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Home > Eco-Friendly Synthesis of Thiazolidinone Derivatives and Their Biological Studies

Eco-Friendly Synthesis of Thiazolidinone Derivatives and Their Biological Studies

Thesis Info

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Author

Naeem, Muhammad

Program

PhD

Institute

University of the Punjab

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2010

Thesis Completion Status

Completed

Subject

Social sciences

Language

English

Link

http://prr.hec.gov.pk/jspui/handle/123456789/1033

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676724640416

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Microwave heating, ionic liquids and solid phase catalysts were employed and studied for the preparation of various 4-thiazolidinone derivatives and for “in vitro” antibacterial and antifungal activity. These techniques revealed several advantages over the conventional methods. In combination with microwave radiation, ionic liquids were used as phase transfer catalysts (PTC) and montmorillonite clays (K10 and KSF types) were used as solid phase catalysts. The catalytic efficiency of montmorillonite KSF was marginally inferior to that of montmorillonite K10. Compounds pertaining to main six different series were synthesized. In the first series; two methods Microwave procedure-I: Multi-Component Reaction in DMF and Microwave procedure-II: Solvent free, Multi- Component Reaction were used and it was found that first was better in yield ranging from 82.4% to 96.0% while yield in procedure-II ranging from 42.6% to 84.6%. The compound 4,6-dimethylpyrimidin-2-amine was treated with disubstituted aromatic aldehydes in dimethylformamide to form a Schiff base and Schiff base was further treated with sulfanyl acetic acid under microwave radiation to obtain the compounds (88-97). The compounds of first series were synthesized and elucidated as 2-(2,4-dimethylphenyl)-3-(4,6-dimethylpyrimidin-2-yl)-thiazolidin-4-one (88), 3- (4,6-dimethylpyrimidin-2-yl)-2-(2-hydroxy-4-methylphenyl)-thiazolidin-4-one (89), 2- (2,4-dihydroxyphenyl)-3-(4,6-dimethylpyrimidin-2-yl)-thiazolidin-4-one (90), 2-(2,4- dichlorophenyl)-3-(4,6-dimethylpyrimidin-2-yl)-thiazolidin-4-one 3-(4,6- (91), dimethylpyrimidin-2-yl)-2-(2-hydroxy-4-methoxyphenyl)-thiazolidin-4-one (92), 2-(4- chloro-2-methylphenyl)-3-(4,6-dimethylpyrimidin-2-yl)-thiazolidin-4-one (93), 3-(4,6- dimethylpyrimidin-2-yl)-2-(4-fluorophenyl)-thiazolidin-4-one (94), 3-(4,6- dimethylpyrimidin-2-yl)-2-(4-nitrophenyl)-thiazolidin-4-one (95), 2-(2,4- difluorophenyl)-3-(4,6-dimethylpyrimidin-2-yl)-thiazolidin-4-one (96) and 2-(3- (dimethylamino)phenyl)-3-(4,6-dimethylpyrimidin-2-yl)- thiazolidin-4-one (97). In the second series (98-107); two methods Microwave procedure-I: Multi- Component Reaction using Montmorillonite Clays (K-10 and KSF) and Microwave procedure-II: Solvent free, Multi-Component Reaction were employed. First procedure was found better in yield ranging from (yield 78.4% to 94.1% with K-10 and 68.3% to 88.1% with KSF) while yield in second procedure ranging from 14.3% xii to 76.4%. In this procedure Schiff base was treated with mercaptoacetic acid under microwave radiation followed by the condensation reaction of aniline and substituted benzaldehydes. The compounds 2-(3,5-dimethylphenyl)-3-phenyl-thiazolidin-4-one (98), 2-(3-hydroxy-5-methoxyphenyl)-3-phenyl-thiazolidin-4-one (99), 2-(3-chloro-5- methylphenyl)-3-phenyl-thiazolidin-4-one (100), 2-(3,5-dichlorophenyl)-3-phenyl- thiazolidin-4-one (101), 2-(3-nitrophenyl)-3-phenyl-thiazolidin-4-one (102), 2-(3- ethoxyphenyl)-3-phenyl-thiazolidin-4-one thiazolidin-4-one (105), (104), (103), 2-(3-methoxyphenyl)-3-phenyl- 2-[3-(dimethylamino)phenyl]-3-phenyl-thiazolidin-4-one 2-(3,5-difluorophenyl)-3-phenyl-thiazolidin-4-one (106) and 2-(3,5- dihydroxyphenyl)-3-phenyl-thiazolidin-4-one (107) were obtained. For the compounds (108-117), two methods Microwave procedure-I: Ionic Liquids (PEG, TBAB and TEBAC) and Microwave procedure-II: Solvent free, Multi- Component Reaction were used. The second procedure was found better in yield and environmentally than Ionic Liquids (PEG, TBAB and TEBAC). The yield ranged from 33.4%-48.8% with TBAB, 33.5%-52.2% with PEG and 20.4%-32.4% with TEBAC while in solvent free procedure-II 66.8% to 92.8%. The compounds 1,3- dipyridin-2-ylthiourea, chloroacetic acid and different aromatic aldehydes were used for the preparation of compounds (108-117) of third series named as 5-benzylidene- 3-(pyridin-2-yl)-2-(pyridin-2-ylimino)-thiazolidin-4-one (108), 5-(4- methoxybenzylidene)-3-(pyridin-2-yl)-2-(pyridin-2-ylimino)-thiazolidin-4-one (109), 5- (2-hydroxy-4-methoxybenzylidene)-3-(pyridin-2-yl)-2-(pyridin-2-ylimino)-thiazolidin-4- one (110), 5-[4-(dimethylamino)benzylidene]-3-(pyridin-2-yl)-2-(pyridin-2-ylimino)- thiazolidin-4-one (111), 5-(2,4-dichlorobenzylidene)-3-(pyridin-2-yl)-2-(pyridin-2- ylimino)-thiazolidin-4-one (112), 5-(4-nitrobenzylidene)-3-(pyridin-2-yl)-2-(pyridin-2- ylimino)-thiazolidin-4-one (113), 5-(4-ethoxybenzylidene)-3-(pyridin-2-yl)-2-(pyridin- 2-ylimino)-thiazolidin-4-one (114), 5-(2,4-difluorobenzylidene)-3-(pyridin-2-yl)-2- (pyridin-2-ylimino)-thiazolidin-4-one (115), 5-(4-ethylbenzylidene)-3-(pyridin-2-yl)-2- (pyridin-2-ylimino)-thiazolidin-4-one (116) and 5-(1,3-benzodioxol-5-ylmethylidene)- 3-(pyridin-2-yl)-2-(pyridin-2-ylimino)-thiazolidin-4-one (117). In the forth series; two methods Microwave procedure-I: Multi-Component Reaction using Montmorillonite Clays (KSF and K-10) and Microwave procedure-II: Solvent free, Multi-Component Reaction were used and it was found that first was better in yield ranging from 78.8% to 96.1% with K-10 and 70.8% to 84.2% with KSF xiii while yield in second ranging from 34.6% to 78.8%. In this series compounds (118- 127) were synthesized by adopting environmentally safe procedure. (4-substituted- phenyl)methylidene]aniline was treated with sulfanyl(thioxo)acetic acid in the presence of montmorillonite clays under microwave radiation for ten to twelve minutes. The compounds (118-127) (5-benzylidene-3-phenyl-2-thioxo-thiazolidin-4- one (118), 5-(4-methylbenzylidene)-3-phenyl-2-thioxo-thiazolidin-4-one (119), 5-(4- methoxybenzylidene)-3-phenyl-2-thioxo-thiazolidin-4-one 5-(3-hydroxy-4- (120), methoxybenzylidene)-3-phenyl-2-thioxo-thiazolidin-4-one (121), (dimethylamino)benzylidene]-3-phenyl-2-thioxo-thiazolidin-4-one nitrobenzylidene)-3-phenyl-2-thioxo-thiazolidin-4-one yl)benzylidene]-3-phenyl-2-thioxo-thiazolidin-4-one 5-(4- (124), 5-[2-(furan-2- (125), (126) 5-(4- 5-(2,4- (123), dichlorobenzylidene)-3-phenyl-2-thioxo-thiazolidin-4-one ethoxybenzylidene)-3-phenyl-2-thioxo-thiazolidin-4-one (122), 5-[4- and 5-(2,4- difluorobenzylidene)-3-phenyl-2-thioxo-thiazolidin-4-one) (127) were synthesized. The compounds (128-137) of fifth series were prepared by using environmentally benign procedure and reaction time was also dramatically reduced. In this series two methods Microwave procedure-I: Multi-Component Reaction using Montmorillonite Clays (KSF and K-10) and Microwave procedure-II: Solvent free, Multi-Component Reaction were employed and procedure-I was found better in yield ranging yields ranging from 78.8% to 94.4% with K-10 and 68.9-% to 88.6% with KSF while yield in procedure-II ranging from 34.4% to 65.3%. Sulfanylacetic acid was reacted with (2,5-disubstituted-phenyl)methylidene-4-methoxypyrimidin-2-amine followed by the condensation between 4-methoxypyrimidin-2-amine and various aldehydes. The compounds 2-(2,5-dimethylphenyl)-3-(4-methoxypyrimidin-2-yl)- thiazolidin-4-one (128), 2-(4-ethylphenyl)-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4- one (129), 2-(4-methoxyphenyl)-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one (130), 2-(2-hydroxy-5-methoxyphenyl)-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one (131), 2-(4-ethoxyphenyl)-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one (132), 2-[4- (dimethylamino)phenyl]-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one (133), 2-(2,5- dichlorophenyl)-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one difluorophenyl)-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one (134), (135), 2-(2,5- 2-(2,5- dihydroxyphenyl)-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one (136), 2-[3-(furan-2- yl)phenyl]-3-(4-methoxypyrimidin-2-yl)-thiazolidin-4-one (137) were thus achieved.
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استفہام بمعنی امر

استفہام بمعنی امر

بسااوقات استفہام امر کے معنوں میں استعمال ہوتا ہے ۔ ذیل کی آیت:

"إِنَّمَا يُرِيدُ الشَّيْطَانُ أَنْ يُوقِعَ بَيْنَكُمُ الْعَدَاوَةَ وَالْبَغْضَاءَ فِي الْخَمْرِ وَالْمَيْسِرِ وَيَصُدَّكُمْ عَنْ ذِكْرِ اللَّهِ وَعَنِ الصَّلَاةِ فَهَلْ أَنْتُمْ مُنْتَهُونَ"۔ [[1]]

"شیطان تو یہی چاہتا ہے کہ شراب اور جوئے کے ذریعے تمہارے درمیان دشمنی اور بغض کے بیج ڈال دے اور تمہیں اللہ کی یاد اور نماز سے روک دے ، اب بتاؤ کہ کیا تم ان چیزوں سے باز آ جاؤ گے"۔

اس آیت میں ’’فھل انتم منتھون ‘‘ در اصل ’’انتھوا عنھا‘‘ کے معنی میں مستعمل ہے ۔

"فَإِلَّمْ يَسْتَجِيبُوا لَكُمْ فَاعْلَمُوا أَنَّمَا أُنْزِلَ بِعِلْمِ اللَّهِ وَأَنْ لَا إِلَهَ إِلَّا هُوَ فَهَلْ أَنْتُمْ مُسْلِمُونَ"۔[[2]]

"اس کے بعد اگر یہ تمہاری بات قبول نہ کریں تو (اے لوگو) یقین کر لو کہ یہ وحی صرف اللہ کےحکم سے اتری ہےاور یہ کہ اللہ کے سوا کوئی عبادت کے لائق نہیں، تو کیا اب تم فرما بردار بنو گے"۔

جناب فلاحی کی رائے میں آیت مذکور میں ’’فھل انتم مسلمون‘‘ استفہام کے معنی میں نہیں بلکہ امر کے مفہوم میں استعمال ہوا ہے یعنی ’’اسلموا لھذا لاکتاب و آمنو ‘‘ ۔[[3]]

" قُلْ أَرَأَيْتُمْ إِنْ أَهْلَكَنِيَ اللَّهُ وَمَنْ مَعِيَ أَوْ رَحِمَنَا”[[4]]

"اے پیغمبر ان سے کہو کہ ذرا یہ بتلاؤ کہ چاہے اللہ مجھے اور میرے ساتھیوں کو ہلاک کر دے یا ہم پر رحم فرما دے"۔

قاضی ثناء اللہ پانی پتی کے مطابق ’’ارءیتم‘‘ میں ابتدائی ہمزہ استفہام تقریری کے لیے...

اسلامی نظام اقتصاد کی اخلاقیات تجارت ومعیشت میں دینی و اخلاقی اقدار کی اہمیت کے حوالے سے علمی و تحقیقی جائزہ

Islam is a holistic and comprehensive system of life because the Creator of universe has given the instructions that are eternal and are perfect guide for humanity in all ages and circumstances. Islamic teachings are consistent with the comprehensive nature. Those instructions that human being has given for all walks of life in that the elements of morality is distinct and dominant and prohibited every act that is harmful to others. This fact is quite clear that the moral aspect of Islam is so important to consider the ethics of Islam has taken into consideration and there is no command to be out of the realm of ethics and particularly matters of life which is part of religion and are important aspect of society. Islamic teachings are so clear that there is no example of it in any economic system the world. Today we have different economic systems in the world which essentially teach us that the purpose of human life is to make money and collect goods even if affects the lives of others. But in Islamic economic world it is emphasized that this world is not the original house and satisfactory zone of human being and his purpose is not to collect wealth but the worship of Almighty. Human being is gifted fair system of order in every aspect of which there is clearly ethics thus human is strictly prohibited to collect money through unfair means and in cruel manners. In this article we will discuss the ethical consideration of Islamic economical system. So it is quite clear that the guarantor of peace, love and harmony in the world is Islamic system.

Data Driven Modelling for Improved Water Management in Indus Basin

Proper water resources planning, development, and management need reliable forecasts of river flows. The trends of two hydrologic variables including precipitation and temperature and their effects on streamflow have been examined at the start of this thesis. Thirty years’ (1985 – 2014) data from eight climatic stations located in five subbasins (Skardu, Gupis, Gilgit, Drosh, and Astore) of the Upper Indus River Basin (UIRB) have been analysed. The climate station data were compared with the results of two General Circulation Models/ Global Climate Model (GCMs), BCC-CSM1-1and GFDL-CM3 (each with RCP 2.6 and RCP 8.5 scenario), in order to check their commonalities and differences. The statistical properties of the selected variables and their diversities linked with the characteristics of the UIRB were estimated using various stochastic techniques. The variation in the streamflow of Astore River, a tributary of Indus River, due to the impact of the changing trends of the two variables temperature and precipitation was assessed. The escalating temperature in three of the four seasons, as well as the increase in precipitation in the summer and spring seasons, will evidently result in longer summers and shorter winters. It will also produce an increasing runoff in the basin annually on a short-term basis whereas the runoff will decline in the distant future. In recent decades an important technique has been introduced in the prediction of the hydrologic phenomenon through artificial intelligence based modeling with several categories of models. In this thesis, the performance of three Artificial Neural Network (ANN) and four Support Vector Regression (SVR) models have been investigated to predict streamflow of the Astore River. Results from ANN models using three different optimization techniques namely Broyden-Fletcher-Goldfarb-Shannon, Conjugate Gradient, and Back Propagation were compared with one another. A further comparison was made between these ANN and four types of SVR models which were based on linear, polynomial, radial basis function, and the sigmoid kernels. Three types of input combinations with main input variables (temperature, precipitation, and streamflow) and several types of combinations with respect to time lag were tested. The best input for ANN and SVR models was identified using Correlation Coefficient Analysis, Monte Carlo Analysis (MCA) and Genetic Algorithm. The performance of the ANN and SVR models was evaluated by mean bias error and Nash-Sutcliffe efficiency. The efficiency of the Broyden-Fletcher-Goldfarb-Shannon -ANN model was found to be much better than that of the other models, while the SVR model based on radial basis function kernel predicted stream flows with comparatively higher accuracy than that of the other kernels. Finally, long-term predictions of streamflow have been made by the best ANN and Global Climate Model GCM. It was found that the stream flow of the selected river has increasing trends till mid-21stcentury and decreasing trend by the last decade of the century and even onwards. The result of GCMs reported values under the RCP 2.6 and RCP 8.5 scenarios showed almost the same pattern in the trends of the streamflow throughout the century with higher stream-flows predicted for RCP 8.5 scenario. Although observed data was used to test the data-driven models, this thesis also compares a Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) conceptual model and the ANN model coupled with conjugate gradient (CG) method to predict the streamflow. The results show that the hybrid ANN-CG model can predict streamflow very close to HEC-HMS. A parametric study was undertaken using MCA and found that the most important parameters for HEC-HMS models are the storage coefficient (S) and the time of concentration (tc); for ANN models, input combinations are the most important, which were determined by application of MCA to ANN first time. This study measures the uncertainty allied with these parameters and the outcomes that can be used to confine the range at which preliminary estimations are made in future modeling. Finally, the impact of any errors in streamflow predictions on flowduration curves (FDC) has been investigated. It is noticed that the FDCs are significantly affected by any inaccuracy in simulating the streamflow. The FDC evaluated that extreme event (floods and low flows) are expected in the selected river basin in near and distant future. All the above techniques applied to predict the streamflow in UIB shows that there will be an increase in the water availability in the short term but the streamflow will decrease in the long term. Any changes in the streamflow will obviously change the level of water in reservoirs downstream of study area, especially the Tarbela reservoir located on the downstream of UIRB, which will require changing the reservoir operating policy for better management of available water. This thesis has provided comprehensive data for current and future sustainable water resources management within the basin. Keywords: Water resource management, Artificial Neural Network, Climate change, CUSUM test, Flow Duration Curves, Genetic Algorithm, HEC-HMS, Mann-Kendall test, Monte Carlo Analysis, River Indus, Rank sum test, Sen’s slope test, Short-term Streamflow Forecast, Support Vector Machine, Sensitivity Analysis, Tarbela, Trend analysis.