CANDO and the infinite drug discovery frontier

Abstract

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound–proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12–25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 ‘high value’ predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Multiscale Modelling of Relationships between Protein Classes and Drug Behavior Across all Diseases Using the CANDO Platform

“…choice of structural and chemical comparison methods and docking algorithms, limitation of a singular targeted therapy etc.) resulting in a better signal-to-noise to identify compounds with similar phenotype for repositioning [26]. CANDO predicts interaction between all human approved compounds and all protein structures.…”

Cutting Edge: Antimalarial Drugs Inhibit IFN-β Production through Blockade of Cyclic GMP-AMP Synthase–DNA Interaction

“…In silico structure-based drug screening was performed using Computational Analysis of Novel Drug Opportunities (17). Predictions made by this docking algorithm were confirmed by publicly available software, such as AutoDock Vina (18), and analyzed with the PyMOL Molecular Graphics System (version 1.5.0.4; Schrödinger) or UCSF Chimera (19).…”

Teriflunomide Restores 5-Azacytidine Sensitivity Via Activation of Pyrimidine Salvage in 5-Azacytidine-Resistant Leukemia Cells

“…We found teriflunomide, an immunomodulator approved for treatment of multiple sclerosis, to be an agent that can overcome and prevent AZA resistance in leukemia by using an approach based on the molecular mechanism underlying AZA resistance. Recent attention to drug repositioning has mainly focused on computational approaches using virtual screening of the comprehensive libraries of approved compounds based on threedimensional structures of target proteins [16][17][18]. However, mechanism-based drug repositioning may be another approach to finding drugs that can overcome drug resistance in cancer.…”