DiPCell: Designing of promiscuous inhibitors against pancreatic cancer cell lines

DiPCell is a specialized computational platform designed to accelerate the drug discovery process for pancreatic cancer, one of the most devastating diseases with a very poor prognosis. Unlike tools focused on peptides, this specific iteration of DiPCell is a web-bench for predicting and screening promiscuous inhibitors—small molecules capable of targeting multiple oncogenic pathways—to improve therapeutic outcomes in pancreatic cancer. Web Server: https://webs.iiitd.edu.in/raghava/dipcell/ Citation Kumar, R., Chaudhary, K., Singla, D. et al. Designing of promiscuous inhibitors against pancreatic cancer cell lines. Sci Rep 4, 4668 (2014). https://doi.org/10.1038/srep04668 About the Research The primary goal of this resource is to identify effective drug candidates by leveraging large-scale pharmacological data. The platform uses Quantitative Structure-Activity Relationship (QSAR) models to predict the efficacy of compounds against various pancreatic cancer cell lines. Model Performance: The QSAR models achieved a maximum Pearson correlation coefficient of 0.86 during 10-fold cross-validation, indicating high predictive reliability. Validation: The models successfully validated known drug-to-oncogene relationships, ensuring the computational predictions align with biological reality. Experimental Testing: The researchers used these models to screen FDA-approved drugs, which were subsequently tested in vitro to confirm their effectiveness.