Droxicam

A density functional theory study of eight oxicams was carried out in order to determine their global and local reactivities. These types of reactivities were measured by means of global and local reactivity descriptors coming from the conceptual density functional theory. Net electrophilicity as a global reactivity descriptor and local hypersoftness as a local reactivity descriptor were the used tools to distinguish reactivity and selectivity among these oxicams. Globally, isoxicam presents the highest electron donating capacity; meanwhile, the highest electron accepting capacity is exhibited by droxicam. Locally, two oxicams present neither nucleophilic nor electrophilic relevant reactivity in their peripheral pyridine ring, droxicam and tenoxicam, so that their more reactive zones are found on the respective fused rings. Oxicams have been divided into two subgroups in order to facilitate the local analysis of reactivity. One group is characterized because their most important condensed values for local hypersoftnes are well-separated: 4-meloxicam, lornoxicam, meloxicam, and normeloxicam. Meanwhile, the opposite situation is found in droxicam, isoxicam, piroxicam, and tenoxicam. As a whole, the nucleophilic characteristic noticeably predominates in these eight oxicams instead of an electrophilic behavior, thus meaning a greater tendency to donate electrons rather than withdrawing them; a consequence of this behavior implies a favorable interaction with a hypothetical receptor bearing one or more electron acceptor functional groups rather than electron donor functional groups; this would imply a maximization of this interaction from the covalent point of view.

Nonsteroidal anti-inflammatory drugs (NSAIDs) are a group of agents important for their analgesic, anti-inflammatory, and antipyretic properties. This study presents several approaches to predict and elucidate new molecular structures of NSAIDs based on 36 known and proven anti-inflammatory compounds. Based on 36 known NSAIDs the mean value of Log P is found to be 3.338 (standard deviation= 1.237), mean value of polar surface area is 63.176 Angstroms2 (standard deviation = 20.951 A2), and the mean value of molecular weight is 292.665 (standard deviation = 55.627). Nine molecular properties are determined for these 36 NSAID agents, including Log P, number of -OH and -NHn, violations of Rule of 5, number of rotatable bonds, and number of oxygens and nitrogens. Statistical analysis of these nine molecular properties provides numerical parameters to conform to in the design of novel NSAID drug candidates. Multiple regression analysis is accomplished using these properties of 36 agents followed with examples of predicted molecular weight based on minimum and maximum property values. Hierarchical cluster analysis indicated that licofelone, tolfenamic acid, meclofenamic acid, droxicam, and aspirin are substantially distinct from all remaining NSAIDs. Analysis of similarity (ANOSIM) produced R = 0.4947, which indicates low to moderate level of dissimilarity between these 36 NSAIDs. Non-hierarchical K-means cluster analysis separated the 36 NSAIDs into four groups having members of greatest similarity. Likewise, discriminant analysis divided the 36 agents into two groups indicating the greatest level of distinction (discrimination) based on nine properties. These two multivariate methods together provide investigators a means to compare and elucidate novel drug designs to 36 proven compounds and ascertain to which of those are most analogous in pharmacodynamics. In addition, artificial neural network modeling is demonstrated as an approach to predict numerous molecular properties of new drug designs that is based on neural training from 36 proven NSAIDs. Comprehensive and effective approaches are presented in this study for the design of new NSAID type agents which are so very important for inhibition of COX-2 and COX-1 isoenzymes.