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Drug-target interaction, molecular screening, ADMET, compound databases, pharmaceutical data
626 datasets
A dataset of 1150 compounds used to develop and validate machine learning models for predicting acute oral toxicity across six drug scaffolds. The models, including QSAR, q-RASAR, and deep learning methods, were applied to virtually screen over 23,000 untested molecules. The work was authored by Jianing Xu and last updated on June 2, 2026.
A dataset for training models to detect toxic comments in Russian. It supports multilabel classification where a single text can belong to multiple toxicity categories simultaneously. The dataset was created by Gloomreach and was last updated on July 16, 2026.
Franziska Thomas presents a protocol for introducing amines into peptides via an on-resin iodination-substitution approach. The method is compatible with primary and secondary amines, anilines, and heteroaromatic N-nucleophiles, yielding good to excellent results. As a proof-of-concept, the metal ligand tris(2-aminoethyl)amine was introduced into a tryptophan zipper scaffold, resulting in a thermal stabilization of more than 30 K.
F1ow421 aggregated and cleaned Russian-language comments from various social platforms and annotated corpora. The dataset is labeled for three independent toxicity classes: profanity, threat, and illegal content. It was last updated on the platform in July 2026.
Data Sheet 1 contains compiled public data on the binding affinity and functional potency of synthetic cannabinoid receptor agonists at the cannabinoid 1 receptor (CB1). The dataset was used to train machine learning models with molecular descriptors and fingerprints, achieving high performance metrics. It was authored by Verena Schöning and last updated on 2026-05-20.
A 26.1 KB Excel file published on figshare under a CC-BY-4.0 license by Giulia Palladino, last updated June 1, 2026. The dataset likely contains information related to multiplexed, barcoded assays for measuring G protein-coupled receptor (GPCR) activities in living cells, as described in an accompanying review article.
A 40.9 KB Excel file authored by Giulia Palladino, summarizing multiplexed assays for G protein-coupled receptors. The review highlights tools for screening GPCR-modulating compounds in living cells, published under a CC-BY-4.0 license. Last updated on June 1, 2026, the dataset likely contains tabular data supporting the review's analysis.
16.6 KB Excel file from a 2026 figshare upload by Tongfei Wang. The dataset likely contains results from a multi-method study investigating the anticancer role of celecoxib. The research combined in vitro assays, network pharmacology, and Mendelian randomization analyses to explore immune-related mechanisms.
A 31.7 KB Excel file contains results from a study investigating the anticancer role of celecoxib. The dataset likely includes statistical outputs from Mendelian randomization analyses, in vitro assay results, and network pharmacology findings. The data was authored by Tongfei Wang and last updated in May 2026.
A 709.1 KB Excel dataset presents results from a multi-method study investigating celecoxib's anticancer role against cervical cancer. The research combines in vitro assays, network pharmacology, and Mendelian randomization analyses to identify causal relationships and immune-related mechanisms. The dataset was authored by Tongfei Wang and last updated on May 19, 2026.
A 756.4 KB Excel file contains results from a study investigating the anticancer role of celecoxib. The research combined in vitro assays, network pharmacology, and Mendelian randomization analyses to identify mechanisms. The dataset was authored by Tongfei Wang and last updated on May 19, 2026.
A May 2026 dataset by Tongfei Wang presents results from a multi-method study investigating the anticancer role of celecoxib. The data likely contains results from in vitro assays, network pharmacology, and Mendelian randomization analyses linking NEU1 inhibition to cervical cancer risk. The dataset is licensed under CC-BY-4.0 and hosted on figshare.
A 13.6 KB Excel file published on figshare in May 2026 by Tongfei Wang. It presents results from a study integrating in vitro experiments, network pharmacology, and Mendelian randomization to investigate the anticancer role of celecoxib against cervical cancer and its immune-related mechanisms.
Tongfei Wang published a pharmacological study on figshare in May 2026. The dataset integrates in vitro experiments, network pharmacology, and Mendelian randomization analyses to explore the anticancer role of celecoxib against cervical cancer. It includes results on cell proliferation inhibition and causal inference linking NEU1 inhibition to reduced cancer risk.
A May 2026 dataset by Tongfei Wang presents results from a multi-method study investigating the anticancer role of celecoxib. The data likely contains results from in vitro assays, network pharmacology, and Mendelian randomization analyses linking NEU1 inhibition to cervical cancer risk. The dataset is licensed under CC-BY-4.0 and hosted on figshare.
A 2026 study by Wen-wei Gong presents data from a network pharmacology and molecular docking analysis of the natural compound shikonin against renal cell carcinoma. The dataset includes 374 shikonin targets, 1,087 RCC-related targets, and 98 overlapping genes, with validation from in vitro cellular experiments. It was published on figshare under a CC-BY-4.0 license.
KinoPotok Support Toxicity Dataset is designed for training and testing systems for automatic filtering and moderation of messages in the support chat of the online cinema "KinoPotok". The dataset was created by author fdlvaaa and was last updated on July 15, 2026.
A dataset of 306 patients with stage II/III colorectal cancer receiving oxaliplatin-based adjuvant chemotherapy, used to develop a predictive nomogram for severe chemotherapy-induced toxicity. The data includes baseline Systemic Immune-Inflammation Index (SII) and Prognostic Nutritional Index (PNI) values, patient age, and outcomes including grade 3–4 adverse events and therapy duration. The dataset was created by Wenjing Li and last updated on May 11, 2026.
A toxicological study presents data on the effects of iron oxide nanoparticles (NP Fe2O3). The research includes physicochemical characterization, cell viability assays using different cell lines, genotoxicity evaluations via the Allium cepa test and comet assay, and oxidative stress analyses in Danio rerio. The dataset likely contains results from these experiments, such as nanoparticle size (65.55 nm), polydispersity index (0.24), zeta potential (11.4 mV), and toxicity measurements across various concentrations.
A dataset from paperswithcode presents electrochemical and cytotoxicity data for eleven synthetic 3-thio-substituted-nor-beta-lapachone derivatives. The data includes first wave reduction potentials and cytotoxic activity against several cancer cell lines and one normal cell, with four compounds being novel. Author Yen G. de Paiva contributed this research, which investigates the relationship between electrochemical parameters and anti-cancer activity.