Abstract
Clinical efficacy of targeted signaling inhibitors for hematologic malignancies is limited bynoutgrowth of subpopulations with alternative pathways independent of the drug target. The eIF4F complex responsible for translation initiation is a convergence point for cancer-promoting signaling pathways and its inhibition leads to decreased expression of key oncoproteins and apoptosis. Lymphomas and leukemias show particular dependence on constitutive eIF4F activation. Indeed, natural compounds targeting the eIF4F enzymatic component, eIF4A1, demonstrate activities in vitro and in vivo against lymphoma and leukemia model systems, among other tumor types. The natural compound silvestrol is a potent inhibitor of eIF4A1, results in cancer cell cytotoxicity, and has an established therapeutic window in vivo. Silvestrol shows potent antitumor activity against 924 pan-cancer tumor cell lines with 830/924 (90%) sensitive at IC50 <100nM with lymphoma and leukemia cell lines being particularly sensitive. Silvestrol and other natural compounds, however, lack core drug-like properties and synthetic tractability. To discover new, specific and tractable inhibitors of eIF4A1 that are more drug-like, we have constructed several molecular models that we used to virtually screen more than 20 million compounds. eIF4A1 is the founding member of the DEAD-box RNA helicases, which include its paralogs eIF4A2 (91% amino-acid identity with eIF4A1) and eIF4A3 (60% identity). All DEAD-box helicases contain two RecA-like domains separated by a flexible linker. The cleft between these domains is lined with helicase motifs that mediate nucleotide binding and hydrolysis. In an absence of RNA or nucleotide, eIF4A proteins adopt diffuse open conformations; binding of RNA and ATP triggers transition to a more stable closed state. Modeling small-molecule interactions in the nucleotide cleft of eIF4A1 therefore assesses ability of molecules to lock eIF4A1 in a conformation unable to cycle through ATPase and helicase activities. A new crystal structure of eIF4A1 has become available (2019) with a resolution of 2 angstroms. The protein is co-crystallized with ANP in the nucleotide binding site at the interface of the N and C-terminal domains and with known inhibitor, Rocaglamide, bound to the interface of the eIF4A1and a polypurine RNA. We used this high-resolution crystal structure to build models predicting interactions of small molecules in the interdomain nucleotide-binding cleft. We then performed all-atom explicit-water molecular dynamics (MD) simulations for 500-700 ns to study conformational dynamics and atomic interactions of ATP-bound and ATP-unbound states. Extended molecular dynamic simulations confirm the hypothesis that rocaglamide stabilizes the interaction between the helicase and a polypurine sequence on RNA, thus preventing further ATPase activity and RNA unwinding. Pooling these results, we constructed two homology models of human eIF4A1 with both open and closed conformations as structural templates. Over 50 compounds identified as hits in silicowere ordered and tested thus far in our biochemical and cell-based validation platform. Using our machine learning and virtual screening approach targeted to the ATP binding site of eIF4A1, we identified a promising piperazine-amide fragment scaffold (UM107; ~300 MW) with similar electronics to nucleotide triphosphates. UM107 caused cellular toxicities with an LD50 of 50 uM and was weakly active in the biochemical screen against eIF4A1 with an IC50 of 250 uM. We will increase molecular weight by adding more groups to maximize hydrogen bond interactions in the active site. These analogs will be synthesized and screened virtually building on the core using established medicinal chemistry optimization tools followed by biochemical and cellular validation. We therefore have developed an accurate and novel in silico models of eIF4A1 highly useful in assessing interactions of small-molecule ATPase inhibitors, with focus on the ATP-binding cleft. Disclosures No relevant conflicts of interest to declare.
