Active learning driven prioritisation of compounds from on-demand libraries targeting the SARS-CoV-2 main protease.

FEgrow is an open-source software package for building congeneric series of compounds in protein binding pockets. For a given ligand core and receptor structure, it employs hybrid machine learning/molecular mechanics potential energy functions to optimise the bioactive conformers of supplied linkers and functional groups. Here, we introduce significant new functionality to automate, parallelise and accelerate the building and scoring of compound suggestions, such that it can be used for automated design.

Cyclic peptides target the aromatic cage of a PHD-finger reader domain to modulate epigenetic protein function.

Plant homeodomain fingers (PHD-fingers) are a family of reader domains that can recruit epigenetic proteins to specific histone modification sites. Many PHD-fingers recognise methylated lysines on histone tails and play crucial roles in transcriptional regulation, with their dysregulation linked to various human diseases. Despite their biological importance, chemical inhibitors for targeting PHD-fingers are very limited.