Statistical Analysis and Compound Selection of Combinatorial Libraries for Soluble Epoxide Hydrolase
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Summary
This study illustrates that the balanced approach by G-SELC could provide a general method for combinatorial library design, to effectively identify promising compounds to be created in the laboratory.
- Type
- article
- Published
- 2011-06-20
- Cited by
- 6
- References
- 22
- OpenAlex
- https://openalex.org/W21615155
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:5223834
Keywords
Gray (unit), Queer, Art, Philosophy, Humanities
References
- Efficient Global Optimization of Expensive Black-Box Functions
- Applications of rule-induction in the derivation of quantitative structure-activity relationships
- G-SELC: Optimization by sequential elimination of level combinations using genetic algorithms and Gaussian processes
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- Novel Inhibitors of Human Histone Deacetylase (HDAC) Identified by QSAR Modeling of Known Inhibitors, Virtual Screening, and Experimental Validation
- Discovery of potent inhibitors of soluble epoxide hydrolase by combinatorial library design and structure-based virtual screening.
- Application of predictive QSAR models to database mining: identification and experimental validation of novel anticonvulsant compounds.
- Consensus Ranking Approach to Understanding the Underlying Mechanism With QSAR
- Structure-directed combinatorial library design.
- Application of validated QSAR models of D1 dopaminergic antagonists for database mining.
- QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.
- Stochastic gradient boosting
- A Novel Automated Lazy Learning QSAR (ALL-QSAR) Approach: Method Development, Applications, and Virtual Screening of Chemical Databases Using Validated ALL-QSAR Models
- Beware of q2!
- Development of CYP3A4 Inhibition Models: Comparisons of Machine-Learning Techniques and Molecular Descriptors
- Multivariate adaptive regression splines
- Soluble epoxide hydrolase inhibition reveals novel biological functions of epoxyeicosatrienoic acids (EETs).
- Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis
- Identifying Promising Compounds in Drug Discovery: Genetic Algorithms and Some New Statistical Techniques
Cited by
- Structural insights into binding of inhibitors to soluble epoxide hydrolase gained by fragment screening and X-ray crystallography.
- Predicting the binding modes and sites of metabolism of xenobiotics.
- A rapid identification of hit molecules for target proteins via physico-chemical descriptors.
- Predicting the DPP-IV Inhibitory Activity pIC50 Based on Their Physicochemical Properties
- Identification of N-ethylmethylamine as a novel scaffold for inhibitors of soluble epoxide hydrolase by crystallographic fragment screening.
- A random forest model to predict the activity of a large set of soluble epoxide hydrolase inhibitors solely based on a set of simple fragmental descriptors.
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