ArticleJournal of chemical information and modeling2020
cando.py: Open Source Software for Predictive Bioanalytics of Large Scale Drug-Protein-Disease Data.
Article in Journal of chemical information and modeling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 32 citations in OpenAlex.
- Combining cutting edge computational and experimental methods for targeting KRAS mutations in non-small cell lung cancer.Expert opinion on drug discovery · 2026Review
- Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform.Journal of cheminformatics · 2026Article
- Deciphering bisphenol A (BPA)-elicited osteoarthritis mechanisms through network toxicology and molecular docking, then de novo generation of novel therapeutic candidates.BMC pharmacology & toxicology · 2025Article
- Strategies for robust, accurate, and generalizable benchmarking of drug discovery platforms.Bioinformatics (Oxford, England) · 2025Article
- Strategies for robust, accurate, and generalizable benchmarking of drug discovery platforms.bioRxiv : the preprint server for biology · 2025Article
- Umbelliferone as an effective component of Rhodiola for protecting the cerebral microvascular endothelial barrier in cSVD.Frontiers in pharmacology · 2025Article
- Drug repositioning pipeline integrating community analysis in drug-drug similarity networks and automated ATC community labeling to foster molecular docking analysis.Frontiers in bioinformatics · 2025Article
- Modeling Molecular Mechanisms of Pirfenidone Interaction with Kinases.bioRxiv : the preprint server for biology · 2024Article
- Antiviral Approaches against Influenza Virus.Clinical microbiology reviews · 2023Review
- Multiscale Analysis and Validation of Effective Drug Combinations Targeting Driver KRAS Mutations in Non-Small Cell Lung Cancer.International journal of molecular sciences · 2023Article
- Identifying Protein Features and Pathways Responsible for Toxicity Using Machine Learning and Tox21: Implications for Predictive Toxicology.Molecules (Basel, Switzerland) · 2022Article
- Proteomic Network Analysis of Bronchoalveolar Lavage Fluid in Ex-Smokers to Discover Implicated Protein Targets and Novel Drug Treatments for Chronic Obstructive Pulmonary Disease.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Evaluating the performance of drug-repurposing technologies.Drug discovery today · 2022Review
- Optimal COVID-19 therapeutic candidate discovery using the CANDO platform.Frontiers in pharmacology · 2022Article
- A Deep-Learning Proteomic-Scale Approach for Drug Design.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Multiscale Virtual Screening Optimization for Shotgun Drug Repurposing Using the CANDO Platform.Molecules (Basel, Switzerland) · 2021Article
- Shotgun drug repurposing biotechnology to tackle epidemics and pandemics.Drug discovery today · 2020Article
- Shotgun drug repurposing biotechnology to tackle epidemics and pandemics.ChemRxiv : the preprint server for chemistry · 2020Article
- Pathway-Based Drug-Repurposing Schemes in Cancer: The Role of Translational Bioinformatics.Frontiers in oncology · 2020Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Traditional drug discovery methods focus on optimizing the efficacy of a drug against a single biological target of interest for a specific disease. However, evidence supports the multitarget theory, i.e., drugs work by exerting their therapeutic effects via interaction with multiple biological targets, which have multiple phenotypic effects. Analytics of drug-protein interactions on a large proteomic scale provides insight into disease systems while also allowing for prediction of putative therapeutics against specific indications. We present a Python package for analysis of drug-proteome and drug-disease relationships implementing the Computational Analysis of Novel Drug Opportunities (CANDO) platform. The CANDO package allows for rapid drug similarity assessment, most notably via an in-house interaction scoring protocol where billions of drug-protein interactions are rapidly scored and the similarity of drug-proteome interaction signatures is calculated. The package also implements a variety of benchmarking protocols for shotgun drug discovery and repurposing, i.e., to determine how every known drug is related to every other in the context 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. Support for comparing and ranking novel chemical entities, as well as machine learning modules for both benchmarking and putative drug candidate prediction is also available. The CANDO Python package is available on GitHub at https://github.com/ram-compbio/CANDO, through the Conda Python package installer, and at http://compbio.org/software/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.