Molecular docking studies were performed on 18 17β-carboxamide steroids in order to select compounds with potential local anti-inflammatory activity. These derivatives are amides of cortienic acids (obtained from hydrocortisone, prednisolone, and methylprednisolone) with methyl or ethyl esters of six amino acids. Interactions with the glucocorticoid receptor (GR), binding energies and ligand efficiency values of these compounds were compared with dexamethasone and cortienic acid obtained from prednisolone (inactive metabolite). On the basis of molecular docking studies, seven compounds were selected and their binding affinities for the GR were predicted by use of the exponential model created in this study. Subsequently, selected compounds were synthesized in good yields by use of modified N,N'-dicyclohexylcarbodiimide (DCC)/1-hydroxybenzotriazole (HOBt) coupling procedure. Finally, the local anti-inflammatory activity of the synthesized compounds was examined by use of the croton oil-induced ear edema test. In vivo evaluation of systemic side effects as well as in silico prediction of metabolism were performed on the derivative with the best local anti-inflammatory activity. The combination of molecular docking studies and the exponential model for the GR binding affinity prediction could be used as an in silico tool for the rational design of novel 17β-carboxamide steroids with potentially better biological profile than dexamethasone.
Ontology construction of a certain domain is an important step in applying
the Semantic web. A number of software tools adapted for building domain
ontologies of most wide-spread natural languages are available, but
accomplishing that for any given natural language presents a challenge. Here
we propose a semi-automatic procedure to create ontologies for different
natural languages. Our approach utilizes various software tools available on
the Internet most notably DODDLE-OWL - a domain ontology development tool
implemented for English and Japanese languages. By using this tool, WordNet,
Prot?g? and XSLT transformations, we propose a general procedure to
construct domain ontology for any natural language.
This paper presents grey wolf optimization - GWO. After presenting the biological basis of GWO, it explains the method itself and then the main algorithms of the GWO method as well as their mathematical models. The Grey Wolf Algorithm (GWO) is presented in detail as well as the manner of its operation and it application to optimization examples of engineering problems, such as: optimization of speed reducer, pressure vessel, spring, car side impact, cone coupling and cantilever beam. At the end, the results obtained by the GWO method are compared to the results previously obtained by other methods.
In this paper we will demonstrate how Marine Predators Algorithm (MPA for short) can be used for solving certain optimization problems in applied mechanics. In the first part, biological fundamentals, as well as method explanation are given. Afterwards, MPA algorithm and its ' applicability is explained in detail. The pseudo code for this algorithm was written using Matlab R2019a software suite. This algorithm can be used for optimization o f engineering problems, such as: pressure vessel optimization, cantilever beam optimization, cone clutch optimization and speed reducer optimization. In the end, all the results for the fore mentioned problems, as well as a result comparison with other methods are shown.
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