Chotpatiwetchkul, Warot

Preferred name

Main Affiliation

School of Science

warot.ch@kmitl.ac.th

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3D-QSAR and molecular docking studies of peptide-hybrids as dengue virus NS2B/NS3 protease inhibitors
(2024-06-01)
Jitonnom, Jitrayut
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Meelua, Wijitra
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Tue-nguen, Panthip
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Saparpakorn, Patchreenart
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Hannongbua, Supa
Global warming and climate change have made dengue disease a global health issue. More than 50 % of the world's population is at danger of dengue virus (DENV) infection, according to the World Health Organization (WHO). Therefore, a clinically approved dengue fever vaccination and effective treatment are needed. Peptide medication development is new pharmaceutical research. Here we intend to recognize the structural features inhibiting the DENV NS2B/NS3 serine protease for a series of peptide-hybrid inhibitors (R<inf>1</inf>–R<inf>2</inf>-Lys-R<inf>3</inf>-NH<inf>2</inf>) by the 3D-QSAR technique. Comparative molecular field analysis (q2 = 0.613, r2 = 0.938, r2<inf>pred</inf> = 0.820) and comparative molecular similarity indices analysis (q2 = 0.640, r2 = 0.928, r2<inf>pred</inf> = 0.693) were established, revealing minor, electropositive, H-bond acceptor groups at the R<inf>1</inf> position, minor, electropositive, H-bond donor groups at the R<inf>2</inf> position, and bulky, hydrophobic groups at the R<inf>3</inf> position for higher inhibitory activity. Docking studies revealed extensive H-bond and hydrophobic interactions in the binding of tripeptide analogues to the NS2B/NS3 protease. This study provides an insight into the key structural features for the design of peptide-based inhibitors of DENV NS2B/NS3 protease.
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StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors
(2021-10-01)
Malik, Aijaz Ahmad
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Chotpatiwetchkul, Warot
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Phanus-umporn, Chuleeporn
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Nantasenamat, Chanin
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Charoenkwan, Phasit
Fast and accurate identification of inhibitors with potency against HCV NS5B polymerase is currently a challenging task. As conventional experimental methods is the gold standard method for the design and development of new HCV inhibitors, they often require costly investment of time and resources. In this study, we develop a novel machine learning-based meta-predictor (termed StackHCV) for accurate and large-scale identification of HCV inhibitors. Unlike the existing method, which is based on single-feature-based approach, we first constructed a pool of various baseline models by employing a wide range of heterogeneous molecular fingerprints with five popular machine learning algorithms (k-nearest neighbor, multi-layer perceptron, partial least squares, random forest and support vectors machine). Secondly, we integrated these baseline models in order to develop the final meta-based model by means of the stacking strategy. Extensive benchmarking experiments showed that StackHCV achieved a more accurate and stable performance as compared to its constituent baseline models on the training dataset and also outperformed the existing predictor on the independent test dataset. To facilitate the high-throughput identification of HCV inhibitors, we built a web server that can be freely accessed at http://camt.pythonanywhere.com/StackHCV. It is expected that StackHCV could be a useful tool for fast and precise identification of potential drugs against HCV NS5B particularly for liver cancer therapy and other clinical applications.
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Synthesis and Anti-Plant Pathogenic Fungal Activity of Flavokawain-Derived Flavones and Related Flavones Against Rhizoctonia solani
(2024-01-03)
Onnom, Panuwat
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Chotpatiwetchkul, Warot
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Meesin, Jatuporn
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Thapanapongworakul, Pilunthana
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Kittiwongwattana, Chokchai
Flavones are organic compounds in the flavonoid family that have a diverse range of biological functions. In this research, many flavones with various substituents were designed and synthesized from flavokawains A, B, and C, and their chalcone derivatives via an iodinecatalyzed oxidative cyclization process. All synthetic flavones were investigated for antifungal activities against Rhizoctonia solani, a plant pathogenic fungus. At 400 µg, most of the substances did not inhibit the tested species and R. solani growth was inhibited by only obromoflavone (40) by 74.88±0.91%. This indicated that the detrimental effect of flavones depends on the type and position of substituent, with the ortho bromo group showing the most promise. The molecular docking study on the succinate dehydrogenase (SDH) enzyme revealed that the bromophenyl moiety (ring B) is a key molecular substructure of the flavone fungicide. The findings of this study will be used to develop novel plant pathogenic fungicides.
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Bioassay-Guided Extraction and Isolation of Natural Herbicides from Dried Zanthoxylum limonella Alston Fruits
(2025-01-01)
Chotpatiwetchkul, Warot
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Charoenying, Patchanee
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Teerarak, Montinee
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Meesin, Jatuporn
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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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Investigation on the interactions between glucomannans and bifidobacterium protein by using molecular dynamics simulations
(2018-01-01)
Jensupakarn, Napassorn
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Chotpatiwetchkul, Warot
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Gleeson, Duangkamol
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Boonyarattanakalin, Kanokthip
Konjac glucomannan is a polysaccharide extracted from the Amorphophallus konjac K.Koch plant. It is often used as food additives due to their low toxicity, biodegradability and low calories. The unique properties of konjac glucomannan is its prebiotic activities. Konjac glucomannan which cannot be digested and absorbed in human stomachs and small intestines. Therefore, it is fermented in the large intestine and becomes food for the beneficial bacteria or probiotics especially bifidobacteria and lactobacilli in human colons. This study examined the effect of the size of konjac glucomannan on the prebiotic property. The interactions between the different degrees of polymerization of konjac glucomannan and Bifidobacterium protein were investigated in 0.15 M sodium chloride solution at 310 K by using molecular dynamics simulation. The results have shown that water molecules dramatically affect the alignment of konjac glucomannan in the system. The active site of Bifidobacterium protein that determined by the calculations are composed of ASP154, ARG49, ASN206, and ASN401. The lowest flexibility of GM5 structure shows strong interactions with Bifidobacterium protein. The most suitable size of konjac glucomannan that can bind with the protein has the degrees of polymerization no more than 8.
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Design, Synthesis, and Herbicidal Activity of Novel Dihydrochalcones Derived from Flavokawains and Their Analogs
(2026-05-01)
Poprom, Suriyaphong
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Meesin, Jatuporn
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Chotpatiwetchkul, Warot
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Waratchareeyakul, Watcharee
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Chotsaeng, Nawasit
Weeds are a major cause of crop production losses worldwide, and environmentally friendly chemical control based on natural or semisynthetic compounds has attracted increasing attention. In this study, flavokawains, a class of natural chalcones, and their analogues were converted into dihydrochalcones (1–27) via Pd-catalyzed hydrogenation. The herbicidal activities of these compounds were evaluated against Chinese amaranth (Amaranthus tricolor) and barnyard grass (Echinochloa crus-galli). Several compounds significantly inhibited seed germination and seedling growth in both species. Herbicidal activity was strongly influenced by the type and position of aromatic substituents, with electron-withdrawing groups and meta substitution providing higher activity. The meta-chloro derivative (15) exhibited the highest activity, markedly inhibiting seed germination as well as shoot and root growth. Further investigation of its mode of action revealed that this compound interfered with seed imbibition, inhibited α-amylase activity, and affected membrane integrity and malondialdehyde (MDA) levels in A. tricolor in a concentration-dependent manner. These findings provide valuable insights for the development of natural product-derived herbicides.
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A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides
(2021-12-01)
Charoenkwan, Phasit
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Chotpatiwetchkul, Warot
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Lee, Vannajan Sanghiran
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Nantasenamat, Chanin
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Shoombuatong, Watshara
Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906–0.910) and 2–17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.
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What make malarial adenosine deaminase from PLASMODIUM VIVAX recognise adenosine and 5′-methylthioadenosine: simulation studies
(2023-01-01)
Chotpatiwetchkul, Warot
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Sittiwanichai, Sirin
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Niramitranon, Jitti
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Pongprayoon, Prapasiri
Malaria is a life-threatening disease in humans caused by Plasmodium parasites. Plasmodium vivax (P. vivax) is one of the prevalent species found worldwide. An increase in an anti-malarial drug resistance suggests the urgent need for new drugs. Zn2+-containing adenosine deaminase (ADA) is a promising drug target because the ADA inhibition is fatal to the parasite. Malarial ADA accepts both adenosine (ADN) and 5′-methylthioadenosine (MTA) as substrates. The understanding of the substrate binding becomes crucial for an anti-malarial drug development. In this work, ADA from P. vivax (pvADA) is of interest due to its prevalence worldwide. The binding of ADN and MTA are studied here using Molecular Dynamics (MD) simulations. Upon binding, the open and closed states of pvADA are captured. The displacement of (Formula presented.) 7, linking loops of (Formula presented.) 3/ (Formula presented.) 12, (Formula presented.) 4/ (Formula presented.) 13, (Formula presented.) 5/ (Formula presented.) 15, and (Formula presented.) / (Formula presented.) 11 is involved in the cavity closure and opening. Also, the inappropriate substrate orientation induces a failure in a complete cavity closure. Interactions with D46, D172, S280, D310, and D311 are important for ADN binding, whereas only hydrogen bonds with D172 and D311 are sufficient to anchor MTA inside the pocket. No Zn2+-coordinated histidine residues is acquired for substrate binding. D172 is found to play a role in ribose moiety recognition, while D311 is crucial for trapping the amine group of an adenine ring towards the Zn2+ site. Comparing between ADN and MTA, the additional interaction between D310 and an amine nitrogen on ADN supports a tighter fit that may facilitate the deamination. Communicated by Ramaswamy H. Sarma.
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CO2photoreduction on mixed Ti/Zr-MOF-525: bicarbonate as the active intermediate and the role of Ti substitution
(2026-02-11)
Puengpoka, Thanyaporn
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Santatiwongchai, Jirapat
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Chotpatiwetchkul, Warot
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Bureekaew, Sareeya
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Saleh, Muhammad
The photocatalytic reduction of CO<inf>2</inf> in metal–organic frameworks (MOFs) offers a sustainable route to C<inf>1</inf> fuels and chemicals. Herein, density functional theory (DFT) calculations elucidate CO<inf>2</inf> reduction on mixed Ti/Zr-MOF-525 clusters bearing missing linker defects, modeled by Zr<inf>6</inf>, Ti<inf>1</inf>Zr<inf>5</inf>, and Ti<inf>2</inf>Zr<inf>4</inf> clusters. Two distinct mechanistic pathways are identified: the OH-passive and OH-assisted routes. In the passive case, CO<inf>2</inf> binds weakly at a coordinatively unsaturated Ti/Zr site and undergoes direct hydrogenation to CO and HCOOH, with desorption being thermodynamically preferred over further hydrogenation. In contrast, the OH-assisted pathway proceeds via a bicarbonate-mediated mechanism, where surface –OH attacks adsorbed CO<inf>2</inf> to form node-bound *HCO<inf>3</inf>. This step is both thermodynamically favorable and kinetically accessible (ΔG‡ < 0.5 eV). Subsequent proton-electron additions convert *HCO<inf>3</inf> to *OCHO and H<inf>2</inf>O, favored by ∼1 eV over competing routes. These findings identify *HCO<inf>3</inf> as the true reactive precursor and reveal that Ti substitution promotes deeper hydrogenation beyond two-electron products, enhancing CH<inf>4</inf> formation on the Ti<inf>2</inf>Zr<inf>4</inf> cluster. Overall, the results highlight the importance of node composition and surface hydroxyl groups in porphyrinic MOFs for optimizing multi-electron CO<inf>2</inf> reduction and controlling product selectivity by tailoring the metal node environments.
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Hydrogenation of CO2 to formic acid catalyzed by Co and Cu Single-atom catalysts supported on MOF-808: A DFT investigation
(2024-12-01)
Kusonjariyakun, Nawarat
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Santatiwongchai, Jirapat
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Meeprasert, Jittima
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Chotpatiwetchkul, Warot
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Maihom, Thana
In this work, DFT-based calculations and microkinetic modeling were employed to investigate CO<inf>2</inf> hydrogenation to formic acid using H<inf>2</inf> over Co and Cu single-atom catalysts supported on MOF-808. We investigated two pathways: one without the introduction of a second H<inf>2</inf> molecule (pathway A) and another one with it (pathway B). Pathway B, which involves introducing the second H<inf>2</inf> molecule alongside the formate intermediate from the first step, exhibits significantly lower energy barriers (three times lower) for the transformation into formic acid in the second step of CO<inf>2</inf> hydrogenation. Moreover, pathway B shifts the reaction thermodynamics from endergonic to exergonic, highlighting its kinetic and thermodynamic advantages. Notably, we observed formate intermediates with quasi-bidentate geometry alongside the prevalent bidentate chelating geometry. Cu2+-MOF-808 exhibits superior catalytic activity compared to Co2+-MOF-808, attributed to Cu's stronger preference for stabilizing the transition state in its square planar geometry through the Jahn-Teller effect, which is less effective in Co. Furthermore, our microkinetic modeling consistently confirms that Cu2+-MOF-808 outperforms Co2+-MOF-808 at lower temperatures, with the rate of formic acid production depending on the concentration of H<inf>2</inf>. The desorption of formic acid is identified as the rate-determining step of the reaction, significantly impacting overall efficiency.
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Chotpatiwetchkul, Warot

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