Designing combinatorial library mixtures using a genetic algorithm

The design of combinatorial mixture libraries should take account of a number of factors. This paper describes the application of a genetic algorithm to optimizing the diversity of libraries while minimizing the effort that will be needed to deconvolute the biological hits by mass-spectroscopic techniques. It differs from previous applications of genetic algorithms to combinatorial library design in that each chromosome encodes an entire library with the result that properties of the library are optimized. Our method is such that it is easily extensible to optimizing the distributions of any number of physical or other properties of the library. The method allows for the combinatorial constraint inherent in mixtures that every substituent at each diversity site must occur in combination with every substituent at every other site. We present results showing that the genetic algorithm can produce good library designs in timely manner.