Exploration of interaction scoring criteria in the CANDO platform

Abstract Background Drug discovery is an arduous process that requires many years and billions of dollars before approval for patient use. However, there are a number of drugs and human ingestibles approved for a variety of indications/diseases that can be potentially repurposed as new treatments for others, decreasing the time and cost required. Methods CANDO (Computational Analysis of Novel Drug Opportunities) is a platform for shotgun, multitarget drug discovery and repurposing. The CANDO platform scores interactions between 46,784 proteins structures and 3,733 human use compounds using a bioinformatic docking protocol to generate compound-proteome interaction signatures that are then compared to identify candidates for repurposing. Benchmarking of the platform is accomplished by comparing the compound-proteome interaction signatures and determining whether signatures corresponding to pairs of drugs approved for the same indication fall within particular cutoffs. Results We have altered the scoring function of bioinformatic docking protocol in the newest version of our platform (v1.5) to use the best OBscore for each compound-protein interaction, resulting in an increased benchmarking accuracy from 11.7% in v1 to 12.8% in v1.5 for the top10 cutoff, the most stringent one used, and correspondingly from 24.9% to 31.2% for the top100 cutoff. Conclusions The change in the interaction scoring and other bug fixes in CANDO v1.5 have resulted in improved benchmarking performance, making the platform more effective at predicting novel, therapeutic drug-indication pairs.