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Drug-target interaction, molecular screening, ADMET, compound databases, pharmaceutical data
627 datasets
A dataset measuring the antiviral activity and cytotoxicity of benzamide series compounds. The data, published by Donghoon Chung under a CC-BY-4.0 license, is stored in a 5.5 KB XLS file. It was last updated on April 3, -2026.
1,397 compounds, primarily FDA-approved small molecule drugs, are screened for one or more types of activity against various biological targets. The dataset is provided by EvE Bio and is actively generated, with new target data added every other month. Results include measurements such as agonism and antagonism for drug-target interactions.
Additional computational data supporting a publication on machine learning–enabled virtual screening. The data includes docking poses, key structures from clustered molecular dynamics simulation frames, and protein apo geometries. It was authored by John Trant and last updated on May 16, 2026.
Benjamin Long published a dataset on figshare in April 2026 supporting a study on pharmaceuticals in a freshwater terminal lake. The data concerns Lake Colac in Victoria, Australia, tracing pharmaceutical concentrations in surface water and biota. It includes R files for analysis of spatiotemporal dynamics, risk assessment, and trophic fate.
Training, validation, and testing data support the research paper "3D Structural Analysis of Plasmodium Falciparum to Detect Inhibitors." The dataset, authored by Arham Wasti and hosted on Harvard Dataverse, is intended for applying machine learning to malaria drug discovery. It was last updated on April 25, 2026.
The AI3 Protein-Ligand Binding Affinity Dataset was created by teams from IIIT Hyderabad, Intel, AWS, and Insilico Medicine. It contains physics-based calculations on approximately 20,000 protein-ligand complexes, including molecular dynamics snapshots and binding affinities calculated via the MM-PBSA method. The dataset provides 3D coordinates and CSV files with energy components like electrostatic and van der Waals interactions.
Laboratory studies determined the 96-hour lethal concentration (LC50) for 13 chemicals on juvenile rainbow trout. The dataset includes toxicity rankings for three ammonia-based fire retardants, five surfactant-based foams, three nitrogenous chemicals, and two anionic surfactants. The study was conducted by the CEOS_EXTRA organization.
A preclinical toxicity study of the empty P2 poly(2-oxazoline) block copolymer in Rhesus Macaques. The dataset includes results from low-dose (30 mg/kg) and high-dose (90 mg/kg) trials conducted in July 2023 and January 2025, respectively, on four named subjects. The data was authored by Jacob Ramsey and last updated in April 2026.
13,572 molecules across four diseases form this preprocessed dataset for drug discovery. It appears to be derived from the NTD (Neglected Tropical Diseases) dataset and has been processed using an LLM-based pipeline. The specific source, license, and update date are not provided.
Raw data from a study measuring the effects of environmentally relevant microplastics on earthworms (Eisenia fetida). The dataset includes measurements of ingestion, survival, reproduction, and avoidance responses across common polymer types. Author Ryan Prosser contributed the data to the Borealis Harvested Dataverse, with a last update recorded on 2026-04-25.
The Cell Painting Gallery is a collection of image datasets created using the Cell Painting assay. Images of cells are captured by microscopy to reveal the response of labeled cell components to treatments like genetic perturbations, chemicals, or drugs. The collection is maintained by the Carpenter–Singh and Cimini labs at the Broad Institute.
5.5 KB XLS file contains computational docking scores comparing a novel compound DdpMPyPEPhU against FDA-approved drugs Lapatinib and Tamoxifen. The dataset includes metrics like Binding Affinity, MM-GBSA, and RMSD for three protein receptors: CDK2, ER-α, and GR. Authored by Shaban Ahmad and last updated in March 2026, it is shared under a CC BY 4.0 license.
A dataset containing pIC50 values for compounds acting as carbonic anhydrase inhibitors. The data was published on Kaggle, but the author, organization, and collection date are unknown. The specific number of compounds, features, and data source are not provided in the available metadata.
The National Ocean Service collected sediment toxicity data from multiple U.S. coastal regions between March 18, 1991 and March 3, 1993 as part of the National Status and Trends program. Data includes results from three laboratory toxicity tests performed on surficial fine-grained sediments: a 10-day amphipod survival test, a 48-hour clam larvae test, and a 15-minute bacterial bioluminescence test. The study aimed to assess the spatial extent and severity of toxicity in estuaries like the Hudson-Raritan Estuary and Tampa Bay.
Experimental data compares copper uptake and physiological responses in two marine fish species, the clear nosed skate (Raja erinacea) and the sculpin (Myoxocephalus octodecemspinosus), during controlled exposure to elevated water-borne copper for up to seven days. The study was conducted by SCIOPS, measuring gill copper concentrations, plasma ammonia levels, and Na+/K+-ATPase activity across multiple tissues. It investigates osmoregulatory disturbance as a primary toxic mechanism of copper in marine elasmobranchs and teleosts.
A dataset by Raúl Acosta-Murillo, last updated in March 2026, comparing the performance of different chemical representations for predicting pIC50 values. The 5.5 KB Excel file contains coefficient of determination (R²) and Root Mean Square Error (RMSE) values, with the highest-performing representation indicated in bold. The dataset's specific row count and column details are not provided in the metadata.
Fifteen novel anticancer peptide sequences were generated by artificial intelligence. The dataset provides calculated physicochemical properties and bioactivity scores for each sequence. Binyu Li authored this resource, which was last updated in March 2026.
Additional file 8 from a study on the network pharmacology and computational dissection of Solanum trilobatum bioactives. The 65 KB XLSX file likely contains results from molecular docking and simulation analyses targeting steroid receptor-associated signaling in breast cancer. Its cross-platform presence on figshare suggests it is a core supplementary dataset for the published research.
An 82 KB Excel file contains computational results from a network pharmacology and molecular docking study of Solanum trilobatum bioactives against breast cancer steroid receptors. The dataset is associated with a research article investigating the modulation of steroid receptor-associated signaling pathways. Its specific contents, likely including compound-receptor interaction scores or network node data, require verification after download.
30711 bytes of computational data support a network pharmacology study of Solanum trilobatum compounds targeting steroid receptor signaling in breast cancer. The dataset, likely containing molecular docking scores and network analysis results, is associated with a published research article. Its columns suggest details on bioactive compounds, protein targets, and interaction metrics.