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Various molecular docking software packages are available for modeling interactions between small molecules and proteins.However,there have been few reports of modeling the interactions between metal ions and metalloproteins.In this study,the AutoDock package was employed to example docking into a di-iron binding protein,bacterioferritin.Each binding site of this protein was tested for docking with iron ions.Blind docking experiments showed that all docking conformations converged into two clusters,one for internal iron binding in sites within the metalloprotein and the other for external iron binding on the protein surface.Local docking experiments showed that there were significant differences between two internal iron binding sites.Docking at one site gave a reasonable root-mean-square deviation(RMSD) distribution with relatively low binding energy.Analysis of the binding mode quality for this site revealed that more than half of the docking conformations were categorized as having good binding geometry,while no good conformations were found for the other site.Further investigations indicated that coordinating water molecules contributed to the stability of binding geometries.This study provides an empirical approach towards the study of molecular docking in metalloproteins. 相似文献
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《微型电脑应用》2009,(6):I0001-I0003
Application of Improved BP Neural Network in Forecasting Grain Yield ( 1 ) WU Yan, DU Dong(Business School of Hohai University, Nanjing 210098, China) Abstract: Cause for slow convergence about the traditional BP neural network are analyzed, and an improved BP algorithm is proposed in this paper. Moreover, we develop a forecast model of time sequence object on this basis, and then this model is studied on the Grain Yield in Jiangsu Province with Matlab. The results from the simulation test proved that the algorithm is feasible and practicable. 相似文献
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