Cyclo-oxygenase-2 (COX-2), a rate-limiting enzyme for prostanoid synthesis, is induced during inflammation and participates in inflammation-mediated cytotoxicity. The discovery of two cyclo-oxygenase (COX) isoenzymes, viz. COX-1 and COX-2, has updated the knowledge of non steroidal anti-inflammatory drugs (NSAIDs). The two COX isoenzymes share structural and enzymatic similarities, but are specifically regulated at the molecular level and may be distinguished apart in their functions, although some physiological overlap between them does occur. The major goal in developing selective COX inhibitors is to improve NSAID tolerability. Conventional non steroidal antiinflammatory drugs (NSAIDs) nonspecifically inhibit cyclooxygenase-1 (COX-1), an enzyme critical to normal platelet function, and COX-2 which mediates inflammatory response mechanisms. Celecoxib, the 1, 5-diarylpyrazole compounds was the first launched selective COX-2 inhibitor, and has excellent selectivity and potent anti-inflammatory activity. COX-2 is required for both the constitutive and mitogen-induced PGE 2 synthesis. Moreover, over-expression and persistent expression of COX-2 may be influenced by breast tumor hormone status and seem to be a feature of the aggressive, metastaticpheno type. Recent studies have indicated that the relationships between polyunsaturated fatty acid metabolism and carcinogenesis have led to new targets for the design of mechanism based drugs in cancer chemoprevention research. Selective inhibition of COX-2 provided a new class of anti inflammatory, analgesic, and antipyretic drugs with significantly reduced side effects. It has been reported that inhibiting COX-2 could also be an important strategy for preventing or treating a number of cancers. COX-2 selective inhibitors such as celecoxib, rofecoxib and valdecoxib are currently being used to reduce inflammatory response. However, they lack anti-thrombotic activity and hence lead to cardiovascular and renal liabilities apart from gastrointestinal irritation. Therefore, there is still a need to develop more potent COX-2 inhibitors. One of the keys to developing COX-2 selective drugs is the larger active site of COX-2, which makes it possible to make molecules too large to fit into the COX-1 active site but still able to fit the COX-2.
Selective inhibition of COX-2 provided a new class of anti inflammatory, analgesic, and antipyretic drugs with significantly reduced side effects. It has been reported that inhibiting COX-2 could also be an important strategy for preventing or treating a number of cancers. We report a modified k-means clustering algorithm to cluster groups of compounds obtained from regression analysis along with few compounds which were non-tested against COX-2 and screened them using regression model. The regression model due to its high predictive ability can be utilized as an alternative aid to the costly and time consuming experiments for recognizing and determining compounds with high COX-2 binding affinity. Hence, a group of new derivatives from literature are subjected to screening utilizing the produced model. A set of 32 compounds with pyrazole ring as main nucleus was selected from a published review paper. We present a modification of k-means algorithm that efficiently searches data to cluster points by computing sum of squares within each cluster which makes the program to select the most promising subset of classes for clustering. From a set of 32 compounds, only the top 5 compounds are combined with 58 molecule data set to perform cluster analysis. From the analysis it is evidenced that k-means clustering algorithm is able to group data objects of all molecules based on the 3 centroids provided and all top 5 compounds appear to be centred on one spade whereas Celecoxib appeared in another cluster.
COX-2 provided a new class of anti inflammatory, analgesic and antipyretic drugs with significantly reduced side effects. It has been reported that inhibiting COX-2 could also be an important strategy for preventing or treating a number of cancers. A report with modified k-means clustering algorithm to cluster groups of compounds obtained from regression analysis along with few compounds which were non-tested against COX-2 and screened them using regression model. The regression model due to its high predictive ability can be utilized as an alternative aid to the costly and time consuming experiments for recognizing and determining compounds with high COX-2 binding affinity. Hence, a group of new derivatives from literature are subjected to screening utilizing the produced model. A set of 32 compounds with pyrazole ring as main nucleus was selected from a published review paper. In this work, a modification of k-means algorithm that efficiently searches data to cluster points by computing sum of squares within each cluster which makes the program to select the most promising subset of classes for clustering. From a set of 32 compounds, only the top 5 compounds are combined with 58 molecule data set to perform cluster analysis. From the analysis it is evidenced that k-means clustering algorithm is able to group data objects of all molecules based on the 3 centroids provided and all top 5 compounds appear to be centred on one spade whereas Celecoxib appeared in another cluster.
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