ArticleJournal of computer-aided molecular design2012
The inevitable QSAR renaissance.
Article in Journal of computer-aided molecular design, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Beyond Amyloid: A Machine Learning-Driven Approach Reveals Properties of Potent GSK-3β Inhibitors Targeting Neurofibrillary Tangles.International journal of molecular sciences · 2024Article
- Gains from no real PAINS: Where 'Fair Trial Strategy' stands in the development of multi-target ligands.Acta pharmaceutica Sinica. B · 2021Review
- Comprehensive strategies of machine-learning-based quantitative structure-activity relationship models.iScience · 2021Review
- Outliers in SAR and QSAR: 3. Importance of considering the role of water molecules in protein-ligand interactions and quantitative structure-activity relationship studies.Journal of computer-aided molecular design · 2021Article
- Targeting Tumors Using Peptides.Molecules (Basel, Switzerland) · 2020Review
- BCL::Mol2D-a robust atom environment descriptor for QSAR modeling and lead optimization.Journal of computer-aided molecular design · 2019Article
- Performance of Machine Learning Algorithms for Qualitative and Quantitative Prediction Drug Blockade of hERG1 channel.Computational toxicology (Amsterdam, Netherlands) · 2018Article
- Quantitative Structure-Activity Relationship Model for HCVNS5B inhibitors based on an Antlion Optimizer-Adaptive Neuro-Fuzzy Inference System.Scientific reports · 2018Article
- A perspective on multi-target drug discovery and design for complex diseases.Clinical and translational medicine · 2018Article
- Meta-QSAR: a large-scale application of meta-learning to drug design and discovery.Machine learning · 2018Article
- Aromatase inhibitory activity of 1,4-naphthoquinone derivatives and QSAR study.EXCLI journal · 2017Article
- Three-dimensional QSAR analysis and design of new 1,2,4-oxadiazole antibacterials.Bioorganic & medicinal chemistry letters · 2016Article
- Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies.Frontiers in neuroscience · 2016Review
- Antiprotozoal Nitazoxanide Derivatives: Synthesis, Bioassays and QSAR Study Combined with Docking for Mechanistic Insight.Current computer-aided drug design · 2015Article
- QSAR modeling: where have you been? Where are you going to?Journal of medicinal chemistry · 2014Article
- On exploring structure-activity relationships.Methods in molecular biology (Clifton, N.J.) · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
QSAR approaches, including recent advances in 3D-QSAR, are advantageous during the lead optimization phase of drug discovery and complementary with bioinformatics and growing data accessibility. Hints for future QSAR practitioners are also offered.
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.