QSAR and molecular docking for the search of AOX inhibitors: a rational drug discovery approach

Validamycin A Inhibited FB1 Biosynthesis by the Target FvNth in Fusarium verticillioides

Validamycin A (VMA) is an antifungal antibiotic derived from Streptomyces hygroscopicus commonly used in plant disease management. Surprisingly, VMA was discovered to impede the production of fumonisin B1 (FB1) in agricultural settings. However, the specific target of VMA in Fusarium verticillioides remained unclear. To unravel the molecular mechanism of VMA, ultrastructural observations unveiled damage to mitochondrial membranes. Trehalase (FvNth) was pinpointed as the target of VMA by utilizing a 3D-printed surface plasmon resonance sensor. Molecular docking identified Trp285, Arg447, Asp452, and Phe665 as the binding sites between VMA and FvNth. A ΔFvnth mutant lacking amino acids 250-670 was engineered through homologous recombination. Transcriptome analysis indicated that samples treated with VMA and ΔFvnth displayed similar expression patterns, particularly in the suppression of the FUM gene cluster. VMA treatment resulted in reduced trehalase and ATPase activity as well as diminished production of glucose, pyruvic acid, and acetyl-CoA. Conversely, these effects were absent in samples treated with ΔFvnth. This research proposes that VMA hinders acetyl-CoA synthesis by trehalase, thereby suppressing the FB1 biosynthesis. These findings present a novel target for the development of mycotoxin control agents.

Development of an immunoinflammatory indicator-related dynamic nomogram based on machine learning for the prediction of intravenous immunoglobulin-resistant Kawasaki disease patients

BACKGROUND

Approximately 10-20% of Kawasaki disease (KD) patients suffer from intravenous immunoglobulin (IVIG) resistance, placing them at higher risk of developing coronary artery aneurysms. Therefore, we aimed to construct an IVIG resistance prediction tool for children with KD in Shanghai, China.

METHODS

Retrospective analysis was conducted on data from 1271 patients diagnosed with KD and the patients were randomly divided into a training set and a validation set in a 2:1 ratio. Machine learning algorithms were employed to identify important predictors associated with IVIG resistance and to build a predictive model. The best-performing model was used to construct a dynamic nomogram. Moreover, receiver operating characteristic curves, calibration plots, and decision-curve analysis were utilized to measure the discriminatory power, accuracy, and clinical utility of the nomogram.

RESULTS

Six variables were identified as important predictors, including C-reactive protein, neutrophil ratio, procalcitonin, CD3 ratio, CD19 count, and IgM level. A dynamic nomogram constructed with these factors was available at https://hktk.shinyapps.io/dynnomapp/. The nomogram demonstrated good diagnostic performance in the training and validation sets (area under the receiver operating characteristic curve = 0.816 and 0.800, respectively). Moreover, the calibration curves and decision curves analysis indicated that the nomogram showed good consistency between predicted and actual outcomes and had good clinical benefits.

CONCLUSION

A web-based dynamic nomogram for IVIG resistance was constructed with good predictive performance, which can be used as a practical approach for early screening to assist physicians in personalizing the treatment of KD patients in Shanghai.

Alternative Oxidase: From Molecule and Function to Future Inhibitors

In the respiratory chain of the majority of aerobic organisms, the enzyme alternative oxidase (AOX) functions as the terminal oxidase and has important roles in maintaining metabolic and signaling homeostasis in mitochondria. AOX endows the respiratory system with flexibility in the coupling among the carbon metabolism pathway, electron transport chain (ETC) activity, and ATP turnover. AOX allows electrons to bypass the main cytochrome pathway to restrict the generation of reactive oxygen species (ROS). The inhibition of AOX leads to oxidative damage and contributes to the loss of adaptability and viability in some pathogenic organisms. Although AOXs have recently been identified in several organisms, crystal structures and major functions still need to be explored. Recent work on the trypanosome alternative oxidase has provided a crystal structure of an AOX protein, which contributes to the structure-activity relationship of the inhibitors of AOX. Here, we review the current knowledge on the development, structure, and properties of AOXs, as well as their roles and mechanisms in plants, animals, algae, protists, fungi, and bacteria, with a special emphasis on the development of AOX inhibitors, which will improve the understanding of respiratory regulation in many organisms and provide references for subsequent studies of AOX-targeted inhibitors.

Filamentous Fungi-Derived Orsellinic Acid-Sesquiterpene Meroterpenoids: Fungal Sources, Chemical Structures, Bioactivities, and Biosynthesis

Fungi-derived polyketide-terpenoid hybrids are important meroterpenoid natural products that possess diverse structure scaffolds with a broad spectrum of bioactivities. Herein, we focus on an ever-increasing group of meroterpenoids, orsellinic acid-sesquiterpene hybrids comprised of biosynthetic start unit orsellinic acid coupling to a farnesyl group or/and its modified cyclic products. The review entails the search of China National Knowledge Infrastructure (CNKI), Web of Science, Science Direct, Google Scholar, and PubMed databases up to June 2022. The key terms include "orsellinic acid", "sesquiterpene", "ascochlorin", "ascofuranone", and "Ascochyta viciae", which are combined with the structures of "ascochlorin" and "ascofuranone" drawn by the Reaxys and Scifinder databases. In our search, these orsellinic acid-sesquiterpene hybrids are mainly produced by filamentous fungi. Ascochlorin was the first compound reported in 1968 and isolated from filamentous fungus Ascochyta viciae (synonym: Acremonium egyptiacum; Acremonium sclerotigenum); to date, 71 molecules are discovered from various filamentous fungi inhabiting in a variety of ecological niches. As typical representatives of the hybrid molecules, the biosynthetic pathway of ascofuranone and ascochlorin are discussed. The group of meroterpenoid hybrids exhibits a broad arrange of bioactivities, as highlighted by targeting hDHODH (human dihydroorotate dehydrogenase) inhibition, antitrypanosomal, and antimicrobial activities. This review summarizes the findings related to the structures, fungal sources, bioactivities, and their biosynthesis from 1968 to June 2022.

In silico identification of novel heterocyclic compounds combats Alzheimer's disease through inhibition of butyrylcholinesterase enzymatic activity

Increasing evidence indicates that heterocyclic molecules possess properties against butyrylcholinesterase (BChE) enzymatic activity, which is a potential therapeutic target for Alzheimer's disease (AD). Thus, this study aimed to further evaluate the relationship between heterocyclic molecules and their biological activities. A dataset of 38 selective and potent heterocyclic compounds (-log[the half‑maximal inhibitory concentration (pIC50)]) values ranging from 8.02 to 10.05) was applied to construct a quantitative structure-activity relationship (QSAR) study, including Bayesian model average (BMA), artificial neural network (ANN), multiple nonlinear regression (MNLR), and multiple linear regression (MLR) models. Four models met statistical acceptance in internal and external validation. The ANN model was superior to other models in predicting the pIC50 of the outcome. The descriptors put into the models were found to be comparable with the target-ligand complex X-ray structures, making these models interpretable. Three selected molecules possess drug-like properties (pIC50 values ranged from 9.19 to 9.54). The docking score between candidates and the BChE receptor (RCSB ID 6EYF) ranged from -8.4 to -9.0 kcal/mol. Remarkably, the pharmacokinetics, biological activities, molecular dynamics, and physicochemical properties of compound 18 (C20H22N4O, pIC50 value = 9.33, oxadiazole derivative group) support its protective effects on AD treatment due to its non-toxic nature, non-carcinogen, cholinergic nature, capability to penetrate the blood-brain barrier, and high gastrointestinal absorption.Communicated by Ramaswamy H. Sarma.

Prediction of drug-induced mitochondrial dysfunction using succinate-cytochrome c reductase activity, QSAR and molecular docking

There is increasing evidence that links mitochondrial off-target effects with organ toxicities. For this reason, predictive strategies need to be developed to identify mitochondrial dysfunction early in the drug discovery process. In this study, as a major mechanism of mitochondrial toxicity, first, the inhibitory activity of 35 compounds against succinate-cytochrome c reductase (SCR) was investigated. This in vitro study led to the generation of consistent experimental data for a diverse range of compounds, including pharmaceutical drugs and fungicides. Next, molecular docking and protein-ligand interaction fingerprinting (PLIF) analysis were used to identify significant residues and protein-ligand interactions for the Q_o site of complex III and Q site of complex II. Finally, this data was used for the development of QSAR models using a regression-based approach to highlight structural and chemical features that might be responsible for SCR inhibition. The statistically validated QSAR models from this work highlighted the importance of low aqueous solubility, low ionisation, fewer 6-membered rings and shorter hydrocarbon alkane chains in the molecular structure for increased inhibition of SCR, hence mitochondrial toxicity. PLIF analysis highlighted two key residues for inhibitory activity of the Q_o site of complex III: His 161 as H-bond acceptor and Pro 270 for arene interactions. Currently, there are limited structure-activity models published in the scientific literature for the prediction of mitochondrial toxicity. We believe this study helps shed light on the chemical space for the inhibition of mitochondrial electron transport chain (ETC).

Electrospun nanofibrous membrane with antibacterial and antiviral properties decorated with Myoporum bontioides extract and silver-doped carbon nitride nanoparticles for medical masks application

Public health safety issues have been plaguing the world since the pandemic outbreak of coronavirus disease (COVID-19). However, most personal protective equipments (PPE) do not have antibacterial and anti- toxicity effects. In this work, we designed and prepared a reusable, antibacterial and anti-toxicity Polyacrylonitrile (PAN) based nanofibrous membrane cooperated with Ag/g-C₃N₄ (Ag-CN), Myoporum.bontioides (M. bontioides) plant extracts and Ag nanoparticles (NPs) by an electrospinning-process. The SEM and TEM characterization revealed the formation of raised, creased or wrinkled areas on the fiber surface caused by the Ag nanoparticles, the rough surface prevented the aerosol particles on the fiber surface from sliding and stagnating, thus providing excellent filtration performance. The PAN/M. bontioides/Ag-CN/Ag nanofibrous membrane could be employed as a photocatalytic bactericidal material, which not only degraded 96.37% of methylene blue within 150 min, but also exhibited the superior bactericidal effect of 98.65 ± 1.49% and 97.8 ± 1.27% against E. coli and S. aureus, respectively, under 3 hs of light exposure. After 3 cycles of sterilization experiments, the PAN/M. bontioides/Ag-CN/Ag nanofibrous membrane maintained an efficient sterilization effect. Molecular docking revealed that the compounds in M. bontioides extracts interacted with neo-coronavirus targets mainly on Mpro and RdRp proteins, and these compounds had the strongest docking energy with Mpro protein, the shortest docking radius, and more binding sites for key amino acids around the viral protein targets, which influenced the replication and transcription process of neo-coronavirus. The PAN/M.bontioides/Ag-CN/Ag nanofibrous membrane also performed significant inhibition of influenza A virus H3N2. The novel nanofiber membrane is expected to be applied to medical masks, which will improve human isolation and protection against viruses.

Targeting the alternative oxidase (AOX) for human health and food security, a pharmaceutical and agrochemical target or a rescue mechanism?

Some of the most threatening human diseases are due to a blockage of the mitochondrial electron transport chain (ETC). In a variety of plants, fungi, and prokaryotes, there is a naturally evolved mechanism for such threats to viability, namely a bypassing of the blocked portion of the ETC by alternative enzymes of the respiratory chain. One such enzyme is the alternative oxidase (AOX). When AOX is expressed, it enables its host to survive life-threatening conditions or, as in parasites, to evade host defenses. In vertebrates, this mechanism has been lost during evolution. However, we and others have shown that transfer of AOX into the genome of the fruit fly and mouse results in a catalytically engaged AOX. This implies that not only is the AOX a promising target for combating human or agricultural pathogens but also a novel approach to elucidate disease mechanisms or, in several cases, potentially a therapeutic cure for human diseases. In this review, we highlight the varying functions of AOX in their natural hosts and upon xenotopic expression, and discuss the resulting need to develop species-specific AOX inhibitors.

A Deep Learning-Based Quantitative Structure-Activity Relationship System Construct Prediction Model of Agonist and Antagonist with High Performance

Molecular design and evaluation for drug development and chemical safety assessment have been advanced by quantitative structure–activity relationship (QSAR) using artificial intelligence techniques, such as deep learning (DL). Previously, we have reported the high performance of prediction models molecular initiation events (MIEs) on the adverse toxicological outcome using a DL-based QSAR method, called DeepSnap-DL. This method can extract feature values from images generated on a three-dimensional (3D)-chemical structure as a novel QSAR analytical system. However, there is room for improvement of this system’s time-consumption. Therefore, in this study, we constructed an improved DeepSnap-DL system by combining the processes of generating an image from a 3D-chemical structure, DL using the image as input data, and statistical calculation of prediction-performance. Consequently, we obtained that the three prediction models of agonists or antagonists of MIEs achieved high prediction-performance by optimizing the parameters of DeepSnap, such as the angle used in the depiction of the image of a 3D-chemical structure, data-split, and hyperparameters in DL. The improved DeepSnap-DL system will be a powerful tool for computer-aided molecular design as a novel QSAR system.

Comparison of the Kinetic Parameters of Alternative Oxidases From Trypanosoma brucei and Arabidopsis thaliana-A Tale of Two Cavities

The alternative oxidase (AOX) is widespread in plants, fungi, and some protozoa. While the general structure of the AOX remains consistent, its overall activity, sources of kinetic activation and their sensitivity to inhibitors varies between species. In this study, the recombinant Trypanosoma brucei AOX (rTAO) and Arabidopsis thaliana AOX1A (rAtAOX1A) were expressed in the Escherichia coli ΔhemA mutant FN102, and the kinetic parameters of purified AOXs were compared. Results showed that rTAO possessed the highest V _max and K _m for quinol-1, while much lower V _max and K _m were observed in the rAtAOX1A. The catalytic efficiency (k _cat/K _m) of rTAO was higher than that of rAtAOX1A. The rTAO also displayed a higher oxygen affinity compared to rAtAOX1A. It should be noted that rAtAOX1a was sensitive to α-keto acids while rTAO was not. Nevertheless, only pyruvate and glyoxylate can fully activate Arabidopsis AOX. In addition, rTAO and rAtAOX1A showed different sensitivity to AOX inhibitors, with ascofuranone (AF) being the best inhibitor against rTAO, while colletochlorin B (CB) appeared to be the most effective inhibitor against rAtAOX1A. Octylgallate (OG) and salicylhydroxamic acid (SHAM) are less effective than the other inhibitors against protist and plant AOX. A Caver analysis indicated that the rTAO and rAtAOX1A differ with respect to the mixture of polar residues lining the hydrophobic cavity, which may account for the observed difference in kinetic and inhibitor sensitivities. The data obtained in this study are not only beneficial for our understanding of the variation in the kinetics of AOX within protozoa and plants but also contribute to the guidance for the future development of phytopathogenic fungicides.

Outliers in SAR and QSAR: 3. Importance of considering the role of water molecules in protein-ligand interactions and quantitative structure-activity relationship studies

It is frequently mentioned that QSARs have not generally lived up to expectations, especially in cases where high predictability is expected yet failed to deliver satisfactory results. Even though outliers can provide an increased opportunity in drug discovery research, outliers in SAR and QSAR can contort predictions and affect the accuracy if proper attention is not given. The percentages of outliers in QSARs have not changed appreciably over the last decade. In our previous studies, we suggested two possible sources of outliers in SAR and QSAR. In this paper, we suggest an additional possible source of outliers in QSAR. We presented several literature examples that show one or more water molecules that play a critical role in protein-ligand binding interactions as observed in their crystal structures. These examples illustrate that failing to account for the effects of water molecules in protein-ligand interactions could mislead interpretation and possibly yield outliers in SAR and QSAR. Examples include cases where QSAR, considering the role of water molecules in protein-ligand crystal structures, provided deeper insight into the understanding and interpretation of the developed QSAR.