ArticleNature chemistry2012
Quantifying the chemical beauty of drugs.
Article in Nature chemistry, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 810 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
810 citing papers in PubMed.
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- ChemLint: Conversational Cheminformatics with Large Language Models.Journal of chemical information and modeling · 2026Article
- Pharmacological stratification of public bioactivity databases: a reusable, OECD-anchored curation and benchmarking framework demonstrated for opioid receptors.Digital discovery · 2026Article
- Pocket contrastive learning and conformation fusion for robust structure-conditioned 3D molecular generation under receptor conformational variation.Bioinformatics (Oxford, England) · 2026Article
- Exploring the renoprotective potential of Beta vulgaris in diabetic nephropathy: an integrated network pharmacology, molecular docking and dynamics simulation study.Molecular diversity · 2026Article
- VizChemoton: Visualization of Quantum Chemical Reaction Networks and Their Cheminformatics Features.Journal of chemical information and modeling · 2026Article
- Artificial intelligence-assisted lead optimization in drug discovery: bridging computational advances and translational challenges.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- PockLigGPT: Pocket-Sequence-Conditioned Molecular Generation with GPTs and RL.Journal of chemical information and modeling · 2026Article
- Data-Driven Critical Evaluation of the General Solubility Equation.Journal of chemical information and modeling · 2026Article
- Molecular modeling design of antitrypanosomal pyrazolone derivatives targeting Chagas disease: QSAR, docking, molecular dynamics and free energy calculations.Journal of molecular modeling · 2026Article
- Integrated experimental and computational evaluation of atractylenolide III from Tubipora musica for anticancer lead identification.Scientific reports · 2026Article
- AI-Powered Marine Drug Discovery: A Putative Dual c-Met/VEGFR2 Lead Candidate for Hepatocellular Carcinoma via Deep Learning and Multiscale Simulation.Current issues in molecular biology · 2026Article
- Design, Synthesis, Antimycobacterial Evaluation, and In Silico Investigation of Benzisothiazole-Based Hydrazide Derivatives as Potential Anti-Tuberculosis Agents.Chemical biology & drug design · 2026Article
- AI-enhanced adaptive virtual screening of large libraries for ligand discovery.Nature biotechnology · 2026Article
- MMP2Mol: a matched molecular pairs-based framework for ligand-based de novo drug design.Briefings in bioinformatics · 2026Article
- AET5: A transcriptome-guided molecular generation framework with contrastive self-supervised learning.PLoS computational biology · 2026Article
- From Fragments to Function: Novel Hydrazone Derivatives as Monoamine Oxidase Inhibitors.ChemMedChem · 2026Article
- Targeting WEE1 kinase: an integrated machine learning-cheminformatics framework for ultra-large-scale virtual screening and novel inhibitor discovery.Journal of computer-aided molecular design · 2026Article
750 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Drug-likeness is a key consideration when selecting compounds during the early stages of drug discovery. However, evaluation of drug-likeness in absolute terms does not reflect adequately the whole spectrum of compound quality. More worryingly, widely used rules may inadvertently foster undesirable molecular property inflation as they permit the encroachment of rule-compliant compounds towards their boundaries. We propose a measure of drug-likeness based on the concept of desirability called the quantitative estimate of drug-likeness (QED). The empirical rationale of QED reflects the underlying distribution of molecular properties. QED is intuitive, transparent, straightforward to implement in many practical settings and allows compounds to be ranked by their relative merit. We extended the utility of QED by applying it to the problem of molecular target druggability assessment by prioritizing a large set of published bioactive compounds. The measure may also capture the abstract notion of aesthetics in medicinal chemistry.
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What OpenQuestion holds
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.