Using techniques from optimization theory, we have developed a computer program that approximates a desired probability distribution for amino acids by imposing a probability distribution on the four nucleotides in each of the three codon positions. These base probabilities allow for the generation of biased codons for use in mutational studies and in the design of biologically encoded libraries. The dependencies between codons in the genetic code often makes the exact generation of the desired probability distribution for amino acids impossible. Compromises are often necessary. The program, therefore, not only solves for the “optimal” approximation to the desired distribution (where the definition of “optimal” is influenced by several types of parameters entered by the user), but also solves for a number of “sub-optimal” solutions that are classified into families of similar solutions. A representative of each family is presented to the program user, who can then choose the type of approximation that is best for the intended application. The Combinatorial Codons program is available for use over the web from http://www.wi.mit.edu/kim/computing.html.
