Abstract

Molecular chameleonicity may enable compounds to compensate for the unfavorable ADME properties typically associated with complex molecules, such as PROTACs. Here we present a few in silico strategies to implement chameleonicity considerations in drug design. Initially, we identified six structurally related CRBN-based PROTACs targeting BET proteins and experimentally verified whether chameleonicity is needed to obtain an acceptable physicochemical profile. Then, we utilized experimental data to validate our novel computational strategies based on tools crafted to encompass a spectrum of complexities and innovative features. After confirming that the formation of IMHBs is the primary driving factor behind chameleonicity, we initially utilized conformational sampling data to define cChameCS, an IMHB-mediated, simple, and rapid chameleonicity predictor index suitable for early drug discovery. Subsequently, we identified dynamic IMHB patterns relevant to chameleonicity through molecular dynamics simulations. Finally, we proposed a workflow for designing structurally related chameleonic PROTACs of potential application in the lead optimization process.

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