915-05-9Relevant articles and documents
Extraction, Isolation and Characterization of Valuable Worked on Acacia Tortilis
Muhaisen, Hasan M. H.
, p. 6731 - 6747 (2021/11/01)
Acacia tortilis is one of the important species of genus Acacia belonging to family Leguminaceae. Though there is no more study performed on this plant but it plays important role in the countries where it found. These countries include North Africa, Arabian Peninsula and Asian countries. The various part of Acacia tortilis plant say leaves, pods, gum exudates and bark were used as antidiabetic, antidiarrhoeal, antiasthmatic and also had several other medicinal benefits. The present discussion deals with the isolation and characterization of the following compounds from the leaves of Acacia tortilis. Lupan-3-ol, 12,20-diene, Lupan-12, 20-dien 3-one, Friedelin, ?-amyrin, ?- sitosterol, Apigenin, Luteolin, Quercetin, 5,7-dihydroxy-4-p-methyl benzylisoflavone, Vitexin, 2',6'-dihydroxy chalcone-4'-O-glucoside.
Modeling Antibacterial Activity with Machine Learning and Fusion of Chemical Structure Information with Microorganism Metabolic Networks
Nocedo-Mena, Deyani,Cornelio, Carlos,Camacho-Corona, María Del Rayo,Garza-González, Elvira,Waksman De Torres, Noemi,Arrasate, Sonia,Sotomayor, Nuria,Lete, Esther,González-Díaz, Humbert
, p. 1109 - 1120 (2019/03/19)
Predicting the activity of new chemical compounds over pathogenic microorganisms with different metabolic reaction networks (MRNs) is an important goal due to the different susceptibility to antibiotics. The ChEMBL database contains >160 000 outcomes of preclinical assays of antimicrobial activity for 55 931 compounds with >365 parameters of activity (MIC, IC50, etc.) and >90 bacteria strains of >25 bacterial species. In addition, the Leong and Barabàsi data set includes >40 MRNs of microorganisms. However, there are no models able to predict antibacterial activity for multiple assays considering both drug and MRN structures at the same time. In this work, we combined perturbation theory, machine learning, and information fusion techniques to develop the first PTMLIF model. The best linear model found presented values of specificity = 90.31/90.40 and sensitivity = 88.14/88.07 in training/validation series. We carried out a comparison to nonlinear artificial neural network (ANN) techniques and previous models from the literature. Next, we illustrated the practical use of the model with an experimental case of study. We reported for the first time the isolation and characterization of terpenes from the plant Cissus incisa. The antibacterial activity of the terpenes was experimentally determined. The more active compounds were phytol and α-amyrin, with MIC = 100 μg/mL for Vancomycin-resistant Enterococcus faecium and Acinetobacter baumannii resistant to carbapenems. These compounds are already known from other sources. However, they have been isolated and evaluated for the first time here against several strains of multidrug-resistant bacteria including World Health Organization (WHO) priority pathogens. Last, we used the model to predict the activity of these compounds versus other microorganisms with different MRNs in order to find other potential targets.
Phytochemical investigation and characterization of isolated chemical constituents from Kyllinga triceps Rottb.
Verma, Nishant,Jha,Ahmad, Shamim,Chaudhary, Sudhir,Ali, Mohammad
, p. 1393 - 1400 (2017/05/02)
Four compounds have been isolated by column chromatography from Kyllinga triceps namely quercetin dihydrate (1), rutin (2), β-sitosterol (3) and stigmasterol (4). Their structures have been elucidated by, FTIR, HR-EIMS, 1H NMR and 13C NMR spectroscopic studies.
