Quickstart

0. Prequisites

To get started, you’ll need a FASTA file with one or more parent amino acid sequences. If desired, we can find additional parents with BLAST.

Optionally, you can provide a PDB structure file, but otherwise we’ll find one that matches the first parent sequence you provided. See schemarecomb.PDBStructure for more details.

Note

This guide assumes you’re using Python 3.9 on Linux. If you use MacOS, things will probably work the same, but no guarantees. If you have Windows, I recommend you use the Windows Subsystem for Linux, but again, no guarantees. Please raise an issue on the schemarecomb GitHub page if you have OS difficulty.

1. Install schemarecomb

schemarecomb is available on pip:

$ pip install schemarecomb

Or you can install schemarecomb from source.

In a Python script, import schemarecomb:

import schemarecomb

2. Make a ParentSequences

Load your parent FASTA file and find additional parents if needed. For this example, we’ll use beta-glucosidase (bgl3, PDB ID 1GNX):

parent_fn = 'bgl3.fasta'
p_aln = schemarecomb.ParentSequences.from_fasta(parent_fn)
p_aln.obtain_seqs(num_final_seqs=4, desired_identity=0.7)
p_aln.get_PDB()

After running, p_aln is a ParentSequences with four parents that have about 70% pairwise identity and the closest PDB structure.

See schemarecomb.ParentSequences for more options. Viewing schemarecomb.PDBStructure may also be helpful.

3. Run the SCHEMA-RASPP algorithm

SCHEMA-RASPP finds potential libraries and calculates the probability of Golden Gate assembly for each:

libraries = schemarecomb.generate_libraries(p_aln, 6)

This finds libraries with six blocks (five breakpoints).

See schemarecomb.generate_libraries() for more options.

4. Select and save a library

Select the library with highest mutation_rate - energy and save generated DNA blocks:

best_lib = max(libraries, key=lambda x: x.mutation_rate - x.energy)
SeqIO.write(best_lib.dna_blocks, 'bgl3_library_dna.fasta', 'fasta')

The DNA fragments in FASTA format in a file named “bgl3_library_dna.fasta”. These fragments are ready to order and assemble with NEB’s Golden Gate Assembly Kit. You can simulate the Golden Gate reaction using SnapGene.

See schemarecomb.Library for more options.