A comprehensive review of in silico approaches for the prediction and modulation of aldehyde oxidase-mediated drug metabolism: The current features, challenges and future perspectives

Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

In vivo stability of 211At-radiopharmaceuticals: on the impact of halogen bond formation

211At, when coupled to a targeting agent, is one of the most promising radionuclides for therapeutic applications. The main labelling approach consists in the formation of astatoaryl compounds, which often show a lack of in vivo stability. The hypothesis that halogen bond (XB) interactions with protein functional groups initiate a deastatination mechanism is investigated through radiochemical experiments and DFT modelling. Several descriptors agree on the known mechanism of iodoaryl substrates dehalogenation by iodothyronine deiodinases, supporting the higher in vivo dehalogenation of N-succinimidyl 3-[211At]astatobenzoate (SAB) conjugates in comparison with their iodinated counterparts. The guanidinium group in 3-[211At]astato-4-guanidinomethylbenzoate (SAGMB) prevents the formation of At-mediated XBs with the selenocysteine active site in iodothyronine deiodinases. The initial step of At-aryl bond dissociation is inhibited, elucidating the better in vivo stability of SAGMB conjugates compared with those of SAB. The impact of astatine's ability to form XB interactions on radiopharmaceutical degradation may not be limited to the case of aryl radiolabeling.

Computational and artificial intelligence-based approaches for drug metabolism and transport prediction

Drug metabolism and transport, orchestrated by drug-metabolizing enzymes (DMEs) and drug transporters (DTs), are implicated in drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Reliable and precise predictions of DDIs and ADRs are critical in the early stages of drug development to reduce the rate of drug candidate failure. A variety of experimental and computational technologies have been developed to predict DDIs and ADRs. Recent artificial intelligence (AI) approaches offer new opportunities for better predicting and understanding the complex processes related to drug metabolism and transport. We summarize the role of major DMEs and DTs, and provide an overview of current progress in computational approaches for the prediction of drug metabolism, transport, and DDIs, with an emphasis on AI including machine learning (ML) and deep learning (DL) modeling.

Large Computational Survey of Intrinsic Reactivity of Aromatic Carbon Atoms with Respect to a Model Aldehyde Oxidase

Aldehyde oxidase (AOX) and other related molybdenum-containing enzymes are known to oxidize the C-H bonds of aromatic rings. This process contributes to the metabolism of pharmaceutical compounds and, therefore, is of vital importance to drug pharmacokinetics. The present work describes an automated computational workflow and its use for the prediction of intrinsic reactivity of small aromatic molecules toward a minimal model of the active site of AOX. The workflow is based on quantum chemical transition state searches for the underlying single-step oxidation reaction, where the automated protocol includes identification of unique aromatic C-H bonds, creation of three-dimensional reactant and product complex geometries via a templating approach, search for a transition state, and validation of reaction end points. Conformational search on the reactants, products, and the transition states is performed. The automated procedure has been validated on previously reported transition state barriers and was used to evaluate the intrinsic reactivity of nearly three hundred heterocycles commonly found in approved drug molecules. The intrinsic reactivity of more than 1000 individual aromatic carbon sites is reported. Stereochemical and conformational aspects of the oxidation reaction, which have not been discussed in previous studies, are shown to play important roles in accurate modeling of the oxidation reaction. Observations on structural trends that determine the reactivity are provided and rationalized.

Study of Genotoxicity, Activities on Caspase 8 and on the Stabilization of the Topoisomerase Complex of Isoeleutherin and Analogues

This study evaluated the genotoxicity of Ethanol Extract (EEEp), Dichloromethane Fraction (FDCMEp) and isoeleutherin isolated from Eleutherine plicata, using the micronucleus test and the impact of structural alterations on toxicity and molecular docking (topoisomerase II and DNA complex). The extract was obtained by maceration and fractionation in a chromatography column. The genotoxicity was evaluated by the micronucleus test in human hepatoma cells (HepG2). Isoeleutherin was the starting molecule in the search for analogues by structural similarity, using the ZINC and e-Molecules databases. Isoeleutherin and analogues were subjected to in silico toxicity prediction, and compounds free of toxicological risks (CP13, CP14, CP17 and isoeleutherin) were selected for molecular docking in Topoisomerase II (PDB: 1ZXM). In the micronucleus test, isoeleutherin was less genotoxic. Among the 22 isoeleutherin analogues there were variations in the toxicity profile. Molecular docking studies showed that the compounds have good complementarity in the active site with important hydrogens bonds. Therefore, the structural changes of isoeleutherin led to the obtaining of a molecule with a lower mutagenic potential, and the CP13 can be considered a prototype compound for the development of new molecules with pharmacological potential.

Synthesis of Deuterated Heterocycles with Me2NCD(OMe)2 and Evaluation of the Products for Metabolism by Aldehyde Oxidase

The metabolic oxidation of drug-like small molecules by aldehyde oxidase (AO) has commonly been mitigated through the incorporation of deuterium at the oxidation site. We report that dimethylformamide dimethyl acetal and related compounds undergo rapid CH to CD isotopic exchange upon exposure to methanol-d and similar deuterated alcohols. This isotopic exchange process can be used to synthesize Me₂NCD(OMe)₂ and has significant implications for the use of Me₂NCD(OMe)₂ in the synthesis of specifically deuterium-labeled compounds. The application of Me₂NCD(OMe)₂ to the synthesis of various heterocycles that have been associated with AO metabolism is described, and we report the impact of deuteration on the rate of in vitro AO-mediated metabolism.

Investigation of Janus Kinase (JAK) Inhibitors for Lung Delivery and the Importance of Aldehyde Oxidase Metabolism

The Janus family of tyrosine kinases (JAK1, JAK2, JAK3, and TYK2) play an essential role in the receptor signaling of cytokines that have been implicated in the pathogenesis of severe asthma, and there is emerging interest in the development of small-molecule-inhaled JAK inhibitors as treatments. Here, we describe the optimization of a quinazoline series of JAK inhibitors and the results of mouse lung pharmacokinetic (PK) studies where only low concentrations of parent compound were observed. Subsequent investigations revealed that the low exposure was due to metabolism by aldehyde oxidase (AO), so we sought to identify quinazolines that were not metabolized by AO. We found that specific substituents at the quinazoline 2-position prevented AO metabolism and this was rationalized through computational docking studies in the AO binding site, but they compromised kinome selectivity. Results presented here highlight that AO metabolism is a potential issue in the lung.