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Drug-target interaction, molecular screening, ADMET, compound databases, pharmaceutical data
619 datasets
Four seagrass species were exposed to four priority PSII herbicides in controlled experiments to measure inhibition concentrations (IC10, IC20, IC50) over 72 hours. The dataset, from the NERP TE 4.2 project by AIMS and JCU, contains dose-response curves derived from pulse amplitude modulation fluorometry measurements. Data is provided as a multi-sheet spreadsheet from experiments conducted in 2012-2013.
Eight herbicides detected in Great Barrier Reef catchments were tested for their effects on the specific growth rates of the marine microalgae Tetraselmis sp. during laboratory experiments conducted in 2019. The project applied standard ecotoxicology protocols to determine the effects of Photosystem II (PSII) and alternative herbicides on algal growth over 3-day exposures. Data was contributed by the Australian Ocean Data Network.
Laboratory experiments from 2018-2019 measured the effects of 12 specific pesticides on the growth rates of the marine microalgae Tisochrysis lutea. The Australian Ocean Data Network hosts this dataset, which applies standard ecotoxicology protocols to assess risks to Great Barrier Reef ecosystems. Toxicity data for diuron, metribuzin, tebuthiuron, bromacil, propazine, simazine, imazapic, haloxyfop-p-methyl, 2,4-D, MCPA, fluroxypyr, and propiconazole were generated over 72-hour exposures.
Experiments conducted in 2014 measured the response of seagrass photosystems to herbicides. The dataset was created to develop and validate a miniature toxicity assay using isolated seagrass leaves in 12-well plates. It was contributed by the Australian Ocean Data Network.
ETH Zurich researchers led by Christophe Capelle generated this dataset for a 2023 Nature Communications study on idiopathic Parkinson's disease. It contains raw mass cytometry (CyTOF) and flow cytometry fcs files from discovery and validation analyses of immune cells in blood samples. The dataset includes files for five staining panels, cytotoxicity analysis within CD8 T cells, and single-color compensation controls.
800 primary alphabetical entries define terms for neurotoxicology and related neurology concepts. Douglas M. Templeton of the University of Toronto authored this glossary to aid chemists, toxicologists, and regulators in interpreting neurotoxic effects literature. The resource includes annexes of common abbreviations and examples of chemicals with known nervous system effects.
218 individual binary mixtures of pesticides and veterinary drugs were collected for statistical analysis of combined toxicity in bees. Data includes lethal dose and concentration endpoints for honeybees and wild bee species across acute contact, chronic oral, and acute oral exposure patterns. Edoardo Carnesecchi of Utrecht University compiled this dataset, described in a 2019 paper.
A dataset of 13,221 small molecules with up to 7 heavy atoms derived from the GDB-11 and GDB-13 chemical universe databases. For each molecule, it includes a minimized geometry and up to 10 geometries sampled from molecular dynamics, with RHF and B3LYP energies computed using five basis sets in the Psi4 package. The dataset was created by Søren Holm of Stanford University.
60 million datapoints comprise the Papyrus dataset, an aggregated collection of small molecule bioactivities for machine learning. It combines large public sources like ChEMBL and ExCAPE-DB with smaller high-quality datasets, standardized for predictive modeling. The dataset was created by Olivier J. M. Béquignon of Leiden University.
Ligand Binding Affinity (LBA) data from the ATOM3D project, provided in LMDB format. The upload includes the full dataset and pre-split versions at 60% and 30% protein sequence identity thresholds, along with corresponding train, validation, and test indices. The dataset was created by Raphael J.L. Townshend of Stanford University.
Three novel PSMA-targeted radioligands (PSA3-1, PDA3-1, PDB3-1) were synthesized and evaluated for prostate cancer theranostics. PDB3-1 demonstrated high binding affinity (IC50 = 19.1 nM) and, in PC-3 PIP tumor-bearing mice, showed high tumor uptake with rapid renal clearance. Tao Zhang published this preclinical data on figshare in May 2026.
Boronic acid compounds designed via a de novo library and virtual screening platform target the ClpP enzyme. The dataset likely contains results from a study identifying α-aminoboronic acids as inhibitors of human ClpXP, which degrades misfolded proteins. R.E. Lee from the University of Toronto authored this research, which is available under an Open Access license.
A descriptor-free deep learning model predicts chemical toxicity for androgen and estrogen receptors directly from SMILES strings. The models were trained on 1,664 and 1,529 chemicals with experimental binary labels for AR and ER, respectively, achieving accuracy scores of 0.75 and 0.81. Francesca Cutropia published this work on figshare in 2026, introducing an explainable AI approach for substructure-level interpretability.
Ursula Scheffel of Johns Hopkins University describes the development of PET and SPECT radioligands targeting the serotonin transporter. The description details the need for such imaging agents to screen at-risk populations and study serotonergic function in neuropsychiatric disorders. It evaluates several candidate tracers, including [11C]RTI-55 and [11C]McN-5652-X, discussing their binding affinity, selectivity, and current research status.
Tao Zhang's dataset on figshare contains results from a preclinical study evaluating novel PSMA-targeted radioligands for prostate cancer theranostics. The data likely includes radiochemical purity (>98%), binding affinity (IC50 = 19.1 nM), and in vivo biodistribution results from PC-3 PIP tumor-bearing mice. The dataset was last updated on 2026-05-28.
A paper from the University of Manchester presents rules for computing co-reference chains across multiple drug discovery datasets. The work addresses the challenge of linking equivalent concepts across datasets that use different identifiers and data models. The approach emphasizes capturing the context of equivalence to allow data consumers to control which co-references are included in their applications.
A research analysis by Steven F. Magruder of Johns Hopkins University Applied Physics Laboratory correlates over-the-counter pharmaceutical sales counts with physician encounter counts for public health surveillance. The study measures timeliness and illustrates a two-stage clustering method that produced 16 product supergroups. The dataset likely contains sales and clinical encounter data, though its specific size and format are not detailed.
2,400 Russian-language texts annotated for binary toxicity classification. The dataset is balanced with 1,200 toxic and 1,200 non-toxic entries, split into training, validation, and test sets. It was created by user 'tankoooo' and last updated on Hugging Face in July 2026.
John H. Duffus of the University of Edinburgh compiled this glossary of terms used in toxicology. It is a revision of prior IUPAC glossaries, incorporating definitions and explanatory notes for terms relevant to hazard and risk assessment. The glossary includes three annexes with abbreviations, acronyms, and a classification of carcinogenicity.
Experimental data on two artificial single point mutations (S129A and S129W) of the α-synuclein protein, compared to the wild-type. The dataset includes results from Circular Dichroism and Raman spectroscopy for secondary structure, Thioflavin T assays and atomic force microscopy for aggregation kinetics, and cytotoxicity tests on SH-SY5Y neuronal cell lines. It was authored by Esha Pandit and last updated on 2026-06-03.