============================================================================== eCodonOpt, v1.0 Last Updated 04/23/02 ReadMe.txt ============================================================================== Contents of eCodonOpt 1.0 distribution: eCodonOpt is a two-phase computational framework. First, sequences (both nucleotide and residue) must be transferred to GAMS input by preprocessing them with 2 FORTRAN 90 codes. Then, with the new include files for GAMS, the codon optimization is performed and new nucleotide sequences are designed and output. Below are some notes on the two phases. Phase 1 - FORTRAN 90 preprocessing: Two pieces of information are needed by GAMS: (1) the residue sequences, so it knows the set of nucleotide allowed at each position, and (2) the wild-type nucleotide sequences, so the number of mutations away from wild-type can be limited. The preprocessing/ directory contains two FORTRAN 90 programs for doing this. Two files are generated for GAMS: (1) allowed.inc and (2) originals.inc. Some samples of these include files can be found in the root directory. In addition, another include file containing information on the nearest-neighbor enthalpy and entropy parameters is found in the core_includes/ directory. Phase 2 - GAMS codon optimization: Three GAMS codes are included (all in the root directory): 1) eCodonOpt.gms - utilized for free energy minimization of any number of parental sequences. Also can be used for minimizing bias in family DNA shuffling by including upper and lower bounds on free energies of parental pairs. 2) positions.gms - utilized to position crossovers in specific regions (e.g., loop, scaffold). 3) metrics.gms - utilized for free energy minimization with constraints on metrics (CAI, MCU) that account for host-specific codon preferences. ============================================================================== Contact Costas Maranas (costas@psu.edu) or Greg Moore (greg@cyprus.che.psu.edu) with questions and comments. Also see: Moore, G.L. & C.D. Maranas (2002), "eCodonOpt: A Systematic Computational Framework for Optimizing Codon Usage in Directed Evolution Experiments," Nucleic Acids Research, in press. http://fenske.che.psu.edu/CMaranas/ ==============================================================================