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Organic/inorganic chemistry, analytical chemistry, electrochemistry, molecular properties, chemical reactions
2,028 datasets
112.8 MB of computational chemistry data for analyzing complex polycyclic products from vinyl-substituted arene and benzyne reactions. The dataset, authored by Thomas Hoye and last updated in June 2026, likely contains structures for Gaussian DFT computations and DP4+ NMR analyses. These reactions can form as many as five new rings and include unexpected modes of reactivity like ene reactions and [2+2] cycloadditions.
Aditi Roy's dataset from 2026 contains results from a computational screening study targeting TEM β-lactamase enzymes in Escherichia coli. The data includes evaluations of 3576 antibacterial compounds, with 55 shortlisted for virtual screening based on drug-likeness and non-toxicity. It features molecular docking scores, molecular dynamics simulation results, and density functional theory analyses for a lead compound identified as 344,265.
3576 antibacterial compounds were screened for drug-like properties to find potential inhibitors of TEM beta-lactamase enzymes in Escherichia coli. Aditi Roy published the results on figshare in May 2026, listing 55 shortlisted compounds with molecular docking, dynamics, and density functional theory analysis. The dataset highlights compound 344,265 as a promising lead with high binding affinities to TEM-1 and TEM-235.
3576 antibacterial compounds were evaluated for drug-like properties to find inhibitors for TEM beta-lactamase enzymes in E. coli. Aditi Roy published the results on figshare in May 2026, identifying a lead compound with high binding affinity. The dataset likely contains the shortlisted 55 compounds and their associated computational analysis scores.
Aditi Roy published a dataset on 2026-05-20 containing results from a computational drug discovery study targeting TEM beta-lactamase enzymes in Escherichia coli. The data likely includes pharmacokinetic properties and molecular docking scores for 55 antibacterial compounds shortlisted from an initial evaluation of 3576 compounds. The study identifies a lead candidate, compound 344,265, with binding affinities of -8.5 kcal/mol for TEM-1 and -8.4 kcal/mol for TEM-235.
Aditi Roy's dataset from 2026 contains results from a computational screening study targeting TEM β-lactamase enzymes in Escherichia coli. The data includes evaluations of 3576 antibacterial compounds, with 55 shortlisted for virtual screening based on drug-likeness and non-toxicity. It features molecular docking scores, molecular dynamics simulation results, and density functional theory analyses for a lead compound identified as 344,265.
Aditi Roy published a computational screening dataset on 2026-05-20. It contains results from evaluating 3576 antibacterial compounds against TEM β-lactamase enzymes in Escherichia coli. The study shortlisted 55 compounds based on drug-likeness and non-toxicity, with detailed molecular docking, dynamics, and density functional theory analyses for a lead candidate.
Jincong Zhuo published data on the discovery of povorcitinib (INCB054707), an orally bioavailable and isoform-selective Janus kinase 1 (JAK1) inhibitor. The dataset, last updated on 2026-05-27, includes protein crystallography data in PDB format, totaling 175.2 KB. It supports the compound's development for treating inflammatory and autoimmune diseases.
386.2 KB of structural data for the JAK1-selective inhibitor povorcitinib (INCB054707), authored by Jincong Zhuo and last updated in May 2026. The dataset, shared on figshare under a CC-BY-NC-4.0 license, includes protein crystallography information supporting the compound's selectivity and improved pharmacokinetics. It was used to demonstrate dose-dependent efficacy in murine arthritis models.
63 protein-derived peptide fragments and two unknown medium-molecular-weight compounds were identified in plasma samples from hyperlipidemia patients. The dataset was generated by Tomoaki Nitta using a novel capillary electrophoresis–mass spectrometry platform with a 60-fold increased injection volume. It was last updated on 2026-05-27.
A novel analytical platform based on capillary electrophoresis–high-resolution mass spectrometry (CE–HRMS) was developed for metabolomics of medium-molecular-weight compounds (MMWCs). The platform was applied to plasma samples from hyperlipidemia patients, identifying elevated levels of peptides like bradykinin, CLIP, schizophrenia-related peptides, 63 additional peptide fragments, and two unknown MMWCs. The dataset, created by Tomoaki Nitta and last updated on 2026-05-27, is shared under a CC-BY-NC-4.0 license on figshare.
63 protein-derived peptide fragments and two unknown medium-molecular-weight compounds were identified in plasma samples from hyperlipidemia patients. The dataset was generated using a novel capillary electrophoresis–mass spectrometry platform with a 60-fold increased injection volume and detection limits of 10 pg/mL. Tomoaki Nitta authored this dataset, which was last updated on 2026-05-27.
374 compounds from the ChemDiv library were screened to identify a novel inhibitor of AmpC β-lactamase, a key enzyme in multidrug-resistant Pseudomonas aeruginosa. The top candidate, N094-0017, showed a binding energy of -5.6 kcal/mol and favorable pharmacokinetic profiles in SwissADME analysis. This dataset, authored by Santhosh Mudipalli Elavarasu and last updated in May 2026, contains the results of molecular dynamics simulations and free energy perturbation calculations.
A 516.5 KB dataset published by Jun Zhou on 2026-05-27 describes the synthesis and catalytic properties of a novel icosahedral Au13 nanocluster. The cluster is protected by 12 thiolate ligands and stabilized by eight t-butyl ammonium groups, forming a supramolecular assembly. It includes data on its use as a heterogeneous catalyst for aniline oxidative coupling, with captured reaction intermediates confirmed by EPR and DFT.
An AI-driven 6D-grid protein-engineering framework integrated a dataset of 1.39 million structural fragments to predict productive enzyme mutations. Five AI-prioritized variants, each containing nine mutations, were validated at 7 L fermentation scale, achieving up to 89% conversion for sitagliptin synthesis. The dataset, shared by Pravin Kumar R on figshare in May 2026, likely contains the computational and experimental results underpinning this biocatalyst development.
A dataset from 2026 describes an AI-driven protein-engineering framework for biocatalyst development. It likely contains structural and energetic descriptors for enzyme variants, derived from a library of 1.39 million structural fragments. The data was authored by Pravin Kumar R and shared on figshare.
1.39 million structural fragments inform an AI-driven protein-engineering framework for biocatalyst development. The dataset, authored by Pravin Kumar R and last updated in May 2026, details the prediction and validation of productive enzyme substitutions. Five AI-prioritized enzyme variants, each containing nine mutations, were evaluated and scaled to 7 L fermentation.
Pravin Kumar R published a dataset on figshare in 2026 detailing an AI-driven protein-engineering framework. The work describes a dataset of 1.39 million structural fragments used to predict productive enzyme substitutions for biocatalysis. It reports results from evaluating five AI-prioritized enzyme variants for the synthesis of sitagliptin.
1.39 million structural fragments were used to train an AI-driven protein-engineering framework. The dataset, authored by Pravin Kumar R and last updated in May 2026, contains AI-prioritized enzyme variants engineered for the biocatalytic synthesis of sitagliptin. Five variants, each containing nine mutations, were validated at a 7 L fermentation scale.
A dataset from 2026 describes an AI-driven protein-engineering framework for biocatalyst development. It likely contains structural and energetic descriptors for enzyme variants, derived from a library of 1.39 million structural fragments. The data was authored by Pravin Kumar R and shared on figshare.