ArticleJournal of medicinal chemistry2015
New Frontiers in Druggability.
Article in Journal of medicinal chemistry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
52 citing papers in PubMed.
- MEGPNM as a multiscale edge-aware GAT network with hybrid pooling predicting permeability of non-peptidic macrocycles.Communications chemistry · 2026Article
- In Silico Druggability Assessment ofAntibiotics (Basel, Switzerland) · 2026Article
- Reading between the Chains: Surface Mapping and Druggable Pockets on the Biological Assemblies of DENV-2's Protein E.ACS omega · 2026Article
- New Bioinformatic Insight into CD44: Classification of Human Variants and Structural Analysis of CD44 Targeting.International journal of molecular sciences · 2025Article
- Alphappimi: a comprehensive deep learning framework for predicting PPI-modulator interactions.Journal of cheminformatics · 2025Article
- E-FTMap: A Protein Structure Based Pharmacophore Identification Server for Guiding Fragment Expansion.Journal of molecular biology · 2025Article
- Recent computational advances in the identification of cryptic binding sites for drug discovery.Bioinformatics advances · 2025Review
- Which cryptic sites are feasible drug targets?Drug discovery today · 2024Review
- Identification and Ranking of Binding Sites from Structural Ensembles: Application to SARS-CoV-2.Viruses · 2024Article
- Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites.Journal of chemical information and modeling · 2024Article
- Conservation of Hot Spots and Ligand Binding Sites in Protein Models by AlphaFold2.Journal of chemical information and modeling · 2024Article
- Identification of a druggable site on GRP78 at the GRP78-SARS-CoV-2 interface and virtual screening of compounds to disrupt that interface.Journal of computer-aided molecular design · 2024Article
- Mining gene expression data for rational identification of novel drug targets and vaccine candidates against the cattle tick, Rhipicephalus microplus.Experimental & applied acarology · 2023Article
- Screening and Biological Evaluation of Soluble Epoxide Hydrolase Inhibitors: Assessing the Role of Hydrophobicity in the Pharmacophore-Guided Search of Novel Hits.Journal of chemical information and modeling · 2023Article
- Conformation-dependent ligand hot spots in the spliceosomal RNA helicase BRR2.Acta crystallographica. Section D, Structural biology · 2023Article
- Conservation of Allosteric Ligand Binding Sites in G-Protein Coupled Receptors.Journal of chemical information and modeling · 2022Article
- Exploring the Surface of the Ectodomain of the PD-L1 Immune Checkpoint with Small-Molecule Fragments.ACS chemical biology · 2022Article
- Mapping the binding sites of challenging drug targets.Current opinion in structural biology · 2022Review
- FTMove: A Web Server for Detection and Analysis of Cryptic and Allosteric Binding Sites by Mapping Multiple Protein Structures.Journal of molecular biology · 2022Article
- A Modular Synthesis of Teraryl-Based α-Helix Mimetics, Part 4: Core Fragments with Two Halide Leaving Groups Featuring Side Chains of Proteinogenic Amino Acids.European journal of organic chemistry · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
A powerful early approach to evaluating the druggability of proteins involved determining the hit rate in NMR-based screening of a library of small compounds. Here, we show that a computational analog of this method, based on mapping proteins using small molecules as probes, can reliably reproduce druggability results from NMR-based screening and can provide a more meaningful assessment in cases where the two approaches disagree. We apply the method to a large set of proteins. The results show that, because the method is based on the biophysics of binding rather than on empirical parametrization, meaningful information can be gained about classes of proteins and classes of compounds beyond those resembling validated targets and conventionally druglike ligands. In particular, the method identifies targets that, while not druggable by druglike compounds, may become druggable using compound classes such as macrocycles or other large molecules beyond the rule-of-five limit.
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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.