical data on the content of the “likely DELT compatible” molecules comparing to the overall array of stock building blocks in the given dataset and discuss the classification of the selected compounds.
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