ReviewCurrent pharmaceutical design2016
Exploring Polypharmacology in Drug Discovery and Repurposing Using the CANDO Platform.
Review in Current pharmaceutical design, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed.
- 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
- Current AI technologies in cancer diagnostics and treatment.Molecular cancer · 2025Review
- 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
- Optimal COVID-19 therapeutic candidate discovery using the CANDO platform.Frontiers in pharmacology · 2022Article
- Hybrid drug-screening strategy identifies potential SARS-CoV-2 cell-entry inhibitors targeting human transmembrane serine protease.Structural chemistry · 2022Article
- Evaluating the performance of drug-repurposing technologies.Drug discovery today · 2022Review
- 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
- Exploiting cheminformatic and machine learning to navigate the available chemical space of potential small molecule inhibitors of SARS-CoV-2.Computational and structural biotechnology journal · 2021Article
- Accurate Prediction of Inhibitor Binding to HIV-1 Protease Using CANDOCK.Frontiers in chemistry · 2021Article
- Identification of potential antivirals against SARS-CoV-2 using virtual screening method.Informatics in medicine unlocked · 2021Article
- CANDOCK: Chemical Atomic Network-Based Hierarchical Flexible Docking Algorithm Using Generalized Statistical Potentials.Journal of chemical information and modeling · 2020Article
- Fingerprinting CANDO: Increased Accuracy with Structure- and Ligand-Based Shotgun Drug Repurposing.ACS omega · 2019Article
- Computational chemoproteomics to understand the role of selected psychoactives in treating mental health indications.Scientific reports · 2019Article
- Molecular Docking: Shifting Paradigms in Drug Discovery.International journal of molecular sciences · 2019Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
backgroundTraditional drug discovery approaches focus on a limited set of target molecules for treatment against specific indications/diseases. However, drug absorption, dispersion, metabolism, and excretion (ADME) involve interactions with multiple protein systems. Drugs approved for particular indication(s) may be repurposed as novel therapeutics for others. The severely declining rate of discovery and increasing costs of new drugs illustrate the limitations of the traditional reductionist paradigm in drug discovery.
methodsWe developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform based on a hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for therapeutic repurposing and discovery. We compiled a library of compounds that are human ingestible with minimal side effects, followed by an 'all-compounds' vs 'all-proteins' fragment-based multitarget docking with dynamics screen to construct compound-proteome interaction matrices that were then analyzed to determine similarity of drug behavior. The proteomic signature similarity of drugs is then ranked to make putative drug predictions for all indications in a shotgun manner.
resultsWe have previously applied this platform with success in both retrospective benchmarking and prospective validation, and to understand the effect of druggable protein classes on repurposing accuracy. Here we use the CANDO platform to analyze and determine the contribution of multitargeting (polypharmacology) to drug repurposing benchmarking accuracy. Taken together with the previous work, our results indicate that a large number of protein structures with diverse fold space and a specific polypharmacological interactome is necessary for accurate drug predictions using our proteomic and evolutionary drug discovery and repurposing platform.
conclusionThese results have implications for future drug development and repurposing in the context of polypharmacology.
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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.