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Author: search.filters.author.Jongkon, Nathjanan

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    Bioassay-Guided Extraction and Isolation of Natural Herbicides from Dried Zanthoxylum limonella Alston Fruits
    (2025-01-01)
    Chotpatiwetchkul, Warot
    ;
    Charoenying, Patchanee
    ;
    Teerarak, Montinee
    ;
    Meesin, Jatuporn
    ;
    Jongkon, Nathjanan
    Weeds are problematic plant species around the world. Various strategies exist for controlling weeds, but chemical treatment remains the preferred method, particularly when using natural substances. In this research, a crude aqueous-methanol extract from dried Zanthoxylum limonella fruits was acid-base partitioned into four fractions: neutral extract (NE), acid extract (AE), basic extract (BE), and aqueous extract (AQ). These fractions were further separated into seventeen subfractions: NEF1 to NEF7, AEF1 to AEF5, and BEF1 to BEF5, which were then tested for herbicidal activity against the growth of Chinese amaranth (Amaranthus tricolor) and barnyard grass (Echinochloa crus-galli). Active subfractions were isolated via column chromatography and identified using spectroscopic methods, yielding seven active compounds: xanthoxyline (1), tambulin (2), atanine (3), prudomestin (4), skimmianine (5), p-methoxybenzoic acid (6), and methyl caffeate (7). Compounds 2–7 had not been previously reported in Z. limonella. Xanthoxyline (1) was identified as the most potent botanical herbicide, fully inhibiting seed germination of Chinese amaranth and barnyard grass. This compound also decreased seed imbibition and α-amylase activity in both species. Molecular docking studies on the α-amylase enzyme (PDB ID: 1BG9) revealed that the aromatic, hydroxy, and carbonyl groups of xanthoxyline (1) interact with the enzyme's active sites.
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    Insights into the EGFR SAR of N-phenylquinazolin-4-amine-derivatives using quantum mechanical pairwise-interaction energies
    (2019-08-01)
    Simeon, Saw
    ;
    Jongkon, Nathjanan
    ;
    Chotpatiwetchkul, Warot
    ;
    Gleeson, M. Paul
    Protein kinases are an important class of enzymes that play an essential role in virtually all major disease areas. In addition, they account for approximately 50% of the current targets pursued in drug discovery research. In this work, we explore the generation of structure-based quantum mechanical (QM) quantitative structure–activity relationship models (QSAR) as a means to facilitate structure-guided optimization of protein kinase inhibitors. We explore whether more accurate, interpretable QSAR models can be generated for a series of 76 N-phenylquinazolin-4-amine inhibitors of epidermal growth factor receptor (EGFR) kinase by comparing and contrasting them to other standard QSAR methodologies. The QM-based method involved molecular docking of inhibitors followed by their QM optimization within a ~ 300 atom cluster model of the EGFR active site at the M062X/6-31G(d,p) level. Pairwise computations of the interaction energies with each active site residue were performed. QSAR models were generated by splitting the datasets 75:25 into a training and test set followed by modelling using partial least squares (PLS). Additional QSAR models were generated using alignment dependent CoMFA and CoMSIA methods as well as alignment independent physicochemical, e-state indices and fingerprint descriptors. The structure-based QM-QSAR model displayed good performance on the training and test sets (r<sup>2</sup> ~ 0.7) and was demonstrably more predictive than the QSAR models built using other methods. The descriptor coefficients from the QM-QSAR models allowed for a detailed rationalization of the active site SAR, which has implications for subsequent design iterations.
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    Elucidation of the catalytic mechanism of 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase using QM/MM calculations
    (2018-01-01)
    Jongkon, Nathjanan
    ;
    Gleeson, Duangkamol
    ;
    Gleeson, M. Paul
    The folate pathway is a recognized intervention point for treating parasitic and bacterial infections in humans. However, the efficacy of treatments targeting dihydropteroate synthase (DHPS) and dihydrofolate reductase (DHFR) has reduced due to disease-related mutations. This has prompted interest in other enzyme targets on this clinically validated pathway, including 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase (HPPK). A challenge in the design of molecules to target this enzyme is that the precise mechanism of the reaction and the role of the active site residues are not fully understood. In this study, we report the first theoretical analysis of the catalytic pathway of the natural substrate using hybrid quantum mechanical/molecular mechanical (QM/MM) methods. The reaction profiles associated with three proposed general bases have been investigated, as well as the profile for two mutant enzymes, namely R92A and R82A. We identified R92 as the general base in the wildtype reaction. The predicted barriers are in good agreement with the observed experimental k<inf>cat</inf> values obtained for wildtype and mutant proteins.