ArticlePLoS computational biology2015
Large-scale chemical similarity networks for target profiling of compounds identified in cell-based chemical screens.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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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Who cites it
34 citing papers in PubMed, 76 citations in OpenAlex.
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- Computational Approaches to the Rational Design of Tubulin-Targeting Agents.Biomolecules · 2023Review
- Random-forest model for drug-target interaction prediction via Kullbeck-Leibler divergence.Journal of cheminformatics · 2022Article
- De Novo Prediction of Drug Targets and Candidates by Chemical Similarity-Guided Network-Based Inference.International journal of molecular sciences · 2022Article
- CytofIn enables integrated analysis of public mass cytometry datasets using generalized anchors.Nature communications · 2022Article
- Whole proteome mapping of compound-protein interactions.Current research in chemical biology · 2022Article
- Computational Methods for Drug Repurposing.Advances in experimental medicine and biology · 2022Article
- Antifungal Drug Resistance: Molecular Mechanisms inChemical reviews · 2021Review
- Currently Available Strategies for Target Identification of Bioactive Natural Products.Frontiers in chemistry · 2021Review
- A review on compound-protein interaction prediction methods: Data, format, representation and model.Computational and structural biotechnology journal · 2021Review
- Computational/in silico methods in drug target and lead prediction.Briefings in bioinformatics · 2020Review
- Extending the small-molecule similarity principle to all levels of biology with the Chemical Checker.Nature biotechnology · 2020Article
- Scope of 3D Shape-Based Approaches in Predicting the Macromolecular Targets of Structurally Complex Small Molecules Including Natural Products and Macrocyclic Ligands.Journal of chemical information and modeling · 2020Article
- Validation strategies for target prediction methods.Briefings in bioinformatics · 2020Review
- Target Identification Using Homopharma and Network-Based Methods for Predicting Compounds Against Dengue Virus-Infected Cells.Molecules (Basel, Switzerland) · 2020Article
- Associating 197 Chinese herbal medicine with drug targets and diseases using the similarity ensemble approach.Acta pharmacologica Sinica · 2020Article
- Dissecting the mechanisms of cell division.The Journal of biological chemistry · 2019Review
- Leukemia Cell Cycle Chemical Profiling Identifies the G2-Phase Leukemia Specific Inhibitor Leusin-1.ACS chemical biology · 2019Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Target identification is one of the most critical steps following cell-based phenotypic chemical screens aimed at identifying compounds with potential uses in cell biology and for developing novel disease therapies. Current in silico target identification methods, including chemical similarity database searches, are limited to single or sequential ligand analysis that have limited capabilities for accurate deconvolution of a large number of compounds with diverse chemical structures. Here, we present CSNAP (Chemical Similarity Network Analysis Pulldown), a new computational target identification method that utilizes chemical similarity networks for large-scale chemotype (consensus chemical pattern) recognition and drug target profiling. Our benchmark study showed that CSNAP can achieve an overall higher accuracy (>80%) of target prediction with respect to representative chemotypes in large (>200) compound sets, in comparison to the SEA approach (60-70%). Additionally, CSNAP is capable of integrating with biological knowledge-based databases (Uniprot, GO) and high-throughput biology platforms (proteomic, genetic, etc) for system-wise drug target validation. To demonstrate the utility of the CSNAP approach, we combined CSNAP's target prediction with experimental ligand evaluation to identify the major mitotic targets of hit compounds from a cell-based chemical screen and we highlight novel compounds targeting microtubules, an important cancer therapeutic target. The CSNAP method is freely available and can be accessed from the CSNAP web server (http://services.mbi.ucla.edu/CSNAP/).
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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.