Normal mode analysis based on an elastic network model for biomolecules in the Protein Data Bank,which uses dihedral angles as independent variables

We have developed a computer program, named PDBETA, that performs normal mode analysis (NMA) based on an elastic network model that uses dihedral angles as independent variables. Taking advantage of the relatively small number of degrees of freedom required to describe a molecular structure in dihedral angle space and a simple potential-energy function independent of atom types, we aimed to develop a program applicable to a full-atom system of any molecule in the Protein Data Bank (PDB). The algorithm for NMA used in PDBETA is the same as the computer program FEDER/2, developed previously. Therefore, the main challenge in developing PDBETA was to find a method that can automatically convert PDB data into molecular structure information in dihedral angle space. Here, we illustrate the performance of PDBETA with a protein–DNA complex, a protein–tRNA complex, and some non-protein small molecules, and show that the atomic fluctuations calculated by PDBETA reproduce the temperature factor data of these molecules in the PDB. A comparison was also made with elastic-network-model based NMA in a Cartesian-coordinate system.     

Highly sensitive and quantitative analysis of polyeptides using a new gradient system based on an abrupt change in adsorption of polypeptide to the reversed-phase column packing

During a study of 100 microL aliquots of urocortin containing various acetonitrile contents, we hypothesized that a change in the acetonitrile content in the solution across a specific content of acetonitrile (critical threshold) causes an abrupt change in adsorption capacity to the column packing. Circular dichroism measurements suggest that the conformational change induced by acetonitrile in the solution causes the abrupt change in adsorption capacity, and this solvent-induced conformational change is reversible across the critical threshold. This hypothesis can apply to various polypeptides with molecular weights range from 1007 to 6789 and to other organic solvents. A new gradient system utilizing the instant recovery of the adsorption capacity across the critical threshold was designed, and applied to the analysis of a 100 microL aliquot of various polypeptide solutions. The results suggest that use of a solution containing organic solvents more than the critical threshold allows successful dilution of polypeptides up to picomolar concentration range without any loss due to its adsorption during handling procedures and loading onto the LC system, and that a new gradient system enables quantitative analysis of polypeptides at picomolar concentrations in such solutions.     

Application of artificial neural network to simultaneous potentiometric determination of silver(I), mercury(II) and copper(II) ions by an unmodified carbon paste electrode

The response characteristics and selectivity coefficients of an unmodified carbon paste electrode (CPEs) towards Ag⁺, Cu²⁺ and Hg²⁺ were evaluated. The electrode was used as an indicator electrode for the simultaneous determination of the three metal ions in their mixtures via potentiometric titration with a standard thiocyanate solution. A three-layered feed-forward artificial neural network (ANN) trained by back-propagation learning algorithm was used to model the complex non-linear relationship between the concentration of silver, copper and mercury in their different mixtures and the potential of solution at different volumes of the added titrant. The network architecture and parameters were optimized to give low prediction errors. The optimized networks were able to precisely predict the concentrations of the three cations in synthetic mixtures.