cando.py: Open source software for predictive bioanalytics of large scale drug-protein-disease data

Abstract

Motivation: Elucidating drug-protein interactions is essential for understanding the beneficial effects of small molecule therapeutics in human disease states. Common drug discovery methods focus on optimizing the efficacy of a drug against a single biological target of interest. However, evidence supports the multitarget theory, i.e., drugs work by exerting their therapeutic effects via interaction with multiple biological targets. Analyzing drug interactions with a library of proteins can provide further insight into disease systems while also allowing for prediction of putative therapeutics. Results: We present the CANDO Python package for analysis of drug-proteome and drug-disease relationships. This package allows for rapid drug similarity assessment, most notably via the bioinformatic docking protocol in which protein interactions can be quickly scored for thousands of compounds. The platform can be benchmarked through a variety of protocols to determine how well drugs are related to each other in terms of the indications/diseases for which they are approved. Drug predictions are generated through consensus scoring of the most similar compounds to drugs known to treat a particular indication. Availability: The CANDO Python package is available on GitHub at https://github.com/ram-compbio/CANDO, through the Conda Python package installer, and at

Evaluating Performance of Drug Repurposing Technologies

“…We developed and deployed the CANDO platform to model the relationships between every disease/indication and every human use drug/compound [7][8][9][10][11][12][13][14][15][16][17]. Built upon the premise of polypharmacology and multitargeting, at the core of CANDO is the ability to infer similarity of compound/drug behavior.…”

“…Since the development and application of CANDO version 1 [7][8][9][10], we have continued to enhance our platform by analyzing the effect of protein subsets on drug behavior, implementing heterogeneous measures of drug/compound similarity, using multiple molecular docking software packages to evaluate interactions, and refining non-similarity based approaches for drug repurposing in situations where there there is no approved drug for a disease/indication [11][12][13][14][15][16][17]38].…”

“…Less defined end goals (high risk) enable researchers to systematically disrupt the entire drug discovery and development process (high reward). Drug repurposing technologies such as our Computational Analysis of Novel Drug Opportunities (CANDO) platform [7][8][9][10][11][12][13][14][15][16][17] may be used to systematically predict the relative efficacy of every drug in its comprehensive library to treat every disease/indication, minimizing risks and amplifying rewards. In conjunction with mechanistic basic science analyses, these platforms may be used to better understand the science of drug behavior and thereby model reality with greater fidelity.…”

Multiscale virtual screening optimization for shotgun drug repurposing using the CANDO platform

“…Drug repurposing is the practice of finding new uses for existing drugs, taking advantage of prior safety, efficacy, and pharmacological knowledge and data [14]. Drug repurposing has the potential to arbitrarily increase the utility of the FDA approved drug library [19,16,20], particularly via innovations such as multitarget drug repurposing [21,22]. Drug repurposing has yielded new uses for multiple drugs [14,16] and has demonstrated potential for the treatment of viral [23,24], bacterial [25], and complex indications such as cancer [16].…”

Shotgun drug repurposing biotechnology to tackle epidemics and pandemics

“…We developed the Computational Analysis of Novel Drug Repurposing Opportunities (CANDO) platform for shotgun multitarget drug discovery, repurposing, and design [1,2,7], funded in part by a 2010 NIH Director's Pioneer Award and previously described in Drug Discovery Today in 2014 [1], for precisely this type of pandemic scenario. The platform screens and ranks every existing human use drug for every disease/indication through large scale modelling and analysis of interactions between comprehensive libraries of drugs/compounds and protein structures.…”