Spectroscopic methods to analyze drug metabolites

New Insights into the Degradation Path of Deltamethrin

Pyrethroids are among the insecticidal compounds indicated by the World Health Organization for mitigation of vector-borne diseases. Active deltamethrin (with chiral configuration α-S,1-R-cis) is one of the most effective pyrethroids characterized by low toxicity to humans, and it is currently tested as active ingredient for insecticidal paints. Nevertheless, several degradation processes can occur and affect the insecticidal efficacy in the complex paint matrix. In the present study, a detailed NMR analysis of deltamethrin stability has been carried out under stress conditions, mimicking a water-based insecticidal paint environment. Two novel by-products, having a diastereomeric relationship, were identified and their structure was elucidated by combining NMR, HPLC, GC-MS, and ESI-MS analyses. These compounds are the result from a nucleophilic addition involving deltamethrin and one of its major degradation products, 3-phenoxybenzaldehyde. Given the known toxicity of the aldehyde, this reaction could represent a way to reduce its concentration into the matrix. On the other hand, the toxicology of these compounds towards humans should be addressed, as their presence may adversely affect the performance of deltamethrin-containing products.

Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways

Prediction and reconstruction of metabolic pathways play significant roles in many fields such as genetic engineering, metabolic engineering, drug discovery, and are becoming the most active research topics in synthetic biology. With the increase of related data and with the development of machine learning techniques, there have many machine leaning based methods been proposed for prediction or reconstruction of metabolic pathways. Machine learning techniques are showing state-of-the-art performance to handle the rapidly increasing volume of data in synthetic biology. To support researchers in this field, we briefly review the research progress of metabolic pathway reconstruction and prediction based on machine learning. Some challenging issues in the reconstruction of metabolic pathways are also discussed in this paper.

An overview of therapeutic anticancer drug monitoring based on surface enhanced (resonance) Raman spectroscopy (SE(R)RS)

Therapeutic drug monitoring (TDM) is important for many therapeutic regimens and has particular relevance for anticancer drugs which often have serious effects and whose optimum dosage can vary significantly between different patients. Many of the features of surface enhanced (resonance) Raman spectroscopy (SE(R)RS) suggest it should be very suitable for TDM of anticancer drugs and some initial studies which explore the potential of SE(R)RS for TDM of anticancer drugs have been published. This review brings this work together in an attempt to draw some general observations about key aspects of the approach, including the nature of the substrate used, matrix interference effects and factors governing adsorption of the target molecules onto the enhancing surface. There is now sufficient evidence to suggest that none of these pose real difficulties in the context of TDM. However, some issues, particularly the need to carry out multiplex measurements for TDM of combination therapies, have yet to be addressed.

Synthesis of two new lipid mediators from docosahexaenoic acid by combinatorial catalysis involving enzymatic and chemical reaction

Omega-3 polyunsaturated fatty acids (PUFAs) have been known to have beneficial effects in the prevention of various diseases. Recently, it was identified that the bioactivities of omega-3 are related to lipid mediators, called pro-resolving lipid mediators (SPMs), converted from PUFAs, so they have attracted much attention as potential pharmaceutical targets. Here, we aimed to build an efficient production system composed of enzymatic and chemical catalysis that converts docosahexaenoic acid (DHA) into lipid mediators. The cyanobacterial lipoxygenase, named Osc-LOX, was identified and characterized, and the binding poses of enzyme and substrates were predicted by ligand docking simulation. DHA was converted into three lipid mediators, a 17S-hydroxy-DHA, a 7S,17S-dihydroxy-DHA (RvD5), and a 7S,15R-dihydroxy-16S,17S-epoxy-DPA (new type), by an enzymatic reaction and deoxygenation. Also, two lipid mediators, 7S,15R,16S,17S-tetrahydroxy-DPA (new type) and 7S,16R,17S-trihydroxy-DHA (RvD2), were generated from 7S,15R-dihydroxy-16S,17S-epoxy-DPA by a chemical reaction. Our study suggests that discovering new enzymes that have not been functionally characterized would be a powerful strategy for producing various lipid mediators. Also, this combination catalysis approach including biological and chemical reactions could be an effective production system for the manufacturing lipid mediators.