We developed a molecular simulation method suitable for estimation of binding free energy, called the filling potential method, based on the concept of the Taboo search, which is a type of self-avoiding random walk consisting of a cycle of local-minimum searches and transition state searches. The filling potential method is an umbrella potential sampling method, and enables the ligand molecule to drift from its local minima automatically. In the case of the filling potential method, the umbrella potential is a combination of Gaussian-type repulsive potentials, which are located on the trajectory of the ligand. Without setting the reaction coordinates a priori, this method searches for and determines the suitable reaction coordinates by successive generation of umbrella potentials based on its trajectory analysis. The weighted histogram analysis for these trajectories gives the binding free energy of the ligand to the receptor protein. It was applied to the complex of thermolysin and its inhibitors in explicit water, and the free energy surfaces with the stable binding state and the energy barrier were examined. The calculated binding free energies agreed well with the experimental results.

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A compound's synthetic accessibility (SA) is an important aspect of drug design, since in some cases computer-designed compounds cannot be synthesized. There have been several reports on SA prediction, most of which have focused on the difficulties of synthetic reactions based on retro-synthesis analyses, reaction databases and the availability of starting materials. We developed a new method of predicting SA using commercially available compound databases and molecular descriptors. SA was estimated from the probability of existence of substructures consisting of the compound in question, the number of symmetry atoms, the graph complexity, and the number of chiral centers of the compound. The probabilities of the existence of given substructures were estimated based on a compound library. The predicted SA results reproduced the expert manual assessments with a Pearson correlation coefficient of 0.56. Since our method required a compound database and not a reaction database, it should be easy to customize the prediction for compound vendors. The correlation between the sales price of approved drugs and the SA values was also examined and found to be weak. The price most likely depends on the total cost of development and other factors.