Prediction on separation factor of chiral arylhydantoin compounds and recognition mechanism between chiral stationary phase and the enantiomers

Intelligent Recommendation Systems Powered by Consensus Neural Networks: The Ultimate Solution for Finding Suitable Chiral Chromatographic Systems?

The selection of suitable combinations of chiral stationary phases (CSPs) and mobile phases (MPs) for the enantioresolution of chiral compounds is a complex issue that often requires considerable experimental effort and can lead to significant waste. Linking the structure of a chiral compound to a CSP/MP system suitable for its enantioseparation can be an effective solution to this problem. In this study, we evaluate algorithmic tools for this purpose. Our proposed consensus model, which uses multiple optimized artificial neural networks (ANNs), shows potential as an intelligent recommendation system (IRS) for ranking chromatographic systems suitable for the enantioresolution of chiral compounds with different molecular structures. To evaluate the IRS potential in a proof-of-concept stage, 56 structural descriptors for 56 structurally unrelated chiral compounds across 14 different families are considered. Chromatographic systems under study comprise 7 cellulose and amylose derivative CSPs and acetonitrile or methanol aqueous MPs (14 chromatographic systems in all). The ANNs are optimized using a fit-for-purpose version of the chaotic neural network algorithm with competitive learning (CCLNNA), a novel approach not previously applied in the chemical domain. CCLNNA is adapted to define the inner ANN complexity and perform feature selection of the structural descriptors. A customized target function evaluates the correctness of recommending the appropriate CSP/MP system. The ANN-consensus model exhibits no advisory failures and requires only an experimental attempt to verify the IRS recommendation for complete enantioresolution. This outstanding performance highlights its potential to effectively resolve this problem.

Update on chiral recognition mechanisms in separation science

The stereospecific analysis of chiral molecules is an important issue in many scientific fields. In separation sciences, this is achieved via the formation of transient diastereomeric complexes between a chiral selector and the selectand enantiomers driven by molecular interactions including electrostatic, ion-dipole, dipole-dipole, van der Waals or π-π interactions as well as hydrogen or halogen bonds depending on the nature of selector and selectand. Nuclear magnetic resonance spectroscopy and molecular modeling methods are currently the most frequently applied techniques to understand the selector-selectand interactions at a molecular level and to draw conclusions on the chiral separation mechanism. The present short review summarizes some of the recent achievements for the understanding of the chiral recognition of the most important chiral selectors combining separation techniques with molecular modeling and/or spectroscopic techniques dating between 2020 and early 2024. The selectors include polysaccharide derivatives, cyclodextrins, macrocyclic glycopeptides, proteins, donor-acceptor type selectors, ion-exchangers, crown ethers, and molecular micelles. The application of chiral ionic liquids and chiral deep eutectic solvents, as well as further selectors, are also briefly addressed. A compilation of all published literature on chiral selectors has not been attempted.

Interface Chirality: From Biological Effects to Biomedical Applications

Chiral surface is a critical mediator that significantly impacts interaction with biological systems on regulating cell behavior. To better understand how the properties of interfacial Chirality affect cell behavior and address the limitations of chiral materials for biomedical applications, in this review, we mainly focus on the recent developments of chiral bio-interfaces for the controllable and accurate guidance of chiral biomedical phenomena. In particular, we will discuss how cells or organisms sense and respond to the chiral stimulus, as well as the chirality mediating cell fate, tissue repair, and organism immune response will be reviewed. In addition, the biological applications of chirality, such as drug delivery, antibacterial, antivirus and antitumor activities, and biological signal detection, will also be reviewed. Finally, the challenges of chiral bio-interfaces for controlling biological response and the further application of interface chirality materials for biomedical will be discussed.

Modelling the enantiorecognition of structurally diverse pharmaceuticals on O-substituted polysaccharide-based stationary phases

This study aims to develop models to predict the retention, separation and elution sequence of the enantiomers of structurally diverse pharmaceuticals. More specifically, Quantitative Structure Retention Relationships (QSRR) models are built that describe the relationship between molecular descriptors and retention. Eighteen structurally diverse chiral mixtures, each consisting of a pair of enantiomers, were analyzed on two polysaccharide chiral stationary phases, Chiralcel OD-RH (cellulose tris(3,5-dimethylphenylcarbamate)) and Lux amylose-2 (amylose tris(5-chloro-2-methylphenylcarbamate)), applying either a basic or an acidic mobile phase, and their retention factor and elution sequence were determined. Both achiral and, in-house defined, chiral descriptors were used as descriptive variables to build the models. Linear regression techniques, i.e. stepwise multiple linear regression (sMLR) and partial least squares (PLS) regression, were applied to model the retention or separation as a function of the descriptors. In a first step, models were built with only achiral descriptors to model the global retention of both enantiomers of a chiral molecule. Subsequently, models were built with only chiral descriptors to predict the enantioseparation and elution sequence, and finally, models were considered with both descriptor types to predict the retention, the separation and the elution sequence of the enantiomers. The global retention was predicted well by the sMLR models with only achiral descriptors. The models with only chiral descriptors were not found suitable to predict the enantioseparation and elution sequence. Finally, the models containing both chiral and achiral descriptors allowed predicting the retention well, but their ability to predict the elution sequence and separation of the enantiomers differed widely for the chromatographic systems considered.

Electronic structure and second-order nonlinear optical properties of linear [3]spirobifluorenylene compounds

The nonlinear optical property of the studied compounds were studied with the aid of the DFT calculations.