| Autor: |
Bhat-Ambure J; MolDrug AI Systems SL, c/Olimpia Arozena Torres, 46018 Valencia, Spain., Ambure P; ProtoQSAR SL, Centro Europeo de Empresas Innovadoras (CEEI), Parque Tecnológico de Valencia, 46980 Valencia, Spain., Serrano-Candelas E; ProtoQSAR SL, Centro Europeo de Empresas Innovadoras (CEEI), Parque Tecnológico de Valencia, 46980 Valencia, Spain., Galiana-Roselló C; Department of Inorganic Chemistry, Institute of Molecular Science, University of Valencia, 46980 Valencia, Spain., Gil-Martínez A; Department of Inorganic Chemistry, Institute of Molecular Science, University of Valencia, 46980 Valencia, Spain., Guerrero M; Biochemistry and Molecular Biology Unit, Biomedicine Department, Faculty of Medicine and Health Sciences, University of Barcelona, 08036 Barcelona, Spain., Martin M; Biochemistry and Molecular Biology Unit, Biomedicine Department, Faculty of Medicine and Health Sciences, University of Barcelona, 08036 Barcelona, Spain.; Clinical and Experimental Respiratory Immunoallergy (IRCE), Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain., González-García J; Department of Inorganic Chemistry, Institute of Molecular Science, University of Valencia, 46980 Valencia, Spain., García-España E; Department of Inorganic Chemistry, Institute of Molecular Science, University of Valencia, 46980 Valencia, Spain., Gozalbes R; MolDrug AI Systems SL, c/Olimpia Arozena Torres, 46018 Valencia, Spain.; ProtoQSAR SL, Centro Europeo de Empresas Innovadoras (CEEI), Parque Tecnológico de Valencia, 46980 Valencia, Spain. |
| Abstrakt: |
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. |
