Drug Metabolism as an Object of Computational Analysis by the Monte Carlo Method

Background: Metabolism of therapeutic agents in organism is extremely important from a point of view of drug discovery. Unfortunately, experimental estimation of phenomena related to metabolism is available for the limited number of substances. Under such circumstances, the development of computational method to predict endpoints related to metabolism of therapeutic agents becomes an attractive alternative for expensive and timeconsuming experiments. Method: A group of semi-empirical calculations are a convenient compromise between a necessity to carry out experiments and the desire to involve in the practical analysis of a bigger amount of molecular features related to the impact of different substances on metabolism. The practical organization of the investigational analysis may be based on the Monte Carlo technique. Results: The statistical quality of predictive models built up with the Monte Carlo method is usually quite satisfactory. Thus, the semi-empirical calculation using the Monte Carlo method may extend available database, which are related to metabolism of different therapeutic agents. It should be noted that the above approach involves minimal animal testing. The CORAL software has been used for the calculations. Conclusion: The described approach based on the Monte Carlo technique is a tool to predict behavior of therapeutic agents in organism. The approach is flexible: small and large molecules (peptides) can be studied by means of building up models of their endpoints which have impact upon metabolism phenomena.