Molecular binding of different classes of organophosphates to methyl parathion hydrolase from Ochrobactrum species.

Methyl parathion hydrolase (MPH) is an enzyme of the metallo-ß-lactamase superfamily, which hydrolyses a wide range of organophosphates (OPs). Recently, MPH has attracted attention as a promising enzymatic bioremediator. The crystal structure of MPH enzyme shows a dimeric form, with each subunit containing a binuclear metal ion center. MPH also demonstrates metal ion-dependent selectivity patterns. The origins of these patterns remain unclear but are linked to open questions about the more general role of metal ions in functional evolution and divergence within enzyme superfamilies. We aimed to investigate and compare the binding of different OP pesticides to MPH with cobalt(II) metal ions. In this study, MPH was modeled from Ochrobactrum sp. with different OP pesticides bound, including methyl paraoxon and dichlorvos and profenofos. The docked structures for each substrate optimized by DFT calculation were selected and subjected to atomistic molecular dynamics simulations for 500 ns. It was found that alpha metal ions did not coordinate with all the pesticides. Rather, the pesticides coordinated with less buried beta metal ions. It was also observed that the coordination of beta metal ions was perturbed to accommodate the pesticides. The binding free energy calculations and structure-based pharmacophore model revealed that all the three substrates could bind well at the active site. However, profenofos exhibit a stronger binding affinity to MPH in comparison to the other two substrates. Therefore, our findings provide molecular insight on the binding of different OP pesticides which could help us design the enzyme for OP pesticides degradation.

Stimulating T cell responses against patient-derived breast cancer cells with neoantigen peptide-loaded peripheral blood mononuclear cells.

Breast cancer stands as a formidable global health challenge for women. While neoantigens exhibit efficacy in activating T cells specific to cancer and instigating anti-tumor immune responses, the accuracy of neoantigen prediction remains suboptimal. In this study, we identified neoantigens from the patient-derived breast cancer cells, PC-B-142CA and PC-B-148CA cells, utilizing whole-genome and RNA sequencing. The pVAC-Seq pipeline was employed, with minor modification incorporating criteria (1) binding affinity of mutant (MT) peptide with HLA (IC50 MT) ≤ 500 nm in 3 of 5 algorithms and (2) IC50 wild type (WT)/MT > 1. Sequencing results unveiled 2513 and 3490 somatic mutations, and 646 and 652 non-synonymous mutations in PC-B-142CA and PC-B-148CA, respectively. We selected the top 3 neoantigens to perform molecular dynamic simulation and synthesized 9-12 amino acid neoantigen peptides, which were then pulsed onto healthy donor peripheral blood mononuclear cells (PBMCs). Results demonstrated that T cells activated by ADGRL1E274K, PARP1E619K, and SEC14L2R43Q peptides identified from PC-B-142CA exhibited significantly increased production of interferon-gamma (IFN-γ), while PARP1E619K and SEC14L2R43Q peptides induced the expression of CD107a on T cells. The % tumor cell lysis was notably enhanced by T cells activated with MT peptides across all three healthy donors. Moreover, ALKBH6V83M and GAAI823T peptides from PC-B-148CA remarkably stimulated IFN-γ- and CD107a-positive T cells, displaying high cell-killing activity against target cancer cells. In summary, our findings underscore the successful identification of neoantigens with anti-tumor T cell functions and highlight the potential of personalized neoantigens as a promising avenue for breast cancer treatment.

GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity.

The proteins within the human epidermal growth factor receptor (EGFR) family, members of the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving the development of various tumors. Tyrosine kinase inhibitors, key compounds in targeted therapy, encounter challenges in cancer treatment due to emerging drug resistance mutations. Consequently, machine learning has undergone significant evolution to address the challenges of cancer drug discovery related to EGFR family proteins. However, the application of deep learning in this area is hindered by inherent difficulties associated with small-scale data, particularly the risk of overfitting. Moreover, the design of a model architecture that facilitates learning through multi-task and transfer learning, coupled with appropriate molecular representation, poses substantial challenges. In this study, we introduce GraphEGFR, a deep learning regression model designed to enhance molecular representation and model architecture for predicting the bioactivity of inhibitors against both wild-type and mutant EGFR family proteins. GraphEGFR integrates a graph attention mechanism for molecular graphs with deep and convolutional neural networks for molecular fingerprints. We observed that GraphEGFR models employing multi-task and transfer learning strategies generally achieve predictive performance comparable to existing competitive methods. The integration of molecular graphs and fingerprints adeptly captures relationships between atoms and enables both global and local pattern recognition. We further validated potential multi-targeted inhibitors for wild-type and mutant HER1 kinases, exploring key amino acid residues through molecular dynamics simulations to understand molecular interactions. This predictive model offers a robust strategy that could significantly contribute to overcoming the challenges of developing deep learning models for drug discovery with limited data and exploring new frontiers in multi-targeted kinase drug discovery for EGFR family proteins.

Machine learning-guided design of potent darunavir analogs targeting HIV-1 proteases: A computational approach for antiretroviral drug discovery.

In the pursuit of novel antiretroviral therapies for human immunodeficiency virus type-1 (HIV-1) proteases (PRs), recent improvements in drug discovery have embraced machine learning (ML) techniques to guide the design process. This study employs ensemble learning models to identify crucial substructures as significant features for drug development. Using molecular docking techniques, a collection of 160 darunavir (DRV) analogs was designed based on these key substructures and subsequently screened using molecular docking techniques. Chemical structures with high fitness scores were selected, combined, and one-dimensional (1D) screening based on beyond Lipinski's rule of five (bRo5) and ADME (absorption, distribution, metabolism, and excretion) prediction implemented in the Combined Analog generator Tool (CAT) program. A total of 473 screened analogs were subjected to docking analysis through convolutional neural networks scoring function against both the wild-type (WT) and 12 major mutated PRs. DRV analogs with negative changes in binding free energy ( ΔΔ G bind ) compared to DRV could be categorized into four attractive groups based on their interactions with the majority of vital PRs. The analysis of interaction profiles revealed that potent designed analogs, targeting both WT and mutant PRs, exhibited interactions with common key amino acid residues. This observation further confirms that the ML model-guided approach effectively identified the substructures that play a crucial role in potent analogs. It is expected to function as a powerful computational tool, offering valuable guidance in the identification of chemical substructures for synthesis and subsequent experimental testing.

Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an r2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design; with the potential to guide experimental synthesis and enzyme assay testing.

Synthesis and biological evaluation of 2'-hydroxychalcone derivatives as AMPK activators.

A series of 2'-hydroxychalcone derivatives with various substituents on B-ring were synthesized and evaluated for AMP-activated protein kinase (AMPK) activation activity in podocyte cells. The results displayed that hydroxy, methoxy and methylenedioxy groups on B-ring could enhance the activitiy better than O-saturated alkyl, O-unsaturated alkyl or other alkoxy groups. Compounds 27 and 29 possess the highest fold change of 2.48 and 2.73, respectively, which were higher than those of reference compound (8) (1.28) and metformin (1.88). Compounds 27 and 29 were then subjected to a concentration-response study to obtain the EC50 values of 2.0 and 4.8 µM, respectively and MTT assays also showed that cell viability was not influenced by the exposure of podocytes to compounds 27 and 29 at concentrations up to 50 µM. In addition, compound 27 was proved to activate AMPK via calcium/calmodulin-dependent protein kinase kinase ß (CaMKKß)-dependent pathway without affecting intracellular calcium levels. The computational study showed that the potent compounds exhibited stronger ligand-binding strength to CaMKKß, particularly compounds 27 (-8.4 kcal/mol) and 29 (-8.0 kcal/mol), compared to compound 8 (-7.5 kcal/mol). Fragment molecular orbital (FMO) calculation demonstrated that compound 27 was superior to compound 29 due to the presence of methyl group, which amplified the binding by hydrophobic interactions. Therefore, compound 27 would represent a promising AMPK activator for further investigation of the treatment of diabetes and diabetic nephropathy.

Anilino-1,4-naphthoquinones as potent mushroom tyrosinase inhibitors: in vitro and in silico studies.

Tyrosinase, a pivotal enzyme in melanin synthesis, is a primary target for the development of depigmenting agents. In this work, in vitro and in silico techniques were employed to identify novel tyrosinase inhibitors from a set of 12 anilino-1,4-naphthoquinone derivatives. Results from the mushroom tyrosinase activity assay indicated that, among the 12 derivatives, three compounds (1, 5, and 10) demonstrated the most significant inhibitory activity against mushroom tyrosinase, surpassing the effectiveness of the kojic acid. Molecular docking revealed that all studied derivatives interacted with copper ions and amino acid residues at the enzyme active site. Molecular dynamics simulations provided insights into the stability of enzyme-inhibitor complexes, in which compounds 1, 5, and particularly 10 displayed greater stability, atomic contacts, and structural compactness than kojic acid. Drug likeness prediction further strengthens the potential of anilino-1,4-naphthoquinones as promising candidates for the development of novel tyrosinase inhibitors for the treatment of hyperpigmentation disorders.

Correction: Nukulkit et al. Eight Indole Alkaloids from the Roots of Maerua siamensis and Their Nitric Oxide Inhibitory Effects. Molecules 2022, 27, 7558.

After a proofreading check, some experimental data were inconsistent with the supplementary information in the original publication [...].

Daidzein Hydroxylation by CYP81E63 Is Involved in the Biosynthesis of Miroestrol in Pueraria mirifica.

White Kwao Krua (Pueraria candollei var. mirifica), a Thai medicinal plant, is a rich source of phytoestrogens, especially isoflavonoids and chromenes. These phytoestrogens are well known; however, their biosynthetic genes remain largely uncharacterized. Cytochrome P450 (P450) is a large protein family that plays a crucial role in the biosynthesis of various compounds in plants, including phytoestrogens. Thus, we focused on P450s involved in the isoflavone hydroxylation that potentially participates in the biosynthesis of miroestrol. Three candidate P450s were isolated from the transcriptome libraries by considering the phylogenetic and expression data of each tissue of P. mirifica. The candidate P450s were functionally characterized both in vitro and in planta. Accordingly, the yeast microsome harboring PmCYP81E63 regiospecifically exhibited either 2' or 3' daidzein hydroxylation and genistein hydroxylation. Based on in silico calculation, PmCYP81E63 had higher binding energy with daidzein than with genistein, which supported the in vitro result of the isoflavone specificity. To confirm in planta function, the candidate P450s were then transiently co-expressed with isoflavone-related genes in Nicotiana benthamiana. Despite no daidzein in the infiltrated N. benthamiana leaves, genistein and hydroxygenistein biosynthesis were detectable by liquid Chromatography with tandem mass spectrometry (LC-MS/MS). Additionally, we demonstrated that PmCYP81E63 interacted with several enzymes related to isoflavone biosynthesis using bimolecular fluorescence complementation studies and a yeast two-hybrid analysis, suggesting a scheme of metabolon formation in the pathway. Our findings provide compelling evidence regarding the involvement of PmCYP81E63 in the early step of the proposed miroestrol biosynthesis in P. mirifica.

Mangiferin is a new potential antimalarial and anticancer drug for targeting serine hydroxymethyltransferase.

Mangiferin, a polyphenolic xanthone glycoside found in various botanical sources, including mango (Mangifera indica L.) leaves, can exhibit a variety of bioactivities. Although mangiferin has been reported to inhibit many targets, none of the studies have investigated the inhibition of serine hydroxymethyltransferase (SHMT), an attractive target for antimalarial and anticancer drugs. SHMT, one of the key enzymes in the deoxythymidylate synthesis cycle, catalyzes the reversible conversion of l-serine and (6S)-tetrahydrofolate (THF) into glycine and 5,10-methylene THF. Here, in vitro and in silico studies were used to probe how mangiferin isolated from mango leaves inhibits Plasmodium falciparum and human cytosolic SHMTs. The inhibition kinetics at pH 7.5 revealed that mangiferin is a competitive inhibitor against THF for enzymes from both organisms. Molecular docking and molecular dynamic (MD) simulations demonstrated the inhibitory effects of the deprotonated forms of mangiferin, specifically the C6-O- species and its resonance C9-O- species appearing at pH 7.5, combined with two docked poses, either a xanthone or glucose moiety, placed inside the THF-binding pocket. The MD analysis revealed that both C6-O- and its resonance-stabilized C9-O- species can favorably bind to SHMT in a similar fashion to THF, supporting the THF competitive inhibition of mangiferin. In addition, characterization of the proton dissociation equilibria of isolated mangiferin revealed that only three hydroxy groups of the xanthone moiety, C6-OH, C3-OH, and C7-OH, underwent varying degrees of deprotonation with pKa values of 6.38 ± 0.11, 8.21 ± 0.35, and 12.37 ± 0.30, respectively, while C1-OH remained protonated. Altogether, our findings demonstrate a new bioactivity of mangiferin and provide the basis for the future development of mangiferin as a potent antimalarial and anticancer drug.

Identification of Promising Sulfonamide Chalcones as Inhibitors of SARS-CoV-2 3CLpro through Structure-Based Virtual Screening and Experimental Approaches.

3CLpro is a viable target for developing antiviral therapies against the coronavirus. With the urgent need to find new possible inhibitors, a structure-based virtual screening approach was developed. This study recognized 75 pharmacologically bioactive compounds from our in-house library of 1052 natural product-based compounds that satisfied drug-likeness criteria and exhibited good bioavailability and membrane permeability. Among these compounds, three promising sulfonamide chalcones were identified by combined theoretical and experimental approaches, with SWC423 being the most suitable representative compound due to its competitive inhibition and low cytotoxicity in Vero E6 cells (EC50 = 0.89 ± 0.32 µM; CC50 = 25.54 ± 1.38 µM; SI = 28.70). The binding and stability of SWC423 in the 3CLpro active site were investigated through all-atom molecular dynamics simulation and fragment molecular orbital calculation, indicating its potential as a 3CLpro inhibitor for further SARS-CoV-2 therapeutic research. These findings suggested that inhibiting 3CLpro with a sulfonamide chalcone such as SWC423 may pave the effective way for developing COVID-19 treatments.

Enhancement by pyrazolones of colistin efficacy against mcr-1-expressing E. coli: an in silico and in vitro investigation.

Owing to the emergence of antibiotic resistance, the polymyxin colistin has been recently revived to treat acute, multidrug-resistant Gram-negative bacterial infections. Positively charged colistin binds to negatively charged lipids and damages the outer membrane of Gram-negative bacteria. However, the MCR-1 protein, encoded by the mobile colistin resistance (mcr) gene, is involved in bacterial colistin resistance by catalysing phosphoethanolamine (PEA) transfer onto lipid A, neutralising its negative charge, and thereby reducing its interaction with colistin. Our preliminary results showed that treatment with a reference pyrazolone compound significantly reduced colistin minimal inhibitory concentrations in Escherichia coli expressing mcr-1 mediated colistin resistance (Hanpaibool et al. in ACS Omega, 2023). A docking-MD combination was used in an ensemble-based docking approach to identify further pyrazolone compounds as candidate MCR-1 inhibitors. Docking simulations revealed that 13/28 of the pyrazolone compounds tested are predicted to have lower binding free energies than the reference compound. Four of these were chosen for in vitro testing, with the results demonstrating that all the compounds tested could lower colistin MICs in an E. coli strain carrying the mcr-1 gene. Docking of pyrazolones into the MCR-1 active site reveals residues that are implicated in ligand-protein interactions, particularly E246, T285, H395, H466, and H478, which are located in the MCR-1 active site and which participate in interactions with MCR-1 in ≥ 8/10 of the lowest energy complexes. This study establishes pyrazolone-induced colistin susceptibility in E. coli carrying the mcr-1 gene, providing a method for the development of novel treatments against colistin-resistant bacteria.

Immunomodulatory Effects of New Phenanthrene Derivatives from Dendrobium crumenatum.

Three new phenanthrene derivatives (1, 2, 4), one new fluorenone (3), and four known compounds (5-8) were isolated from the ethyl acetate extract of Dendrobium crumenatum Sw. stems using column chromatography. The chemical structures were elucidated by analysis of spectroscopic data. The absolute configuration of 4 was determined by electronic circular dichroism calculation. We also evaluated the immunomodulatory effects of compounds isolated from D. crumenatum in human peripheral blood mononuclear cells from healthy individuals and those from patients with multiple sclerosis in vitro. Dendrocrumenol B (2) and dendrocrumenol D (4) showed strong immunomodulatory effects on both CD3+ T cells and CD14+ monocytes. Compounds 2 and 4 could reduce IL-2 and TNF production in T cells and monocytes that were treated with phorbol-12-myristate-13-acetate and ionomycin (PMA/Iono). Deep immune profiling using high-dimensional single-cell mass cytometry could confirm immunomodulatory effects of 4, quantified by the reduction of activated T cell population under PMA/Iono stimulation, in comparison to the stimulated T cells without treatment.

Voriconazole Eye Drops: Enhanced Solubility and Stability through Ternary Voriconazole/Sulfobutyl Ether ß-Cyclodextrin/Polyvinyl Alcohol Complexes.

Voriconazole (VCZ) is a broad-spectrum antifungal agent used to treat ocular fungal keratitis. However, VCZ has low aqueous solubility and chemical instability in aqueous solutions. This study aimed to develop VCZ eye drop formulations using cyclodextrin (CD) and water-soluble polymers, forming CD complex aggregates to improve the aqueous solubility and chemical stability of VCZ. The VCZ solubility was greatly enhanced using sulfobutyl ether ß-cyclodextrin (SBEßCD). The addition of polyvinyl alcohol (PVA) showed a synergistic effect on VCZ/SBEßCD solubilization and a stabilization effect on the VCZ/SBEßCD complex. The formation of binary VCZ/SBEßCD and ternary VCZ/SBEßCD/PVA complexes was confirmed by spectroscopic techniques and in silico studies. The 0.5% w/v VCZ eye drop formulations were developed consisting of 6% w/v SBEßCD and different types and concentrations of PVA. The VCZ/SBEßCD systems containing high-molecular-weight PVA prepared under freeze-thaw conditions (PVA-H hydrogel) provided high mucoadhesion, sustained release, good ex vivo permeability through the porcine cornea and no sign of irritation. Additionally, PVA-H hydrogel was effective against the filamentous fungi tested. The stability study revealed that our VCZ eye drops provide a shelf-life of more than 2.5 years at room temperature, while a shelf-life of only 3.5 months was observed for the extemporaneous Vfend® eye drops.

In Vitro and In Silico Study on the Molecular Encapsulation of α-Tocopherol in a Large-Ring Cyclodextrin.

α-tocopherol is the physiologically most active form of vitamin E, with numerous biological activities, such as significant antioxidant activity, anticancer capabilities, and anti-aging properties. However, its low water solubility has limited its potential use in the food, cosmetic, and pharmaceutical industries. One possible strategy for addressing this issue is the use of a supramolecular complex with large-ring cyclodextrins (LR-CDs). In this study, the phase solubility of the CD26/α-tocopherol complex was investigated to assess the possible ratios between host and guest in the solution phase. Next, the host-guest association of the CD26/α-tocopherol complex at different ratios of 1:2, 1:4, 1:6, 2:1, 4:1, and 6:1 was studied by all-atom molecular dynamics (MD) simulations. At 1:2 ratio, two α-tocopherol units interact spontaneously with CD26, forming an inclusion complex, as supported by the experimental data. In the 2:1 ratio, a single α-tocopherol unit was encapsulated by two CD26 molecules. In comparison, increasing the number of α-tocopherol or CD26 molecules above two led to self-aggregation and consequently limited the solubility of α-tocopherol. The computational and experimental results indicate that a 1:2 ratio could be the most suitable stoichiometry to use in the CD26/α-tocopherol complex to improve α-tocopherol solubility and stability in inclusion complex formation.

Rational Design of a Low-Data Regime of Pyrrole Antioxidants for Radical Scavenging Activities Using Quantum Chemical Descriptors and QSAR with the GA-MLR and ANN Concepts.

A series of pyrrole derivatives and their antioxidant scavenging activities toward the superoxide anion (O2•-), hydroxyl radical (•OH), and 1,1-diphenyl-2-picryl-hydrazyl (DPPH•) served as the training data sets of a quantitative structure-activity relationship (QSAR) study. The steric and electronic descriptors obtained from quantum chemical calculations were related to the three O2•-, •OH, and DPPH• scavenging activities using the genetic algorithm combined with multiple linear regression (GA-MLR) and artificial neural networks (ANNs). The GA-MLR models resulted in good statistical values; the coefficient of determination (R2) of the training set was greater than 0.8, and the root mean square error (RMSE) of the test set was in the range of 0.3 to 0.6. The main molecular descriptors that play an important role in the three types of antioxidant activities are the bond length, HOMO energy, polarizability, and AlogP. In the QSAR-ANN models, a good R2 value above 0.9 was obtained, and the RMSE of the test set falls in a similar range to that of the GA-MLR models. Therefore, both the QSAR GA-MLR and QSAR-ANN models were used to predict the newly designed pyrrole derivatives, which were developed based on their starting reagents in the synthetic process.

Quantitative Structure-Electrochemistry Relationship (QSER) Studies on Metal-Amino-Porphyrins for the Rational Design of CO2 Reduction Catalysts.

The quantitative structure-electrochemistry relationship (QSER) method was applied to a series of transition-metal-coordinated porphyrins to relate their structural properties to their electrochemical CO2 reduction activity. Since the reactions mainly occur within the core of the metalloporphyrin catalysts, the cluster model was used to calculate their structural and electronic properties using density functional theory with the M06L exchange-correlation functional. Three dependent variables were employed in this work: the Gibbs free energies of H*, C*OOH, and O*CHO. QSER, with the genetic algorithm combined with multiple linear regression (GA-MLR), was used to manipulate the mathematical models of all three Gibbs free energies. The obtained statistical values resulted in a good predictive ability (R2 value) greater than 0.945. Based on our QSER models, both the electronic properties (charges of the metal and porphyrin) and the structural properties (bond lengths between the metal center and the nitrogen atoms of the porphyrin) play a significant role in the three Gibbs free energies. This finding was further applied to estimate the CO2 reduction activities of the metal-monoamino-porphyrins, which will prove beneficial in further experimental developments.

In Silico and In Vitro Study of Janus Kinases Inhibitors from Naphthoquinones.

Janus kinases (JAKs) are involved in numerous cellular signaling processes related to immune cell functions. JAK2 and JAK3 are associated with the pathogenesis of leukemia and common lymphoid-derived illnesses. JAK2/3 inhibitors could reduce the risk of various diseases by targeting this pathway. Herein, the naphthoquinones were experimentally and theoretically investigated to identify novel JAK2/3 inhibitors. Napabucasin and 2'-methyl napabucasin exhibited potent cell growth inhibition in TF1 (IC50 = 9.57 and 18.10 µM) and HEL (IC50 = 3.31 and 6.65 µM) erythroleukemia cell lines, and they significantly inhibited JAK2/3 kinase activity (in a nanomolar range) better than the known JAK inhibitor, tofacitinib. Flow cytometric analysis revealed that these two compounds induced apoptosis in TF1 cells in a time and dose-dependent manner. From the molecular dynamics study, both compounds formed hydrogen bonds with Y931 and L932 residues and hydrophobically contacted with the conserved hinge region, G loop, and catalytic loop of the JAK2. Our obtained results suggested that napabucasin and its methylated analog were potential candidates for further development of novel anticancer drug targeting JAKs.

Discovery of Novel EGFR Inhibitor Targeting Wild-Type and Mutant Forms of EGFR: In Silico and In Vitro Study.

Targeting L858R/T790M and L858R/T790M/C797S mutant EGFR is a critical challenge in developing EGFR tyrosine kinase inhibitors to overcome drug resistance in non-small cell lung cancer (NSCLC). The discovery of next-generation EGFR tyrosine kinase inhibitors (TKIs) is therefore necessary. To this end, a series of furopyridine derivatives were evaluated for their EGFR-based inhibition and antiproliferative activities using computational and biological approaches. We found that several compounds derived from virtual screening based on a molecular docking and solvated interaction energy (SIE) method showed the potential to suppress wild-type and mutant EGFR. The most promising PD13 displayed strong inhibitory activity against wild-type (IC50 of 11.64 ± 1.30 nM), L858R/T790M (IC50 of 10.51 ± 0.71 nM), which are more significant than known drugs. In addition, PD13 revealed a potent cytotoxic effect on A549 and H1975 cell lines with IC50 values of 18.09 ± 1.57 and 33.87 ± 0.86 µM, respectively. The 500-ns MD simulations indicated that PD13 formed a hydrogen bond with Met793 at the hinge region, thus creating excellent EGFR inhibitory activity. Moreover, the binding of PD13 in the hinge region of EGFR was the major determining factor in stabilizing the interactions via hydrogen bonds and van der Waals (vdW). Altogether, PD13 is a promising novel EGFR inhibitor that could be further clinically developed as fourth-generation EGFR-TKIs.

Lichen-Derived Diffractaic Acid Inhibited Dengue Virus Replication in a Cell-Based System.

Dengue is a mosquito-borne flavivirus that causes 21,000 deaths annually. Depsides and depsidones of lichens have previously been reported to be antimicrobials. In this study, our objective was to identify lichen-derived depsides and depsidones as dengue virus inhibitors. The 18 depsides and depsidones of Usnea baileyi, Usnea aciculifera, Parmotrema dilatatum, and Parmotrema tsavoense were tested against dengue virus serotype 2. Two depsides and one depsidone inhibited dengue virus serotype 2 without any apparent cytotoxicity. Diffractaic acid, barbatic acid, and Parmosidone C were three active compounds further characterized for their efficacies (EC50), cytotoxicities (CC50), and selectivity index (SI; CC50/EC50). Their EC50 (SI) values were 2.43 ± 0.19 (20.59), 0.91 ± 0.15 (13.33), and 17.42 ± 3.21 (8.95) µM, respectively. Diffractaic acid showed the highest selectivity index, and similar efficacies were also found in dengue serotypes 1-4, Zika, and chikungunya viruses. Cell-based studies revealed that the target was mainly in the late stage with replication and the formation of infectious particles. This report highlights that a lichen-derived diffractaic acid could become a mosquito-borne antiviral lead as its selectivity indices ranged from 8.07 to 20.59 with a proposed target at viral replication.