Protein-based therapeutics are playing an increasingly important role in the treatment of diseases, including diabetes and cancer. The viability of these treatments, however, are highly dependent on the stability of the therapeutic, since stability affects both the shelf life of the therapeutic as well as its active life in the body. Stability engineering can, therefore, be used to increase the effectiveness of protein-based therapeutics. Computational methods of protein stability prediction have been under development for about a decade, but complex molecular interactions make stability prediction difficult and computationally intensive. A rapid computational method of protein stability prediction is developed using feed-forward neural networks and used to predict mutation-induced stability changes in Staphylococcal nuclease. The input to the neural network consisted of sequences of evolutionarily based amino acid similarity scores that were obtained through the comparison of the amino acids in a mutation containing sequence to their positional counterparts in the baseline wild-type amino acid sequence. A training set was created which consisted of similarity score sequences, for which the stabilities of the corresponding amino acid sequences were known, paired with the relative stabilities of the sequences to that of the baseline. Back-propagation of error was used to train the network to output accurate relative stability scores for the sequences in the training set. Neural network-based relative stability predictions for 55 sequences containing mutation combinations not found in the training set had an accuracy of 92.8%.
Synthetic drugs such as allopurinol and benzbromarone are commonly used to treat the complex pathogenesis of gout, a metabolic disease that results from an inflammation of the joints caused by precipitation of uric acid. We seek to discover novel phytochemicals that could treat gout, by targeting the xanthine oxidase and cyclooxygenase-2 enzymes. In this study, we report the screening of nine compounds of flavonoids from the ZINC and PubChem databases (containing 2092 flavonoids) using the IGEMDOCK software tool against the xanthine oxidase and cyclooxygenase-2 3D protein structures. Each compound was also evaluated by an in vitro bioassay testing the inhibition of xanthine oxidase and cyclooxygenase-2. Myricetin and luteolin were found to be the potential dual inhibitors of xanthine oxidase and cyclooxygenase-2 as demonstrated by IC 50 : 62.7 and 3.29 lg/mL (xanthine oxidase)/70.8 and 16.38 lg/mL (cyclooxygenase-2), respectively. In addition, structure-activity relationships and other important factors of the flavonoids binding to the active site of xanthine oxidase and cyclooxygenase-2 were discussed, which is expected for further rational drug design.
Synthetic drugs such as allopurinol and benzbromarone are commonly used to treat the complex pathogenesis of gout, a metabolic disease that results from an inflammation of the joints caused by precipitation of uric acid. We seek to discover novel phytochemicals that could treat gout, by targeting the xanthine oxidase and cyclooxygenase-2 enzymes. In this study, we report the screening of nine compounds of flavonoids from the ZINC and PubChem databases (containing 2092 flavonoids) using the IGEMDOCK software tool against the xanthine oxidase and cyclooxygenase-2 3D protein structures. Each compound was also evaluated by an in vitro bioassay testing the inhibition of xanthine oxidase and cyclooxygenase-2. Myricetin and luteolin were found to be the potential dual inhibitors of xanthine oxidase and cyclooxygenase-2 as demonstrated by IC(50): 62.7 and 3.29 μg/mL (xanthine oxidase)/70.8 and 16.38 μg/mL (cyclooxygenase-2), respectively. In addition, structure-activity relationships and other important factors of the flavonoids binding to the active site of xanthine oxidase and cyclooxygenase-2 were discussed, which is expected for further rational drug design.
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