G4-QuadScreen: A Computational Tool for Identifying Multi-Target-Directed Anticancer Leads against G-Quadruplex DNA

SIMPLE SUMMARY: G-quadruplexes (G4s) are guanine-rich, four-stranded nucleic acid structures that are abundantly found in the promoter region of various oncogenes (cMYC, cKIT, KRAS, etc.) and in the telomeric region. The ligand-induced stabilization of G4s is shown to be efficient in targeted cancer therapy, and simultaneously targeting multiple G4s is beneficial. Thus, this study aimed to achieve the ‘stabilization of G4s with multi-target directed ligands (MTDL)’. We have developed different multi-tasking QSAR models to predict G4 interaction, G4 stabilization, G4 selectivity, and cytotoxicity and we have implemented them in the first computational tool, ‘G4-QuadScreen’, derived from this robust methodology with the functionality to screen-out a library of small-ligand molecules against G4 DNAs. A virtual screening using this ‘G4-QuadScreen’ server and a posterior experimental validation has allowed us to identify a total of three compounds with strong inhibitory effect on various human cancer cell lines, demonstrating the usefulness of computational tools to accelerate the discovery of novel anticancer therapies. ABSTRACT: The study presents ‘G4-QuadScreen’, a user-friendly computational tool for identifying MTDLs against G4s. Also, it offers a few hit MTDLs based on in silico and in vitro approaches. Multi-tasking QSAR models were developed using linear discriminant analysis and random forest machine learning techniques for predicting the responses of interest (G4 interaction, G4 stabilization, G4 selectivity, and cytotoxicity) considering the variations in the experimental conditions (e.g., G4 sequences, endpoints, cell lines, buffers, and assays). A virtual screening with G4-QuadScreen and molecular docking using YASARA (AutoDock-Vina) was performed. G4 activities were confirmed via FRET melting, FID, and cell viability assays. Validation metrics demonstrated the high discriminatory power and robustness of the models (the accuracy of all models is ~>90% for the training sets and ~>80% for the external sets). The experimental evaluations showed that ten screened MTDLs have the capacity to selectively stabilize multiple G4s. Three screened MTDLs induced a strong inhibitory effect on various human cancer cell lines. This pioneering computational study serves a tool to accelerate the search for new leads against G4s, reducing false positive outcomes in the early stages of drug discovery. The G4-QuadScreen tool is accessible on the ChemoPredictionSuite website.