Albizia chinensis Osbeck. Merr. (Family: Fabaceae) is quite abundant in Bangladesh. The plant has a history of its traditional use in scorpion and snake bite. This investigation was designed to analyze the analgesic, anti-diarrheal and anti-inflammatory potentials along with sleep inducing property of the crude methanol extract of stem bark of Albizia chinensis Osbeck. Merr. Peripheral analgesic activity was evaluated by inducing pain through intraperitoneal administration of acetic acid in writhing test. Tail-flick test protocol was followed to determine central analgesic activity. The tail flicking response to thermal stimulus was measured in this assay. A. chinensis extract was also tested for anti-diarrheal activity by inducing castor oil-induced diarrhea in Swiss albino mice model. Phenobarbitone-sodium induced sleeping time was determined to assess CNS depressant activity. The crude methanol extract (400 mg/kg body weight) demonstrated 85.71% inhibition of writhing as compared to 74.49% by diclofenac sodium. The crude extract (400 mg/kg dose) reduced diarrheal feces by 69.05% and revealed 53.03% elongation of the reaction time after 30 min of administration in tail flick test. At the same dose, the crude methanol extract exhibited 91.49% inhibition of rat paw edema at the 4 th h of carrageenan injection. The phytocomponents responsible for observed activity should be isolated and involved in further assessment.

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Background: Natural products have been a rich source of compounds for drug discovery. Usually, compounds obtained from natural sources have little or no side effects, thus searching for new lead compounds from traditionally used plant species is still a rational strategy. Introduction: Natural products serve as a useful repository of compounds for new drugs; however, their use has been decreasing, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. To address this unmet demand, we have developed and validated a high throughput in silico machine learning screening method to identify potential compounds from natural sources. Methods: In the current study, three machine learning approaches, including Support Vector Machine (SVM), Random Forest (RF) and Gradient Boosting Machine (GBM) have been applied to develop the classification model. The model was generated using the cyclooxygenase-2 (COX-2) inhibitors reported in the ChEMBL database. The developed model was validated by evaluating the accuracy, sensitivity, specificity, Matthews correlation coefficient and Cohen’s kappa statistic of the test set. The molecular docking study was conducted on AutoDock vina and the results were analyzed in PyMOL. Results: The accuracy of the model for SVM, RF and GBM was found to be 75.40 %, 74.97 % and 74.60 %, respectively which indicates the good performance of the developed model. Further, the model has demonstrated good sensitivity (61.25 % - 68.60 %) and excellent specificity (77.72 %- 81.41 %). Application of the model on the NuBBE database, a repository of natural compounds, led us to identify a natural compound, enhydrin possessing analgesic and anti-inflammatory activities. The ML methods and the molecular docking study suggest that enhydrin likely demonstrates its analgesic and anti-inflammatory actions by inhibiting COX-2. Conclusion: Our developed and validated in silico high throughput ML screening methods may assist in identifying drug-like compounds from natural sources.

Background: The composition and bioactivity of natural plant extracts strongly depend on the extraction technique employed. Clinacanthus nutans Lindau (C. nutans) is a well-known medicinal plant in South-East Asia that has been traditionally used for the treatment of various diseases. Several conventional methods have been using for extraction of bioactive compounds from C. nutans. However, extraction of fatty acids using supercritical carbon dioxide was not reported yet from this medicinal herbs. Objective: The main objective of the study is to examine the potential of supercritical carbon dioxide (scCO2) extraction of fatty acids from leaves and stems of C. nutans. Method: Fatty acid compositions were determined from leaves and stems of C. nutans oil extracted by scCO2 (temperature 45-65 °C, pressure 25-35 MPa), and compared to the results of Soxhlet extraction. Results: Supercritical CO2 extraction shows the highest oil recovery in both leaves (3.7%) and stems (1.6%) at pressure 35 MPa, temperature 65 °C and 2 ml/min flow rate, which was closer to the yield of Soxhlet. The scCO2 yields presented a higher percentage of polyunsaturated fatty acids (PUFA), especially linoleic acid (C18:2n-6). Palmitic acid ranging from 42%- 47% in leaves and stems of C. nutans was found dominant saturated fatty acids (SFA) in both scCO2 and Soxhlet method. Conclusion: The current results indicate that leaves and stems of C. nutans could be a potential source of fatty acids especially biologically active compounds.Conclusion: The current results indicate that leaves and stems of C. nutans could be a potential source of fatty acids especially biologically active compounds.