ArticleCPT: pharmacometrics & systems pharmacology2014
Identifying druggable targets by protein microenvironments matching: application to transcription factors.
Article in CPT: pharmacometrics & systems pharmacology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The trial behind it
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
18 citing papers in PubMed.
- Integrating evolutionary and compositional features with ML and DL for robust and interpretable druggable protein prediction.Journal of computer-aided molecular design · 2026Article
- Allosteric modulation of Plasmodium falciparum Isoleucyl tRNA synthetase by South African natural compounds.PloS one · 2025Article
- QuoteTarget: A sequence-based transformer protein language model to identify potentially druggable protein targets.Protein science : a publication of the Protein Society · 2023Article
- Empirical comparison and analysis of machine learning-based approaches for druggable protein identification.EXCLI journal · 2023Review
- The applications of deep learning algorithms on in silico druggable proteins identification.Journal of advanced research · 2022Article
- Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework.iScience · 2022Article
- Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks.Molecules (Basel, Switzerland) · 2022Article
- Activation of a Bacterial Mechanosensitive Channel, MscL, Underlies the Membrane Permeabilization of Dual-Targeting Antibacterial Compounds.Antibiotics (Basel, Switzerland) · 2022Article
- PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development.PLoS computational biology · 2018Article
- Biological and functional relevance of CASP predictions.Proteins · 2018Article
- Estimation of Maximum Recommended Therapeutic Dose Using Predicted Promiscuity and Potency.Clinical and translational science · 2016Article
- Targeted gene silencing of CCL2 inhibits triple negative breast cancer progression by blocking cancer stem cell renewal and M2 macrophage recruitment.Oncotarget · 2016Article
- Relating Essential Proteins to Drug Side-Effects Using Canonical Component Analysis: A Structure-Based Approach.Journal of chemical information and modeling · 2015Article
- The CCL2 chemokine is a negative regulator of autophagy and necrosis in luminal B breast cancer cells.Breast cancer research and treatment · 2015Article
- Pharmacological manipulation of transcription factor protein-protein interactions: opportunities and obstacles.Cell regeneration (London, England) · 2015Article
- Modulation of sodium iodide symporter in thyroid cancer.Hormones & cancer · 2014Review
- Knowledge-based fragment binding prediction.PLoS computational biology · 2014Article
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Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Druggability of a protein is its potential to be modulated by drug-like molecules. It is important in the target selection phase. We hypothesize that: (i) known drug-binding sites contain advantageous physicochemical properties for drug binding, or "druggable microenvironments" and (ii) given a target, the presence of multiple druggable microenvironments similar to those seen previously is associated with a high likelihood of druggability. We developed DrugFEATURE to quantify druggability by assessing the microenvironments in potential small-molecule binding sites. We benchmarked DrugFEATURE using two data sets. One data set measures druggability using NMR-based screening. DrugFEATURE correlates well with this metric. The second data set is based on historical drug discovery outcomes. Using the DrugFEATURE cutoffs derived from the first, we accurately discriminated druggable and difficult targets in the second. We further identified novel druggable transcription factors with implications for cancer therapy. DrugFEATURE provides useful insight for drug discovery, by evaluating druggability and suggesting specific regions for interacting with drug-like molecules.CPT: Pharmacometrics Systems Pharmacology (2014) 3, e93; doi:10.1038/psp.2013.66; published online 22 January 2014.
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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.