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Stereoisomerism

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A photonic crystal fiber-based fluorescence sensor for simultaneous and sensitive detection of lactic acid enantiomers.

Analytical and bioanalytical chemistry
A photonic crystal fiber (PCF)-based fluorescence sensor is developed for rapid and sensitive detection of lactic acid (LA) enantiomers in serum samples. The sensor is fabricated by chemical binding dual enzymes on the inner surface of the PCF with n...

Algorithmic Analysis of Cahn-Ingold-Prelog Rules of Stereochemistry: Proposals for Revised Rules and a Guide for Machine Implementation.

Journal of chemical information and modeling
The most recent version of the Cahn-Ingold-Prelog rules for the determination of stereodescriptors as described in Nomenclature of Organic Chemistry: IUPAC Recommendations and Preferred Names 2013 (the "Blue Book"; Favre and Powell. Royal Society of ...

A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes.

Scientific reports
Directed evolution is an important research activity in synthetic biology and biotechnology. Numerous reports describe the application of tedious mutation/screening cycles for the improvement of proteins. Recently, knowledge-based approaches have fac...

Design of Natural-Product-Inspired Multitarget Ligands by Machine Learning.

ChemMedChem
A virtual screening protocol based on machine learning models was used to identify mimetics of the natural product (-)-galantamine. This fully automated approach identified eight compounds with bioactivities on at least one of the macromolecular targ...

Cautionary Guidelines for Machine Learning Studies with Combinatorial Datasets.

ACS combinatorial science
Regression modeling is becoming increasingly prevalent in organic chemistry as a tool for reaction outcome prediction and mechanistic interrogation. Frequently, to acquire the requisite amount of data for such studies, researchers employ combinatoria...

Machine Learning Classification of One-Chiral-Center Organic Molecules According to Optical Rotation.

Journal of chemical information and modeling
In this study, machine learning algorithms were investigated for the classification of organic molecules with one carbon chiral center according to the sign of optical rotation. Diverse heterogeneous data sets comprising up to 13,080 compounds and th...

Leveraging Machine Learning for Enantioselective Catalysis: From Dream to Reality.

Chimia
Catalyst optimization for enantioselective transformations has traditionally relied on empirical evaluation of catalyst properties. Although this approach has been successful in the past it is intrinsically limited and inefficient. To address this pr...

Artificial neural networks to model the enantioresolution of structurally unrelated neutral and basic compounds with cellulose tris(3,5-dimethylphenylcarbamate) chiral stationary phase and aqueous-acetonitrile mobile phases.

Journal of chromatography. A
Artificial neural networks (ANN; feed-forward mode) are used to quantitatively estimate the enantioresolution (Rs) in cellulose tris(3,5-dimethylphenylcarbamate) of chiral molecules from their structural information. To the best of our knowledge, for...