Polymerase chain reaction: a Markov process approach.

A probabilistic approach to the kinetics of the polymerase chain reaction (PCR) is developed. The approach treats the primer extension step of PCR as a microscopic Markov process in which the molecules of deoxy-nucleoside triphosphate (dNTP) are bound to the 3' end of the primer strand one at a time. The binding probability rates are prescribed by combinatorial rules in accord with the microscopic chemical kinetics. As an example, a simple model based on this approach is proposed and analysed, and an exact solution for the probability distribution of lengths of synthesized DNA strands is found by analytical means. Using this solution, it is demonstrated that the model is able to reproduce the main features of PCR, such as extreme sensitivity to the variation of control parameters and the existence of an amplification plateau. A multidimensional optimization technique is used to find numerically the optimum values of control parameters which maximize the yield of the target sequence for a given PCR run while minimizing the overall run time.