The advantage of being virtual-target-induced adaptation and selection in dynamic combinatorial libraries

Numerical simulations are presented that describe the adaptive behavior of simple dynamic combinatorial libraries (DCLs) upon addition of a target. By studying the effect of various parameters such as the network topology, the initial concentrations, the association constants, and the binding affinities, general characteristics of such systems were derived. It is shown that the adaptation may lead to the amplification of molecules with a high affinity to the target, but only for specific boundary conditions. Furthermore, it is demonstrated that the selection process can be refined by using an evolutionary approach. These results are of importance for the design of selection experiments with DCLs.