ReviewMolecules (Basel, Switzerland)2020
QSPR/QSAR: State-of-Art, Weirdness, the Future.
Review in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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
29 citing papers in PubMed.
- SPARFlow: a KNIME workflow for integrated structure-activity or structure-property relationship analysis.Journal of cheminformatics · 2026Article
- A machine learning approach for predicting osmotic coefficients and deriving activity coefficients in alkyl ammonium salts.Scientific reports · 2026Article
- Graph Neural Networks vs. Traditional QSAR: A Comprehensive Comparison for Multi-Label Molecular Odor Prediction.Molecules (Basel, Switzerland) · 2025Article
- MoleculeFormer is a GCN-transformer architecture for molecular property prediction.Communications biology · 2025Article
- Duality of Simplicity and Accuracy in QSPR: A Machine Learning Framework for Predicting Solubility of Selected Pharmaceutical Acids in Deep Eutectic Solvents.Molecules (Basel, Switzerland) · 2025Article
- Overcoming colorectal cancer and cancer stem cell resistance with photodynamic therapy: new frontiers in oncology.RSC advances · 2025Review
- Rational Design of Safer Inorganic Nanoparticles via Mechanistic Modeling-Informed Machine Learning.ACS nano · 2025Article
- Molecular and Descriptor Spaces for Predicting Initial Rate of Catalytic Homogeneous Quinoline Hydrogenation with Ru, Rh, Os, and Ir Catalysts.ACS omega · 2025Article
- The TOXIN knowledge graph: supporting animal-free risk assessment of cosmetics.Database : the journal of biological databases and curation · 2025Article
- MolPredictX: A Pioneer Mobile App Version for Online Biological Activity Predictions by Machine Learning Models.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study.International journal of molecular sciences · 2024Review
- Application of Transformers in Cheminformatics.Journal of chemical information and modeling · 2024Review
- Improving ADMET Prediction Accuracy for Candidate Drugs: Factors to Consider in QSPR Modeling Approaches.Current topics in medicinal chemistry · 2024Review
- Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction.The journal of physical chemistry. B · 2023Article
- The System of Self-Consistent Models: The Case of Henry's Law Constants.Molecules (Basel, Switzerland) · 2023Article
- Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives.Molecules (Basel, Switzerland) · 2023Article
- In vitro and Quantitative and Structure Activity Relationship (QSAR) evaluation of the antifungal activity of terpenoid constituents of essential oils against Alternaria alternata and Fusarium oxysporumBiomedica : revista del Instituto Nacional de Salud · 2023Article
- A compact review of progress and prospects of deep learning in drug discovery.Journal of molecular modeling · 2023Review
- Predicting the Surface Tension of Deep Eutectic Solvents: A Step Forward in the Use of Greener Solvents.Molecules (Basel, Switzerland) · 2022Article
- Maximizing the Performance of Similarity-Based Virtual Screening Methods by Generating Synergy from the Integration of 2D and 3D Approaches.International journal of molecular sciences · 2022Article
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
No grant is acknowledged in the PubMed record.
Abstract
Ability of quantitative structure-property/activity relationships (QSPRs/QSARs) to serve for epistemological processes in natural sciences is discussed. Some weirdness of QSPR/QSAR state-of-art is listed. There are some contradictions in the research results in this area. Sometimes, these should be classified as paradoxes or weirdness. These points are often ignored. Here, these are listed and briefly commented. In addition, hypotheses on the future evolution of the QSPR/QSAR theory and practice are suggested. In particular, the possibility of extending of the QSPR/QSAR problematic by searching for the "statistical similarity" of different endpoints is suggested and illustrated by an example for relatively "distanced each from other" endpoints, namely (i) mutagenicity, (ii) anticancer activity, and (iii) blood-brain barrier.
Indexed as
Identifiers
What Socratic 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 Socratic graph.