RAMHA: a PC-based Monte-Carlo simulation of random saturation mutagenesis

Optimal codon randomization via mathematical programming

Codon randomization via degenerate oligonucleotides is a widely used approach for generating protein libraries. We use integer programming methodology to model and solve the problem of computing the minimal mixture of oligonucleotides required to induce an arbitrary target probability over the 20 standard amino acids. We consider both randomization via conventional degenerate oligonucleotides, which incorporate at each position of the randomized codon certain nucleotides in equal probabilities, and randomization via spiked oligonucleotides, which admit arbitrary nucleotide distribution at each of the codon's positions. Existing methods for computing such mixtures rely on various heuristics.

A computer program for the estimation of protein and nucleic acid sequence diversity in random point mutagenesis libraries

A computer program for the generation and analysis of in silico random point mutagenesis libraries is described. The program operates by mutagenizing an input nucleic acid sequence according to mutation parameters specified by the user for each sequence position and type of point mutation. The program can mimic almost any type of random mutagenesis library, including those produced via error-prone PCR (ep-PCR), mutator Escherichia coli strains, chemical mutagenesis, and doped or random oligonucleotide synthesis. The program analyzes the generated nucleic acid sequences and/or the associated protein library to produce several estimates of library diversity (number of unique sequences, point mutations, and single point mutants) and the rate of saturation of these diversities during experimental screening or selection of clones. This information allows one to select the optimal screen size for a given mutagenesis library, necessary to efficiently obtain a certain coverage of the sequence-space. The program also reports the abundance of each specific protein mutation at each sequence position, which is useful as a measure of the level and type of mutation bias in the library. Alternatively, one can use the program to evaluate the relative merits of preexisting libraries, or to examine various hypothetical mutation schemes to determine the optimal method for creating a library that serves the screen/selection of interest. Simulated libraries of at least 10⁹ sequences are accessible by the numerical algorithm with currently available personal computers; an analytical algorithm is also available which can rapidly calculate a subset of the numerical statistics in libraries of arbitrarily large size. A multi-type double-strand stochastic model of ep-PCR is developed in an appendix to demonstrate the applicability of the algorithm to amplifying mutagenesis procedures. Estimators of DNA polymerase mutation-type-specific error rates are derived using the model. Analyses of an alpha-synuclein ep-PCR library and NNS synthetic oligonucleotide libraries are given as examples.

Optimization of bacteriocin release protein (BRP)-mediated protein release by Escherichia coli: random mutagenesis of the pCloDF13-derived BRP gene to uncouple lethality and quasi-lysis from protein release

Bacteriocin release proteins (BRPs) can be used for the release of heterologous proteins from the Escherichia coli periplasm into the culture medium. However, high-level expression of BRP causes apparent lysis of the host cells in liquid cultures (quasi-lysis) and inhibition of growth on broth agar plates (lethality). To optimize BRP-mediated protein release, the pCloDF13 BRP gene was subjected to random mutagenesis by using PCR techniques. Mutated BRPs with a strongly reduced capacity to cause growth inhibition on broth agar plates were selected, analyzed by nucleotide sequencing, and further characterized by performing growth and release experiments in liquid cultures. A subset of these BRP derivatives did not cause quasi-lysis and had only a small effect on growth but still functioned in the release of the periplasmic protein beta-lactamase and the periplasmic K88 molecular chaperone FaeE and in the release of the bacteriocin cloacin DF13 into the culture medium. These BRP derivatives can be more efficiently used for extracellular production of proteins by E. coli than can the original BRP.

Scoring functions for computational algorithms applicable to the design of spiked oligonucleotides

Protein engineering by inserting stretches of random DNA sequences into target genes in combination with adequate screening or selection methods is a versatile technique to elucidate and improve protein functions. Established compounds for generating semi-random DNA sequences are spiked oligonucleotides which are synthesised by interspersing wild type (wt) nucleotides of the target sequence with certain amounts of other nucleotides. Directed spiking strategies reduce the complexity of a library to a manageable format compared with completely random libraries. Computational algorithms render feasible the calculation of appropriate nucleotide mixtures to encode specified amino acid subpopulations. The crucial element in the ranking of spiked codons generated during an iterative algorithm is the scoring function. In this report three scoring functions are analysed: the sum-of-square-differences function s, a modified cubic function c, and a scoring function m derived from maximum likelihood considerations. The impact of these scoring functions on calculated amino acid distributions is demonstrated by an example of mutagenising a domain surrounding the active site serine of subtilisin-like proteases. At default weight settings of one for each amino acid, the new scoring function m is superior to functions s and c in finding matches to a given amino acid population.

Optimizing doped libraries by using genetic algorithms

The insertion of random sequences into protein-encoding genes in combination with biological selection techniques has become a valuable tool in the design of molecules that have useful and possibly novel properties. By employing highly effective screening protocols, a functional and unique structure that had not been anticipated can be distinguished among a huge collection of inactive molecules that together represent all possible amino acid combinations. This technique is severely limited by its restriction to a library of manageable size. One approach for limiting the size of a mutant library relies on 'doping schemes', where subsets of amino acids are generated that reveal only certain combinations of amino acids in a protein sequence. Three mononucleotide mixtures for each codon concerned must be designed, such that the resulting codons that are assembled during chemical gene synthesis represent the desired amino acid mixture on the level of the translated protein. In this paper we present a doping algorithm that "reverse translates' a desired mixture of certain amino acids into three mixtures of mononucleotides. The algorithm is designed to optimally bias these mixtures towards the codons of choice. This approach combines a genetic algorithm with local optimization strategies based on the downhill simplex method. Disparate relative representations of all amino acids (and stop codons) within a target set can be generated. Optional weighing factors are employed to emphasize the frequencies of certain amino acids and their codon usage, and to compensate for reaction rates of different mononucleotide building blocks (synthons) during chemical DNA synthesis. The effect of statistical errors that accompany an experimental realization of calculated nucleotide mixtures on the generated mixtures of amino acids is simulated. These simulations show that the robustness of different optima with respect to small deviations from calculated values depends on their concomitant fitness. Furthermore, the calculations probe the fitness landscape locally and allow a preliminary assessment of its structure.