PROTACs bearing piperazine-containing linkers: what effect on their protonation state?. Issue 34 (9th August 2022)

• Record Type: Journal Article
• Authors: Desantis, Jenny; Mammoli, Andrea; Eleuteri, Michela; Coletti, Alice; Croci, Federico; Macchiarulo, Antonio; Goracci, Laura
• Is Part Of: RSC advances. Volume 12:Issue 34(2022)
• Page Start: 21968
• Page End: 21977
• Publication Date: 2022-08-09
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d2ra03761k
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : The p K a values of a dataset of PROTACs and PROTAC precursors have been analyzed in order to show how a fine modulation of piperazine-containing linkers can impact their protonation state. Abstract : Proteolysis targeting chimeras (PROTACs) represent an emerging class of compounds for innovative therapeutic application. Their bifunctional nature induces the formation of a ternary complex (target protein/PROTAC/E3 ligase) which allows target protein ubiquitination and subsequent proteasomal-dependent degradation. To date, despite great efforts being made to improve their biological efficacy PROTACs rational design still represents a challenging task, above all for the modulation of their physicochemical and pharmacokinetics properties. Considering the pivotal role played by the linker moiety, recently the insertion of a piperazine moiety into the PROTAC linker has been widely used, as this ring can in principle improve rigidity and increase solubility upon protonation. Nevertheless, the p K a of the piperazine ring is significantly affected by the chemical groups located nearby, and slight modifications in the linker could eliminate the desired effect. In the present study, the p K a values of a dataset of synthesized small molecule compounds including PROTACs and their precursors have been evaluated in order to highlight how a fine modulation of piperazine-containing linkers can impact the protonation state of these molecules or similar heterobifunctional ones. Finally, the possibility of predicting the trend through in silico approaches was also evaluated.