ArticleMolecular diversity2011
First computational chemistry multi-target model for anti-Alzheimer, anti-parasitic, anti-fungi, and anti-bacterial activity of GSK-3 inhibitors in vitro, in vivo, and in different cellular lines.
Article in Molecular diversity, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 71 citations in OpenAlex.
- Machine Learning Approach for Predicting Drug-Like Molecules Targeting Calmodulin Pathway Proteins.Journal of chemical information and modeling · 2025Article
- NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study.Journal of nanobiotechnology · 2024Article
- Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next?International journal of molecular sciences · 2022Review
- QSAR Modeling for Multi-Target Drug Discovery: Designing Simultaneous Inhibitors of Proteins in Diverse Pathogenic Parasites.Frontiers in chemistry · 2021Article
- BET bromodomain inhibitors: fragment-based in silico design using multi-target QSAR models.Molecular diversity · 2019Article
- In Silico Studies in Drug Research Against Neurodegenerative Diseases.Current neuropharmacology · 2018Review
- Three-way interaction model to trace the mechanisms involved in Alzheimer's disease transgenic mice.PloS one · 2017Article
- New α-Methylene-γ-Butyrolactone Derivatives as Potential Fungicidal Agents: Design, Synthesis and Antifungal Activities.Molecules (Basel, Switzerland) · 2016Article
- Glycogen Synthase Kinase-3 (GSK-3)-Targeted Therapy and Imaging.Theranostics · 2016Review
- Predicting antiprotozoal activity of benzyl phenyl ether diamine derivatives through QSAR multi-target and molecular topology.Molecular diversity · 2015Article
- Model for high-throughput screening of multitarget drugs in chemical neurosciences: synthesis, assay, and theoretic study of rasagiline carbamates.ACS chemical neuroscience · 2013Article
- In silico design of multi-target inhibitors for C-C chemokine receptors using substructural descriptors.Molecular diversity · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the work described here, we developed the first multi-target quantitative structure-activity relationship (QSAR) model able to predict the results of 42 different experimental tests for GSK-3 inhibitors with heterogeneous structural patterns. GSK-3β inhibitors are interesting candidates for developing anti-Alzheimer compounds. GSK-3β are also of interest as anti-parasitic compounds active against Plasmodium falciparum, Trypanosoma brucei, and Leishmania donovani; the causative agents for Malaria, African Trypanosomiasis and Leishmaniosis. The MARCH-INSIDE technique was used to quickly calculate total and local polarizability, n-octanol/water partition coefficients, refractivity, van der Waals area and electronegativity values to 4,508 active/non-active compounds as well as the average values of these indexes for active compounds in 42 different biological assays. Both the individual molecular descriptors and the average values for each test were used as input for a linear discriminant analysis (LDA). We discovered a classification function which used in training series correctly classifies 873 out of 1,218 GSK-3 cases of inhibitors (97.4%) and 2,140 out of 2,163 cases of non-active compounds (86.1%) in the 42 different tests. In addition, the model correctly classifies 285 out of 406 GSK-3 inhibitors (96.3%) and 710 out of 721 cases of non-active compounds (85.4%) in external validation series. The result is important because, for the first time, we can use a single equation to predict the results of heterogeneous series of organic compounds in 42 different experimental tests instead of developing, validating, and using 42 different QSAR models. Lastly, a double ordinate Cartesian plot of cross-validated residuals (first ordinate), standard residuals (second ordinate), and leverages (abscissa) defined the domain of applicability of the model as a squared area within ± 2 band for residuals and a leverage threshold of h = 0.0044.
Indexed as
Identifiers
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.