MolGraph: a Python package for the implementation of molecular graphs and graph neural networks with TensorFlow and Keras

Molecular machine learning (ML) has proven important for tackling various molecular problems, such as predicting molecular properties based on molecular descriptors or fingerprints. Since relatively recently, graph neural network (GNN) algorithms have been implemented for molecular ML, showing comparable or superior performance to descriptor or fingerprint-based approaches. Although various tools and packages exist to apply GNNs in molecular ML, a new GNN package, named MolGraph, was developed in this work with the motivation to create GNN model pipelines highly compatible with the TensorFlow and Keras application programming interface (API). MolGraph also implements a chemistry module to accommodate the generation of small molecular graphs, which can be passed to a GNN algorithm to solve a molecular ML problem. To validate the GNNs, they were benchmarked against the datasets of MoleculeNet, as well as three chromatographic retention time datasets. The results on these benchmarks illustrate that the GNNs performed as expected. Additionally, the GNNs proved useful for molecular identification and improved interpretability of chromatographic retention time data. MolGraph is available at https://github.com/akensert/molgraph. Installation, tutorials and implementation details can be found at https://molgraph.readthedocs.io/en/latest/.Comment: 14 pages, 4 figures, 4 table

Development of liquid chromatography methods coupled to mass spectrometry for the analysis of substances with a wide variety of polarity in meconium.

International audienceMeconium is the first fecal excretion of newborns. This complex accumulative matrix allows assessing the exposure of the fetus to xenobiotics during the last 6 months of pregnancy. To determine the eventual effect of fetal exposure to micropollutants in this matrix, robust and sensitive analytical methods must be developed. This article describes the method development of liquid chromatography methods coupled to triple quadrupole mass spectrometry for relevant pollutants. The 28 selected target compounds had different physico-chemical properties from very polar (glyphosate) to non-polar molecules (pyrethroids). Tests were performed with three different types of columns: reversed phase, ion exchange and HILIC. As a unique method could not be determined for the simultaneous analysis of all compounds, three columns were selected and suitable chromatographic methods were optimized. Similar results were noticed for the separation of the target compounds dissolved in either meconium extract or solvent for reversed phase and ion exchange columns. However, for HILIC, the matrix had a significant influence on the peak shape and robustness of the method. Finally, the analytical methods were applied to “real” meconium samples

Novel approaches to coupling orthogonal separation mechanisms in pharmaceutical and environmental ultra-high performance liquid chromatography analysis

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Current and Future Chromatographic Columns: Is One Column Enough to Rule Them All?

The vast majority of separations in liquid chromatography (LC) still use the typical packed particle bed format, most commonly with fully or superficially porous particles in particle sizes as low as 1.3 µm. As an alternative, monolithic columns have been the topic of many studies, but they are currently used only in some niche applications. Research into perfectly ordered microfabricated columns has shown tremendous possibility for these high performance columns for use in nano-LC, but their development is still ongoing. The possibilities that emerging three-dimensional (3D) printing technology offers make it theoretically possible to develop any imaginable structure with high precision, but the technology is currently limited. This article provides a critical review of all these technologies and demonstrates how further development of chromatographic columns will be of paramount importance in the future.status: publishe

Relevance and Assessment of Molecular Diffusion Coefficients in Liquid Chromatography

© 2016, Springer-Verlag Berlin Heidelberg. Molecular diffusion plays an important role in high-performance liquid chromatography, especially in fundamental column performance studies. An accurate knowledge of the molecular diffusion coefficients (Dm) of compounds selected for column evaluation is therefore crucial. In this review, a general overview is presented of the advantages and drawbacks of correlation-based and experimental methods that can be employed to determine molecular diffusion coefficients. The former include the Wilke–Chang, Scheibel, Reddy–Doraiswamy, Lusis–Ratcliff and Hayduk–Laudie equations, and other empirical correlations based on the Wilke–Chang equation. It is discussed how the association factor (ψ) that is required in several of these correlations can be obtained from the solubility parameter (δ). Frequently used experimental methods include the light scattering, nuclear magnetic resonance, peak parking and Taylor–Aris method, and methods employing microfluidic devices. The principles of these experimental methods are elucidated in detail. Moreover, the influence of several parameters, such as solute characteristics, solvent viscosity, temperature and pressure on the molecular diffusion coefficient is described.status: publishe

Current developments in LC-MS for pharmaceutical analysis

Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades. Continuous improvements in mass spectrometry and interface technologies, combined with advanced liquid chromatographic techniques for high-throughput qualitative and quantitative analysis, have resulted in a wider scope of applications in the pharmaceutical field. LC-MS tools are increasingly used to analyze pharmaceuticals across a variety of stages in their discovery and development. These stages include drug discovery, product characterization, metabolism studies (in vitro and in vivo) and the identification of impurities and degradation products. The increase in LC-MS applications has been enormous, with retention times and molecular weights (and related fragmentation patterns) emerging as crucial analytical features in the drug development process. The goal of this review is to give an overview of the main developments in LC-MS based techniques for the analysis of small pharmaceutical molecules in the last decade and give a perspective on future trends in LC-MS in the pharmaceutical field.status: publishe

Graphical Data Representation Methods To Assess The Quality of LC Columns

We discuss the most important plot types for the kinetic performance of liquid chromatography systems and elaborate on how these plots should best be constructed and can be made dimensionless. Distinction is made between plots that are most suited for practitioners (column users) versus those most suited for theoreticians and column manufacturers.status: publishe

Assessment of intra-particle diffusion in hydrophilic interaction liquid chromatography and reversed-phase liquid chromatography under conditions of identical packing structure

A recently developed stripping protocol to completely remove the stationary phase of reversed-phase liquid chromatography (RPLC) columns and turn them into hydrophilic interaction liquid chromatography (HILIC) columns with identical packing characteristics is used to study the underlying mechanisms of intra-particle diffusion in RPLC and HILIC. The protocol is applied to a column with a large geometrical volume (250×4.6mm, 5μm) to avoid extra-column effects and for compounds with a broad range in retention factors (k" from ∼0.6 to 8). Three types of behavior for the intra-particle diffusion (Dpart/Dm) in RPLC versus HILIC can be distinguished: for nearly unretained compounds (k"1.8), intra-particle diffusion in RPLC is larger than in HILIC. To explain these observations, diffusion in the stationary phase (γsDs) and in the stagnant mobile phase in the mesopore zone (γmpDm) are deduced from experimentally determined values of the intra-particle diffusion, using models derived from the Effective Medium Theory. It is demonstrated that the larger intra-particle diffusion obtained for slightly retained compounds under HILIC conditions is caused by the higher mesopore diffusion in HILIC (γmp=0.474 for HILIC versus 0.435 for RPLC), while the larger intra-particle diffusion obtained for strongly retained compounds under RPLC conditions can be related to the much higher stationary phase diffusion in RPLC (γsDs/Dm=0.200 for RPLC versus 0.113 for HILIC).status: publishe

Efficiency and mechanism of diclofenac degradation by sulfite/UV advanced reduction processes (ARPs)

Diclofenac (DCF) is a non-steroidal anti-inflammatory drug which is frequently detected in the aqueous environment. The synergistic treatment using sulfite and UV irradiation is proposed to be one of the most effective advanced reduction processes (ARPs) to degrade refractory contaminants. This paper systematically investigated the performance and mechanism of DCF degradation by sulfite/UV ARP under various conditions. A significant enhancement in degradation efficiency of DCF was exhibited via sulfite/UV ARP compared with direct UV photolysis, which is primarily due to the generation of reductive radicals (eaq- and H). This process was well described by a pseudo first-order kinetic model with a rate constant of 0.154 min-1. The influence of solution pH, sulfite dosage, initial DCF concentration and UV intensity were evaluated. Results revealed that DCF more favorably reacted with H in an acidic environment than with eaq- under alkaline conditions. A positive impact on the DCF decomposition was observed with increasing sulfite dosage, but with an inhibiting trend at high sulfite concentrations. The degradation rate constant was accelerated by increasing the UV intensity, while decreased by promoting the initial DCF concentration. Degradation mechanisms at different pH levels revealed that the reduction reactions were induced by eaq- at pH 9.2, and dominated by H at pH 6.0. Complete dechlorination was readily achieved with all chlorine atoms in DCF released as chloride ions under sulfite/UV ARP, which may lead to a decreased toxicity of the degradation products. This observation emphasized the advantages of sulfite/UV ARP on DCF degradation, in comparison with that under direct UV photolysis.status: Published onlin

Effects of process variables and kinetics on the degradation of 2,4-dichlorophenol using advanced reduction processes (ARP)

This study aims at investigating the efficiency and kinetics of 2,4-DCP degradation via advanced reduction processes (ARP). Using UV light as activation method, the highest degradation efficiency of 2,4-DCP was obtained when using sulphite as a reducing agent. The highest degradation efficiency was observed under alkaline conditions (pH = 10.0), for high sulphite dosage and UV intensity, and low 2,4-DCP concentration. For all process conditions, first-order reaction rate kinetics were applicable. A quadratic polynomial equation fitted by a Box-Behnken Design was used as a statistical model and proved to be precise and reliable in describing the significance of the different process variables. The analysis of variance demonstrated that the experimental results were in good agreement with the predicted model (R2 = 0.9343), and solution pH, sulphite dose and UV intensity were found to be key process variables in the sulphite/UV ARP. Consequently, the present study provides a promising approach for the efficient degradation of 2,4-DCP with fast degradation kinetics.status: publishe