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Drug-target interaction, molecular screening, ADMET, compound databases, pharmaceutical data
627 datasets
8,453 food compounds were screened using a QSAR model to predict their bioactivity against the BACE1 enzyme, a target for Alzheimer's disease. The dataset, authored by Nobendu Mukerjee and updated in May 2026, includes predicted pKi values and identifies a top candidate molecule. It was generated through ligand-based and target-based drug design approaches, including virtual screening and molecular docking.
A dataset of 8,453 food-derived molecules screened for potential inhibitory activity against the BACE1 enzyme, a target for Alzheimer's disease therapy. The data was generated by Nobendu Mukerjee using a QSAR model built from 552 molecules and virtual screening of a larger food compound database, with results last updated in May 2026. It includes predicted binding affinity (pKi) values and identifies a top candidate molecule.
A scoping review synthesizing preclinical and clinical evidence on the gonadotoxic effects of the drug imatinib in males. The review, authored by Xia Ji and published on figshare in 2026, includes 20 studies published between 2003 and 2025. It examines mechanisms, dose- and age-dependent susceptibility, and the reversibility of testicular injury.
16 active components and 499 targets of the Coptis-Cinnamon (HL-RG) pair were identified, intersecting with 55 common targets from 3,194 gastric cancer-related genes. The research, authored by Zhao-zhao Wang and uploaded to figshare in May 2026, includes molecular docking, enrichment analyses, and in vitro experiments on AGS and HGC-27 cells. Results indicate the herbal pair inhibits gastric cancer cell proliferation, migration, and invasion via the MAPK/ERK pathway.
Dong-Yuan Ning published data on a novel tetrahydro-β-carboline-derived Mcl-1 inhibitor, designated N5, on figshare in May 2026. The dataset likely contains experimental results for the compound N5 and its hydrochloride N5Y, including binding affinity, selectivity, ADMET properties, and in vivo efficacy. The data describes a compound with antitumor activity and capability to overcome cisplatin resistance in ovarian cancer models.
Mean triacylglyceride values calculated from three biological replicates for wild-type N2 control and drug-treated C. elegans, including data for the eat-2 mutant treated with triple combinations. The dataset was contributed by author Tesfahun Dessale Admasu and is available via the paperswithcode platform. TAG values are summarized based on fatty acid chain length as medium-chain and long-chain acyl groups.
Four butyl nitrites were found to be moderately toxic compounds in mice, with toxicity varying by administration route. The study, authored by R.P. Maickel of Purdue University West Lafayette, identified TBN as the least toxic and least potent in producing methemoglobinemia. The dataset likely contains tabular results from this pharmacological and toxicological investigation.
Huda Fayez Al-Rashedi published this dataset on figshare in May 2026. It contains results from a study on whey protein concentrate's protective effects against chemically induced intestinal damage in male albino rats. The 25.5 KB Excel file includes data from molecular docking simulations and in vivo measurements of oxidative stress, inflammation, apoptosis, and fibrosis markers.
A research article analyzes a series of oligothiophene-extended Ru(II) polypyridyl complexes (Ru(6,6′-dmb)₂(IP-nT), n=0–4). The study, authored by Alisher Talgatov and published on figshare in 2026, uses spectroscopy, computation, photochemistry, and photobiology to examine how ligand structure modulates excited-state pathways and biological activity. It investigates phototherapeutic responses across mammalian cancer cells and bacterial strains under normoxic and hypoxic conditions.
A 13.2 MB Excel file contains cytotoxicity data for 16 rare earth ions, developed by Yaqi Wang and last updated in May 2026. The framework integrates single and binary exposure data across eight human cell lines with machine learning models for mixture toxicity prediction. Application of the model to human exposure scenarios showed high risks for populations in mining areas.
16 rare earth ions were screened for cytotoxicity across eight human cell lines, including single and 120 binary mixture exposures. The dataset, created by Yaqi Wang and last updated in May 2026, underpins a framework using machine learning to predict mixture toxicity and assess population risk. It includes high-throughput screening results identifying ATP depletion as a key benchmark.
Alexander Engstrom published a dataset on figshare in May 2026 detailing a method for measuring membrane permeability of PROTACs and E3 ligase ligands. The data likely contains quantitative permeability rates measured using NanoBRET live-cell target engagement, comparing results to traditional transwell assays. It focuses on BET-targeting degraders with subtle structural changes.
16.6 KB of attribution data from four explainable AI methods applied to graph neural network models for drug-target interaction prediction. The dataset, created by Mrinal Mahindran and last updated in April 2026, benchmarks methods on kinase and G-protein-coupled receptor targets, mapping attributed ligand atoms to 3D protein structures. Consensus attributions were highly enriched for atoms contacting the binding pocket, with up to 76% within 2 Å in kinase-inhibitor complexes.
Mrinal Mahindran's dataset, last updated April 15, 2026, benchmarks four explainable AI attribution methods on graph neural network models for drug-target interaction prediction. The data likely contains atom-level attribution results for kinase and G-protein-coupled receptor targets, validated against 3D protein-ligand structures. The dataset is 63.5 KB in size and is stored in CSV format.
Mrinal Mahindran's dataset benchmarks four explainable AI attribution methods on graph neural network models for drug-target interactions. The data, last updated in April 2026, includes validation of biological relevance by mapping attributed ligand atoms to 3D protein-ligand structures. It focuses on kinase and G-protein-coupled receptor targets.
A benchmark dataset for four explainable AI attribution methods applied to graph neural network models predicting drug-target interactions. The data was created by Mrinal Mahindran and last updated in April 2026, focusing on kinase and G-protein-coupled receptor targets. It includes validation metrics like atom-level intersection over union and mappings to 3D protein-ligand structures.
MarineTox Predictor is an online library platform containing 1.2 million records of predicted ecotoxicity data and derived environmental hazard thresholds. The dataset was developed by Yongle Zhu using multitask deep learning to predict 31 saltwater toxicity endpoints for 26 marine organisms, sharing knowledge from freshwater ecotoxicity data. It was last updated on 2026-04-21.
A 2026 study by Yongmin Jung evaluates the synergistic toxicity of triclosan and co-occurring chemicals found in household cleaning products. It includes cytotoxicity testing on four human cell lines and mixture modeling to calculate model deviation ratios. The dataset, shared on figshare, provides regulatory insights for consumer chemical management.
A pharmacology dataset from figshare, authored by Alexander A. Kirichok and last updated in May 2026. It contains data on the synthesis and testing of spirocyclic analogues of the local anesthetic bupivacaine. The study measured lethal doses, local anesthetic efficacy in mice, and cardiotoxicity in guinea pig hearts.
202,716 unique small molecules designed to target the Mpox virus VP39 methyltransferase protein. The dataset was generated using deep reinforcement learning and published by Irina Tirosyan on figshare in April 2026. It includes annotations for docking scores, physicochemical properties, ADMET predictions, and synthetic accessibility.