ArticleJournal of medicinal chemistry2023
Molecular Complexity: You Know It When You See It.
Article in Journal of medicinal chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Nickel-catalyzed ring-opening difunctionalization of methylenecyclobutanes via strain-release-enabled C-C activation.Nature communications · 2026Article
- Molecular Complexity Constrained Early Amino Acid Recruitment into the Genetic Code.Genome biology and evolution · 2026Article
- Accessing Molecular Complexity from Methane and Other Gaseous Alkanes via Photocatalytic Cascade Cyclization.Angewandte Chemie (International ed. in English) · 2026Article
- Natural Products Repository of Costa Rica (NAPRORE-CR): An Open-Access Database.Journal of chemical information and modeling · 2025Article
- A View on Molecular Complexity from the GDB Chemical Space.Journal of chemical information and modeling · 2025Review
- Rational Method for Structural Simplification as Key Step in Hit Discovery: The Case of FGFR2 and IGF1R Dual Inhibitors.International journal of molecular sciences · 2025Article
- Unifying principles for the design and evaluation of natural product-inspired compound collections.Chemical science · 2025Review
- Latin American Natural Product Database (LANaPDB): An Update.Journal of chemical information and modeling · 2024Article
- Evaluating Molecular Complexity with Open-Source Machine Learning Approaches to Predict Process Mass Intensity.ACS omega · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Molecular complexity (MC) lacks a universal definition, but various studies address it in contexts ranging from ligand-receptor interactions to DNA sequencing, with the overarching emphasis being its significance in synthetic organic chemistry and pharmaceutical research. Efforts to quantify MC in drug discovery have been numerous, but a unified approach remains challenging. Strategies based on graph theory, information theory, and substructural feature counts employed to gauge MC are often correlated to molecular weight (MW). Herbert Waldmann and his team introduced a new MC metric called the spacial score (SPS), which is based on factors like atom hybridization and stereoisomeric considerations. While SPS and its normalized version, nSPS, correlate with the natural product likeness score, they do not align with traditional chemical properties. We examined nSPS trends for approved drugs and found no significant changes in MC over eight decades, nor did nSPS capture drug innovation during that period. Furthermore, our analysis indicates that while the majority of approved drugs have an nSPS value between 10 and 20, this metric does not correlate with key drug properties like target bioactivity and oral bioavailability. Mirroring a chemist's intuitive sense of chemical complexity, nSPS addresses the need for a precise empirical tool while a universal definition of MC remains elusive.
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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.