Home > Bioassay Guided Isolation and Characterization of Secondary Metabolites from Isodon Rugosus Wall. Ex Benth. and Their Anti-Nociceptive Activities
Bioassay Guided Isolation and Characterization of Secondary Metabolites from Isodon Rugosus Wall. Ex Benth. and Their Anti-Nociceptive Activities
Isodon rugosus Wall.ex Benth. is widely employed in folk medicine to cure various types of pain conditions like dental, gastric, abdominal, ear pain and rheumatism. In this thesis, we have explored the analgesic potential of Isodon rugosus, to isolate the active compounds responsible for analgesic activity and to figure out its possible mechanism of action. The bioassay guided isolation was followed to obtain analgesic compound from Isodon rugosus. Preliminary phytochemical evaluation was carried out for the presence of various secondary metabolites in Isodon rugosus. Initially, the analgesic activity was performed using methanolic extract and subsequent fractions. The chloroform fraction was sorted out as most active following various analgesic activities. The isolation of analgesic compounds was carried out from chloroform fraction by using gravity column chromatography, in which thin layer chromatography and various stains were employed for confirmation of single and pure spots of compounds. At the end, three (3) compounds (AZ-1, AZ-2 and AZ-3) were isolated from chloroform fraction of Isodon rugosus in pure form. The pure compounds were then subjected to various analytical techniques for identification purposes including 1HNMR, 13CNMR and MS. The compound AZ-1 and AZ-2 were in sufficient quantity and were subjected to evaluate their analgesic potential following various standard protocols. In acetic acid induced writhing test, the compound AZ-1 showed 61% inhibition whileAZ-2 showed 4% inhibition of pain. In formalin test, AZ-1at 50 mg/kg displayed 69 and 63% inhibitions at phase-I and phase-II respectively. Similarly, the compound AZ-2at a similar dose, i.e. 50 mg/kg displayed 8 and 13% inhibitions at early and late phase respectively. In hot plate test,AZ-1 and AZ-2 exhibited average reaction times of 8 min and 3 min respectively. The possible mechanism of action of AZ-1 was figured out using different receptors including opioid, dopaminergic and adrenergic receptors. Moreover, the AZ-1 2 was also assessed against enzymes lipoxygenase and cyclooxygenase, which have a prominent role in nociception. The mechanistic study revealed that AZ-1 was actively involved in the anti-nociception through opioid receptors. The possible mechanism of analgesic action was confirmed to be the central pathway using opioid receptors, because the mice showed activity as that of morphine after the administration of opioid antagonist naloxone. The involvement of opioids receptors is evident from both hot plate and formalin assays in which nalaxone was used to figure out the involvement of opioids receptors. The AZ-1 was also involved in anti-nociception through adrenergic receptor and showed the reaction time of 5.35± 0.66, 5.17± 0.53, 6.53± 0.68, 5.90± 0.58 and 4.63±0.56 at the interval of 15, 30, 45, 60 and 90 min respectively. The involvement of adrenergic receptor shown by the pre-treatment of adrenergic antagonist (yohimbine) which reversed the activity of AZ-1. Moreover,AZ-1 was also active against cyclo-oxygenase and lipoxygenase enzymes. The positive control used was Zileuton in lipoxygenase assay, in which the AZ-1 demonstrated 49.40± 0.65, 42.37± 0.72, 36.87± 1.04, 31.80± 0.55 and 26.97± 1.49% inhibitions at concentrations of 1000, 500, 250, 125 and 62.5 μg/ml respectively having IC50of 1024 μg/ml. The celecoxib was used as positive control in cyclo-oxygenase in which AZ-1 showed 42.77± 0.82, 38.87± 0.70, 32.73± 0.95, 28.60± 1.19 and 21.70± 1.57% inhibitions at concentration of 1000, 500, 250, 125 and 62.5 μg/ml respectively with IC50 1423μg/ml. The antioxidant properties of Isodon rugosus was also explored using various free radicals assays such as DPPH, H2O2 and ABTS. In DPPH, H2O2 and ABTS assays, AZ-1 revealed 56.33± 0.89, 49.33± 0.33 and 59.33± 0.33% inhibitions respectively at 1000 μg/ml concentration each. Additionally, the essential oil of Isodon rugosus (Ir.Eo) was also isolated and was subjected to GC coupled MS analysis. A total of 141 compounds found in the essential oil of Isodon rugosus. 3 The essential oil was also subjected to anti-nociceptive and antioxidant activity to find out it role in pain. The Ir.Eo showed a comparative response of the sample (57.14%) with the positive control (70.29%) at the dose of 100 mg/kg. The Ir.Eo in combination with naloxone reduced 09.01and 07.95% pain in phase I and II respectively. Mean reaction time for a sample of Ir.Eo and naloxone at a dose ratio of 50 + 1 mg/kg body weight was figured out as 05.28 ±0.13 min. Similarly, in DPPH and ABTS assay Ir.Eo revealed IC50 of <0.1 μg/ml. In brief, AZ-1 was revealed as an active anti-nociceptive compound of Isodon rugosus. This compound should further be subjected to various investigations which can help in drug discovery.
پنڈت ہردے ناتھ کنزرو یہ سطریں لکھی جارہی تھیں کہ پنڈت ہردنے ناتھ کنزرد کی وفات کی خبر ملی، انھوں نے بڑی لمبی عمر پائی، نوے سال کے تھے، وہ ایک جلیل القدر، مرنجان مرنج، بامروت، وضعدار شخصیت، پارلیمانی دستور کے بڑے ماہر ہندو مسلمان کی ملی جلی تہذیب کے عمدہ نمونہ اور اردو زبان کے بڑے محسن کی حیثیت سے برابر یاد کئے جائیں گے، وہ اپنی ترشی ہوئی بھلمنساہت کی وجہ سے ہندوستان کی سیاست کی جذباتی ہم آہنگی کے قابل تقلید نمونہ بن سکتے ہیں، بشرطیکہ موجودہ قومی دھارے کے بنانے والے ان کو ایسا ہی سمجھیں۔ (’صباح الدین عبدالرحمن، اپریل ۱۹۷۸ء)
Based on the 2013 curriculum 2016’s revision, there are subject materials that demand about local content in English subjects at the level of SMP Class VII. Teachers need many researches and practices integrating and implementating these subjects. Basically, it needs to be done in-depth study in the form of content analysis. This research was conducted on content and learning English in SMP Negeri 5 Sigi. This study aims to find out 1) how many percentage of local content in English lesson material Class VII SMP in the curriculum 2013 revision 2016; 2) how to integrate local content in English subject matter in SMP Negeri 5 Sigi; 3) how the implementation of material with local content in English learning in SMP Negeri 5 Sigi, and; 4) how to integrate local content in effective and efficient English lessons in SMP Negeri 5 Sigi. The study used a qualitative descriptive approach with the method of collecting document studies, interviews, and observation. The research results are 1) the proportion of local content that can be integrated into English language learning material SMP is 95%; 2) the integrity of local content in English learning materials in SMP Negeri 5 Sigi can be found in the lesson plan; 3) implementation of materials with local content in English learning attached to KTSP, Syllabus, lesson plan and learning resources enrichment book.
Protein sequence similarity is commonly used to compare proteins, and to search for proteins similar to a query protein. With the growing use of biomedical ontologies, especially Gene Ontology (GO), semantic similarity between ontology terms, proteins and genes is getting attention of researchers. Protein semantic similarity measurement has many applications in bioinformatics, including protein function prediction and protein-protein interactions. Semantic similarity measures were proposed by Resnik, Jiang and Conrath, and Lin. Recent measures include Wang and AIC. The question whether the semantic similarity has a strong correlation with sequence similarity, has been addressed by some authors. It has been reported that such correlation exists, and it has been used for the evaluation of semantic similarity computation methods as well as for protein function prediction. We investigate the correlation between semantic similarity and sequence similarity using graphs, Pearson''s correlation coe cient and example proteins. Wend that there is no strong correlation between the two similarity measures. Pearson''s correlation coef- cient is not su cient to explain the nature of this relationship, if not accompanied by graph analysis. Wend that there are several pairs with low sequence similarity and high semantic similarity, but very few pairs with high sequence similarity and low semantic similarity. Interestingly, the correlation coe cient depends only on the number of common GO terms in proteins under comparison. We propose a novel method SemSim for semantic similarity measurement. It addresses the limitations of existing methods, and computes similarity in two steps. In therst step, SimGIC like approach is used where contribution of common ancestors is divided by contribution of all ancestors. In the second step, we use two new factors: Speci city computed from ontology based information content, and Uniqueness computed from annotation based information content. Thenal result, after applying these two factors, makes clear distinction between the generalized and specialized terms. We conducted experiments on protein pairs having evidence of high similarity, and the ones having evidence of low similarity. Experiments show that SemSim performs better than the previous measures in both cases. When semantic similarity is used for searching proteins from large databases, the speed issue becomes signi cant. To search for proteins similar to a query protein having m annotations, from the database of p proteins, p m n g comparisons would be required. Here n is the average annotations per protein, g is the complexity of GO term similarity computation algorithm, and it is assumed that each term of one protein is compared with each term of the other. We propose a method SimExact that is suitable for high speed searching of semantically similar proteins. Although SimExact works on common terms only, our experiments show that it gives correct results required for protein semantic searching. SimExact can be used as a pre processor, generating candidate list for the existing methods, which proceed for further computation. Such arrangement will gain high speed while retaining the accuracy of the given method. We provide online tool that generates a ranked list of the proteins similar to a query protein, with a response time of less than 8 seconds in our setup. We use SimExact to search for protein pairs having high disparity between semantic similarity and sequence similarity. SimExact makes such searches possible, which would be NP-hard otherwise.