Discovery of a Covalent Small-Molecule eEF1A1 Inhibitor via Structure-Based Virtual Screening.

Pancreatic cancer remains a formidable health challenge due to its late-stage diagnosis and limited therapeutic options, underscoring the need for novel targets and modalities. Our previous work revealed that the natural product, BE-43547A, could effectively inhibit the progression of pancreatic cancer by the covalent binding to eukaryotic translation elongation factor 1 α 1 (eEF1A1) at Cys234 (C234). Considering the critical role in protein synthesis and the association with pancreatic cancer progression, eEF1A1 is a novel promising target for pancreatic cancer. However, the rational drug design methods for eEF1A1 are extremely lacking. Herein, using microsecond-scale molecular dynamics (MD) simulations, we identify a suitable eEF1A1 conformation for structure-based virtual screening (SBVS) by targeting the residue of C234. Through a tailored SBVS pipeline, we identified AKOS-04 as a novel small-molecule covalent inhibitor with nanomolar-level potency (IC = 28.5 ± 2.86 nM in the PATU8988T cell line). Notably, cellular thermal shift assays (CETSA), with the treatments of dithiothreitol (DTT) and iodoacetamide (IAM), confirmed the covalent Cys-involved interaction of AKOS-04 and eEF1A1. Further structural modification validated the critical contribution of a double bond in the acrylamide group of AKOS-04 for its covalent binding with eEF1A1, manifested by the abolished inhibitory activity of compound with the changed single bond in the acrylamide group. MST experiments confirmed direct binding of the compounds to eEF1A1 protein. AKOS-04 exhibited the strongest binding among the tested compounds, consistent with effective covalent target. Finally, MD simulations and pair-interaction energy analyses highlighted Lys84, Arg218, and Glu230 of eEF1A1 as key residues for driving its binding interactions to AKOS-04. These results reveal that AKOS-04, screened by SBVS against C234 of eEF1A1, represents a promising lead for eEF1A1-targeted pancreatic cancer therapy, highlighting the power of computational approaches in covalent drug discovery.