6-Octadecenoic and Oleic Acid in Liquid Smoke Rice Husk Showed COVID-19 Inhibitor Properties.

In recent years, liquid smoke rice husk (LSRH) has shown its therapeutic potency to diabetes, wound healing, stomatitis, and periodontitis. The phenol, 6-octadecenoic acid, oleic acid, and 9-octadecanoic acid were responsible for their therapeutic effect. The LSRH also demonstrated their potential for infectious diseases such as coronavirus disease (COVID-19). Therefore, the molecular dynamics (MDs) simulation and pharmacophore analysis was performed to analyse the binding stability of 6-octadecenoic and oleic acid. Based on MD simulation, 6-octadecenoic and oleic acids seemed to retain their interactions with Ser144 and Thr24, respectively, with hydrogen bond distance less than 2.9 Å. This interaction was stable during the simulation and has hydrophobic and hydrogen bonds/acceptors. The 6-octadecenoic acid and oleic acid were confirmed to have great potency as inhibitors for COVID-19. These compounds also showed that the existence of hydrophobic and hydrogen bonds/acceptors could increase biological activity.

Antifungal Potential of Secondary Metabolites Derived from Arcangelisia flava (L.) Merr.: An Analysis of In Silico Enzymatic Inhibition and In Vitro Efficacy against Candida Species.

Considering the escalating resistance to conventional antifungal medications, it is critical to identify novel compounds that can efficiently counteract this challenge. The purpose of this research was to elucidate the fungicidal properties of secondary metabolites derived from Arcangelisia flava, with a specific focus on their efficacy against Candida species. This study utilized a combination approach comprising laboratory simulations and experiments to discern and evaluate the biologically active constituents present in the dichloromethane extract of A. flava. The in vitro experiments demonstrated that compounds 1 (palmatine) and 2 (fibraurin) exhibited antifungal properties. The compounds exhibited minimum inhibitory concentrations (MICs) ranging from 15.62 to 62.5 µg/mL against Candida sp. Moreover, compound 1 demonstrated a minimum fungicidal concentration (MFC) of 62.5 µg/mL against Candida glabrata and C. krusei. In contrast, compound 2 exhibited an MFC of 125 µg/mL against both Candida species. Based on a molecular docking study, it was shown that compounds 1 and 2 have a binding free energy of -6.6377 and -6.7075 kcal/mol, respectively, which indicates a strong affinity and specificity for fungal enzymatic targets. This study utilized pharmacophore modeling and Density Functional Theory (DFT) simulations to better understand the interaction dynamics and structural properties crucial for antifungal activity. The findings underscore the potential of secondary metabolites derived from A. flava to act as a foundation for creating novel and highly efficient antifungal treatments, specifically targeting fungal diseases resistant to existing treatment methods. Thus, the results regarding these compounds can provide references for the next stage in antifungal drug design. Further investigation is necessary to thoroughly evaluate these natural substances' clinical feasibility and safety characteristics, which show great potential as antifungal agents.

α-glucosidase and α-amylase inhibitory activity of flavonols from Stenochlaena palustris (Burm.f.) Bedd.

Stenochlaena palustris (Burm.f.) Bedd., a fern species native to India, Southeast Asia, Polynesia, and Australia, has a long history of medical including as a diabetic therapy. This study aimed to isolate bioactive compounds from S. palustris ethyl acetate extract and assess their in vitro and in silico inhibitory activities against α-glucosidase and α-amylase. The successful separation of five flavonols, namely stenopalustroside A (1), tiliroside (2), kaempferol (3), quercetin (4), and rutin (5), was achieved through phytochemical analysis. The compounds exhibited a range of inhibitory activities against α-glucosidase and α-amylase, with IC50 values ranging from 40 to 250 µg/mL. Notably, the biological activities of compound 1 have been reported for the first time. Compound 4 was the most effective inhibitor of both enzymes among the isolated compounds. Studies performed in silico reveal that the interactions between amino acids in compounds 4 and 5 are remarkably comparable to those observed in the positive control. These compounds share this commonality, and as a result, they both have the potential to be active agents.

In Silico Study of Liquid Smoke Rice Husk against COVID-19.

OBJECTIVES: Liquid smoke rice husk has been researched and proved to consist of antibacterial, analgesic, anti-inflammatory, and growth factor stimulatory properties. By these complex properties, the liquid smoke rice hull is able to purpose as a novel coronavirus disease 2019 (COVID-19) inhibitor. The research was conducted to analyze the role of the dominant compound in rice husk liquid smoke against one of the main proteases in complex with inhibitor N3 of COVID-19 and 6LU7 protein data bank (PDB) ID. MATERIAL: AND METHODS: The Molecular Operating Environment (MOE) 2020.0901 (Chemical computing group) was used to analyzed the interaction. The molecular structure test, including phenol, mequinol, 2-methoxy-phenol, 6-octadecenoic acid, oleic acid, 9-cctadecenoic acid, was chosen. The lopinavir as positive control and 6LU7 as COVID-19 protein were chosen. All the protein analyses were conducted using docking molecular. RESULT: The phenol, 2-methoxy-phenol, mequinol and 9-octadecenoic acid have higher binding free energy that causes difficult to bind to the active site of protein 6LU7 (-3.4758, -3.5509, -3.6845, and -5.0173 kcal/mol, respectively). The minor component of liquid smoke, such as 6-octadecenoic acid and oleic acid, has the binding free energy (-5,5327 and -5,4208 kcal/mol) and more factor of binding presumably as active COVID-19 inhibitor. CONCLUSION: The liquid smoke rice husk has active component like 6-octadecenoic acid and oleic acid are presumably as active COVID-19 inhibitor.

Free Radical Scavenging, Anti-Infectious, and Toxicity Activities from Stenochlaena palustris (Burm.f.) Bedd. Extracts.

Stenochlaena palustris (Burm.f.) Bedd. (Blechnaceae) or Kelakai is a traditional medicinal plant found in the Indonesian islands of Borneo and Sumatra. It has been used to treat wound healing, infection, and diabetes. This study looked into the free radical scavenging activity, antiplasmodial activity, toxicity, and antibacterial activity against pathogenic bacteria. The species' aerial part was extracted with methanol, followed by a liquid-liquid extraction against (n-hexane, dichloromethane, and ethyl acetate). The extracts' free radical scavenging activities were determined using DPPH and NO radicals. The antiplasmodial and toxicity assays were conducted using two Plasmodium falciparum strains (3D7 and W2) and the brine shrimp lethality test. In addition, antibacterial activity was determined using the well diffusion method. The results revealed that ethyl acetate depicted potential activities toward the assay. The ethyl acetate showed potential free radical scavenging activities with an IC50 value of 51.63 ± 0.46 µg/mL (DPPH) and 60.03 ± 0.65 µg/mL (NO). The antiplasmodial activities showed that the ethyl acetate had potential activities among the extracts with an IC50 value of 11.06 ± 0.45 µg/mL. However, all the extracts demonstrated nontoxic toward Artemia salina with LC50 > 1000 µg/mL. Furthermore, the ethyl acetate demonstrated intermediate susceptibility against B. cereus ATCC 10876, V. parahaemolyticus ATCC 17802, L. monocytogenes ATCC 7644, and S. Typhimurium ATCC 14028 at a concentration of 500 µg/disc. According to these findings, the ethyl acetate extract of S. palustris (Burm.f.) Bedd is a promising source of natural antioxidants and antiplasmodial agents.

Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line.

The dataset of curcumin derivatives consists of 45 compounds (Table 1) with their anti cancer biological activity (IC50) against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r2 value, r2(CV) value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r2 values of 0.88 were obtained for the test set.

Design of new competitive dengue NS2B/NS3 protease inhibitors-a computational approach.

Dengue is a serious disease which has become a global health burden in the last decade. Currently, there are no approved vaccines or antiviral therapies to combat the disease. The increasing spread and severity of the dengue virus infection emphasizes the importance of drug discovery strategies that could efficiently and cost-effectively identify antiviral drug leads for development into potent drugs. To this effect, several computational approaches were applied in this work. Initially molecular docking studies of reference ligands to the DEN2 NS2B/NS3 serine protease were carried out. These reference ligands consist of reported competitive inhibitors extracted from Boesenbergia rotunda (i.e., 4-hydroxypanduratin A and panduratin A) and three other synthesized panduratin A derivative compounds (i.e., 246DA, 2446DA and 20H46DA). The design of new lead inhibitors was carried out in two stages. In the first stage, the enzyme complexed to the reference ligands was minimized and their complexation energies (i.e., sum of interaction energy and binding energy) were computed. New compounds as potential dengue inhibitors were then designed by putting various substituents successively on the benzyl ring A of the reference molecule. These substituted benzyl compounds were then computed for their enzyme-ligand complexation energies. New enzyme-ligand complexes, exhibiting the lowest complexation energies and closest to the computed energy for the reference compounds, were then chosen for the next stage manipulation and design, which involved substituting positions 4 and 5 of the benzyl ring A (positions 3 and 4 for 2446DA) with various substituents.

Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction.

Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR) method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT) activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r(2) value, r(2) (CV) value and r(2) prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC(50) values ranging from 0.39 µM to 7.04 µM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r(2) prediction for external test set) of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.