Nalini, C N (2009) Computational Design, Synthesis, Characterization and Pharmacological Evaluation of Some Piperidine Derivatives. Doctoral thesis, The Tamilnadu Dr. M.G.R. Medical University, Chennai.
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Abstract
The Aurora kinase family is a collection of highly related serine/threonine kinases that functions as a key regulator of mitosis. In mammalian cells, Aurora has evolved into three related kinases known as Aurora-A, Aurora-B, and Aurora-C. These kinases are over expressed in a number of human cancers, and transfection studies have established Aurora-A as a bone fide oncogene. Because Aurora over expression is associated with malignancy, these kinases have been targeted for cancer therapy. So in the present study, it was decided to design some inhibitory lead compounds of Aurora kinase A as using computational tools like Catalyst (pharmacophore modeling) and GLIDE(structure based drug design/Docking). Then the designed compounds were synthesized and screened for anticancer studies. Eighty two Aurora A kinase inhibitors from Medicinal Chemistry Journals were selected for modeling studies based on chemical and biological diversity. The selected molecules were then divided into 21 training set molecules and 61 test set molecules. Using the training set molecules pharmacophore models (hypothesis) were generated in Hypogen (Catalyst). The most active molecule in the training set fits very well with the top scoring pharmacophore hypothesis. The best hypothesis consists of one hydrogen bond acceptor, one hydrophobic aliphatic and two ring aromatics. The best hypothesis Hypo-1 is characterized by the highest cost difference (58 bits), lowest RMS deviation (1.30) with a correlation of 0.94. The best pharmacophore hypothesis was used to screen the 61 Aurora A Kinase inhibitors in the Aurora kinase inhibitor data base. The model developed was shown to be a good model with 0.65 as Goodness of Hit score (GH) and a enrichment factor of 1.154. GLIDE was the docking program used for the structure based drug design. The 82 Aurora A inhibitors used for the pharmacophore studies were considered for docking study to develop comparative model. Out of the 82 inhibitors 21 were used in the training set. Crystal structure of Aurora A (PDB code: Imq4) was employed for the docking studies Structure based docking studies were carried out using Glide on Aurora A kinase inhibitors to the 3D structure of Aurora A kinase and generated 50 best docking poses. The best poses were selected based on the scoring functions and poses orientation with the active site amino acids. To get a better VS model, a MLR analysis was carried out using pharmacophore model and the docking scoring function. A combination of Pharmacophore model, GLIDE SP dock score gave a good model. The VS model obtained was further used to search the virtual library consisting of 10,000 structurally diversified molecules generated using fragment and knowledge based design, which yielded 300 molecules as potent Hits. The hits obtained were used for PASS prediction studies. A consensus was obtained between the docking scores and the PASS prediction values and finally 40 Hits were selected for synthesis and screening. The docking scores >-7 and prediction values above 0.6 were taken into consideration. PASS predicted some of the molecules to be active against colorectal cancer (1A-29A) and some other molecules to be inhibitors of phosphatase enzyme (P1-P11). A Drug likeness screening was carried out for all the 40 Hits including Lipinski rule of five and Toxicity assessment. All most all the compounds exhibited 2 violations of the Lipinski rule which was found to be normal with anticancer drugs. It is proven that kinase inhibitors in general have high molecular weight and LogP values. So these violations were accepted in the present study. In toxicity assessment all the compounds showed Green colour code except nine molecules having nitro and dimethyl amino substitution exhibiting mutagenicity and Tumorigenicity. But still these molecules were also included in the in vitro screening because so many active scaffolds have these substructures and their activities were also predicted to be good. These hits can be further refined to reduce the unwanted reactions by including detoxifying sub structures. The designed molecules have piperidine-4-ones scaffold attached with 2-Aminopyrimidine (1A-29A) and 2-Pyrazoline (P1-P11) substructures. The Schiff bases and Mannich bases of piperidine-4-ones were synthesized according to the synthetic scheme and characterized by IR,1H NMR,13 C NMR, COSY NMR and Mass spectroscopy. The compounds were subjected to in vitro anticancer studies in colorectal cell lines (1A-29A).The compounds 21A and 25A show the least IC50 values 0.01 and 0.01 respectively. The compound 21A maintains the same level of activity through out the working range (0.01-100 μM). There is no concentration related gradation in the activity profile. In the case of compound 25A, the peak activity is noted in the minimum concentration of 0.01 μM itself. Even though there is a decrease in the activity with increase in the concentration, the activity profile remained well above the required level. The other compounds showing significant activity are 3A, 10A, 13A and 26A. The compounds 6A, 9A and 16A show less activity with IC50 values in the range of 10 μM. All the other compounds showed moderate activity with IC50 values in the range of 1-5 μM. The compounds P1-P11 were subjected to phosphatase inhibition activity. The compounds P1-P11 were used in three concentration levels (50/125/250mcg). The absorbances of these solutions were measured at 620nm after carrying out the assay with Folin’s reagent. The concentrations of the phenol formed in these solutions were obtained from the standard graph of phenol. From the analysis of the data it can be seen that all the compounds P1-P11 are possessing phosphatase inhibition activity. In addition to that they also show a gradation in their dose response. All the compounds show less inhibition at 50 mcg, moderate inhibition at 125 mcg and a fairly good inhibition at 250 mcg. The compounds P1-P11 have 2-pyrazoline moiety as a sub structure in common. The compounds P1-P5 at 50 mcg concentration level shows very less inhibition. A concentration dependent increase in inhibitory activity was observed with P1, P2, P3, P4, and P5. That is better inhibitory activity was observed with higher concentrations (250 mcg). The compounds P6-P11 showed better inhibition in all the three concentration levels. In all these compounds the C3 of piperidin-4-one ring contain isopropyl group which may contribute to the increase in inhibitory activity. Of all compounds, the compound P3 at the 250mcg concentration level shows best activity. Thus the compounds P3, P7 and P11 can be further developed to get effective phosphatase inhibitors. By arriving at the leads 21A and 25A for anticancer activity, the aim of the work to develop leads for anticancer activity was fulfilled. These analogues can be novel templates for lead optimization purpose in cancer chemotherapy. To conclude the anticancer leads obtained in this study can be refined further to get a potent anticancer molecules. Drugs targeting multiple kinases have proven to be effective against treatment of various diseases. The activities of serine/threonine protein phosphatases needs further study, but it is clear that these enzymes are potential targets for novel therapeutics with applications in many diseases, including cancer, inflammatory diseases and neuro degeneration. Computational techniques have provided starting points for designing multiple inhibitors against individual targets using crystal structural information of kinases and pharmacophore of kinase inhibitors. So these techniques can be explored further to design new drug candidates for various diseases.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Computational Design, Synthesis, Characterization, Pharmacological Evaluation, Piperidine Derivatives. |
| Subjects: | PHARMACY > Pharmacy Practice |
| Depositing User: | Devi S |
| Date Deposited: | 27 Jun 2017 10:21 |
| Last Modified: | 13 Sep 2022 15:38 |
| URI: | http://repository-tnmgrmu.ac.in/id/eprint/451 |
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