Computer simulations are extremely useful for evaluating the safety of chemicals and environmental pollutants. Since such simulations can require extensive knowledge of both mathematics and computer programming, however, they are not widely used. To make such computer simulations available to more researchers, the author has developed a Pharmacokinetics Predicting Program (PPP). This program runs under Microsoft Windows and makes it possible to easily determine the tissue distribution curve for chemical substances without requiring the user to deal with differential equations or computer programming. PPP requires only that the user enter the physiological data, the pharmacokinetic parameters, and the conditions under which the chemical substance was administered. The program then predicts in vivo tissue distribution and provides graphs of the predicted pharmacokinetic results. Some environmental pollutants and chemicals become more toxic or express activity following in vivo metabolism. Thus, the development of a computer simulation program was undertaken for predicting the tissue distribution of metabolites produced via complex metabolic pathways (A→B→C...), which would utilize a physiologically based pharmacokinetic (PBPK) model. Results indicate that the peak in tissue concentration is delayed for relatively late-forming metabolites such as metabolite C. This means that, when studying toxic metabolites, we need to consider time-lag in the expression of toxicity. PPP also has potential applications in numerous other areas, including the extrapolation of animal studies to humans, planning for animal testing, and planning for individualized drug treatment.

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20 models were constructed for the comparative modeling section of the Critical Assessment of Fully Automated Structure Prediction-2 (CAFASP2) [1] [2]. Sequence identity between each target and the best possible parent(s) ranged between 6% and 52%. Searching for the reference proteins and sequence alignments between the targets and reference proteins was provided by PSI-BLAST[3]. The modeling protocol was executed by the automated computer software FAMS[4], consisting of a database search and simulated annealing. There was no human intervention in checking the process of sequence alignments and building models. Both our team and another team, which used 3D-JIGSAW[5], succeeded in solving eight target models. The accuracies of the modeled backbone and side chains were estimated by using torsion angles. In particular, our modeled side chains were significantly more accurate than the ones modeled by the JIGSAW team. Moreover, our backbone models were also better than those of the JIGSAW team.

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