ArticleBioorganic & medicinal chemistry2019
Predictive models of aqueous solubility of organic compounds built on A large dataset of high integrity.
Article in Bioorganic & medicinal chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
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- SAR Studies around the SULT1A1-Activated Alkylator YC-1 as Cytotoxic Agents against Biliary Tract Cancer Cells.Journal of medicinal chemistry · 2025Article
- Transformation of a Potent C9-Substituted Phenylmorphan into MOR Partial Agonists with Improvement of Metabolic Stability: An In Vitro, In Vivo, and In Silico Study.ACS chemical neuroscience · 2025Article
- Targeting c-MYC and gain-of-function p53 through inhibition or degradation of the kinase LZK suppresses the growth of HNSCC tumors.Science signaling · 2025Article
- Targeting GOF p53 and c-MYC through LZK Inhibition or Degradation Suppresses Head and Neck Tumor Growth.bioRxiv : the preprint server for biology · 2024Article
- Amidino-rocaglates (ADRs), a class of synthetic rocaglates, are potent inhibitors of SARS-CoV-2 replication through inhibition of viral protein synthesis.Antiviral research · 2024Article
- Understanding predictions of drug profiles using explainable machine learning models.BioData mining · 2024Article
- Small-Molecule Disruptors of the Interaction between Calcium- and Integrin-Binding Protein 1 and Integrin αACS pharmacology & translational science · 2024Article
- In vitro and in vivo pharmacokinetic characterization, chiral conversion and PBPK scaling towards human PK simulation of S-MRI-1867, a drug candidate for Hermansky-Pudlak syndrome pulmonary fibrosis.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2023Article
- The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery.Pharmaceutics · 2023Review
- Use of physiological based pharmacokinetic modeling for cross-species prediction of pharmacokinetic and tissue distribution profiles of a novel niclosamide prodrug.Frontiers in pharmacology · 2023Article
- Retro Drug Design: From Target Properties to Molecular Structures.Journal of chemical information and modeling · 2022Review
- Using in vitro ADME data for lead compound selection: An emphasis on PAMPA pH 5 permeability and oral bioavailability.Bioorganic & medicinal chemistry · 2022Review
- Preclinical Pharmacokinetics andFrontiers in pharmacology · 2022Article
- HybridACS pharmacology & translational science · 2021Article
- Structure-Based Optimization of Small Molecule Human Galactokinase Inhibitors.Journal of medicinal chemistry · 2021Article
- Small Molecule Inhibitors of Activation-Induced Deaminase Decrease Class Switch Recombination in B Cells.ACS pharmacology & translational science · 2021Article
- Application of niclosamide and analogs as small molecule inhibitors of Zika virus and SARS-CoV-2 infection.Bioorganic & medicinal chemistry letters · 2021Article
- Retro Drug Design: From Target Properties to Molecular Structures.bioRxiv : the preprint server for biology · 2021Article
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8 authors.
Funding
Abstract
Aqueous solubility is one of the most important properties in drug discovery, as it has profound impact on various drug properties, including biological activity, pharmacokinetics (PK), toxicity, and in vivo efficacy. Both kinetic and thermodynamic solubilities are determined during different stages of drug discovery and development. Since kinetic solubility is more relevant in preclinical drug discovery research, especially during the structure optimization process, we have developed predictive models for kinetic solubility with in-house data generated from 11,780 compounds collected from over 200 NCATS intramural research projects. This represents one of the largest kinetic solubility datasets of high quality and integrity. Based on the customized atom type descriptors, the support vector classification (SVC) models were trained on 80% of the whole dataset, and exhibited high predictive performance for estimating the solubility of the remaining 20% compounds within the test set. The values of the area under the receiver operating characteristic curve (AUC-ROC) for the compounds in the test sets reached 0.93 and 0.91, when the threshold for insoluble compounds was set to 10 and 50 μg/mL respectively. The predictive models of aqueous solubility can be used to identify insoluble compounds in drug discovery pipeline, provide design ideas for improving solubility by analyzing the atom types associated with poor solubility and prioritize compound libraries to be purchased or synthesized.
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