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"# Getting Started\n",
"\n",
"Welcome to the first `biobuild` tutorial, where we shall learn the basics of operating with `biobuild`!\n",
"\n",
"> ### In this tutorial we will cover:\n",
"> - which (main) classes and modules exist and when to use them\n",
"> - how to read input to make `Molecule`s\n",
"> - how to connect two molecules together"
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"## Main Classes in `biobuild`\n",
"\n",
"The most important class is the `Molecule` class which houses ~90% of all functionality that the average user is likely to use. \n",
"Next, comes the `Linkage` class that defines how multiple molecules can be connected, so the user can build larger structures. Third,\n",
"are the `ResidueGraph` and `Rotatron` environments of the `optimizers` module - to optimize conformations. Finally, the `MoleculeViewer3D` may come in quite handy. It is essentially just a plotly 3D-plot but it can be selectively colored easily so as to highlight specific parts of your molecule - it is a great tool to check if your building process is working (or to debug why it may not be). Finally, the `resources` module houses a wealth of reference structures for users to use when building their favourite structures.\n",
"\n",
"That's already about it! Of course, there is a lot more - but everything else is mostly underneath the surface and will most likely not bother the average user directly. "
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"```mermaid\n",
"\n",
"flowchart TB\n",
" node_0[\"core\"]\n",
" node_1(\"Molecule\")\n",
" node_2(\"ResidueGraph\")\n",
" node_3(\"MoleculeViewer3D\")\n",
" node_4[\"Optimizers\"]\n",
" node_6(\"Rotatron\")\n",
" node_7{\"{}_optimize\"}\n",
" node_5[\"Linkage\"]\n",
" node_8[\"resources\"]\n",
" node_1 -.-> node_2\n",
" node_1 -.-> node_3\n",
" node_0 --- node_1\n",
" node_4 --- node_6\n",
" node_4 --- node_7\n",
" node_6 -.-> node_7\n",
" node_2 -.-> node_7\n",
" node_0 --- node_5\n",
"\n",
"```"
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"import plotly\n",
"plotly.offline.init_notebook_mode()\n",
"\n",
"import biobuild as bb"
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"### Resources\n",
"\n",
"biobuild includes the _PDBE_ component library for small molecules (or at least a pretty large part of it). Since this is quite large, biobuild will not by default load any data, but offers a buch of functions for the user to load what they are interested in using selectively. We can also set defaults that are always loaded if we want to re-use our own custom builds in different sessions. \n",
"\n",
"Available pre-loadable sets are:\n",
"\n",
"```python\n",
"# to load the amino acid and derivative compounds\n",
"bb.load_amino_acids()\n",
"\n",
"# to load nucleotide and derivative compounds\n",
"bb.load_nucleic_acids()\n",
"\n",
"# to load sugar and derivative compounds\n",
"bb.load_sugars()\n",
"\n",
"# to load miscallaneous small molecules of less than 40 atoms\n",
"bb.load_small_molecules()\n",
"```"
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"### Molecules\n",
"\n",
"Molecules are the essential data unit in `biobuild`. Each Molecule houses atoms that form a molecular structure. We can generate Molecules from:\n",
"- a PDB or CIF file (e.g. \"my_structure.pdb\")\n",
"- a PDB ID (e.g. \"GLC\" - the PDB id for alpha-D-glucose)\n",
"- a trivial name (e.g. \"triacetamide\")\n",
"- a chemical formula (e.g. \"C2H6O\" - caution, may produce ambiguities!)\n",
"- SMILES and InChI/InChIKey\n",
"\n",
"The `Molecule` class has classmethods for all of these named `from_pdb`, `from_compound` (for PDB ID, name etc.), `from_pubchem` and so forth. But there also exists the toplevel `molecule` function that will try to automatically figure out the user input and generate a molecule for you."
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"### Linkage \n",
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"> #### Note\n",
"> The linkages do *not* need to follow chemical reasoning - they only connect structures by adding and removing connections. Hence, we could connect the molecules by one of the methyl-groups making one of the hydrogens the leaving group (even though chemically such a reaction would probably never occur) - biobuild builds structures, but it does not imitate chemical reactions! "
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"link = bb.linkage(atom1=\"N1\", atom2=\"C\", delete_in_target=[\"H1\"], delete_in_source=[\"OXT\", \"HXT\"])"
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""
]
},
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],
"source": [
"from biobuild import optimizers\n",
"\n",
"# step (1)\n",
"# make a graph representation of the molecule\n",
"graph = new.get_atom_graph() \n",
"\n",
"# step (2)\n",
"# get edges/bonds to rotate around\n",
"# we choose only edges/bonds that have at least 10 atoms before and after them\n",
"rotatable_edges = graph.find_rotatable_edges(min_descendants=10, min_ancestors=10)\n",
"\n",
"# step (3)\n",
"# make an environment\n",
"# we use the DistanceRotatron environment\n",
"env = optimizers.DistanceRotatron(graph, rotatable_edges)\n",
"\n",
"# step (4) and (5)\n",
"# run the optimization algorithm\n",
"new_optimized = optimizers.optimize(new, env, algorithm=\"genetic\")\n",
"\n",
"# and check what it looks like\n",
"new.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Formats and Integrations\n",
"\n",
"Now that we have a structure we like we can for instance save it as a _PDB_ or _mmCIF_ file. If we have more intricate interests in the molecules we have built we can export them directly to `rdkit` or `openbabel` objects for further analysis. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To make working with different data formats as easy as possible, each biobuild Molecule can be created and saved to the following formats:\n",
"\n",
"```mermaid\n",
"flowchart TB\n",
"\n",
" node_1(\"Molecule\")\n",
" node_2([\"PDB\"])\n",
" node_3([\"mmCIF\"])\n",
" node_9([\"Molfile\"])\n",
" node_11((\"SMILES\"))\n",
" node_4([\"JSON\\n(biobuild)\"])\n",
" node_5([\"pickle\\n(biobuild)\"])\n",
" node_6{{\"rdkit\\n(Chem.rdchem.Mol)\"}}\n",
" node_7{{\"openbabel\\n(pybel.Molecule)\"}}\n",
" node_8{{\"biopython\\n(PDB.Structure)\"}}\n",
" node_10{{\"openmm\\n(openmm.PDBFile)\"}}\n",
" node_2 <--> node_1\n",
" node_3 <--> node_1\n",
" node_9 <-.-> node_1\n",
" node_11 <-.-> node_1\n",
" node_4 <--> node_1\n",
" node_5 <--> node_1\n",
" node_6 <--> node_1\n",
" node_7 <--> node_1\n",
" node_8 <--> node_1\n",
" node_10 <--> node_1\n",
" \n",
"```\n",
"\n",
"Here are is a table with the corresponding methods available in the `Molecule` class:\n",
"\n",
"| Format | As input | As output |\n",
"| --------- | ------------- | -------------- |\n",
"| PDB | `from_pdb` | `to_pdb` |\n",
"| mmCIF | `from_cif` | `to_cif` |\n",
"| Molfile | `from_molfile` | `to_molfile` |\n",
"| SMILES | `from_smiles` | `to_smiles` |\n",
"| JSON | `from_json` | `to_json` |\n",
"| pickle | `load` | `save` |\n",
"| rdkit | `from_rdkit` | `to_rdkit` |\n",
"| openbabel | `from_pybel` | `to_pybel` |\n",
"| openmm | `from_openmm` | `to_openmm` | \n",
"| biopython | `` | `to_biopython` |"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# so let's save our small molecule to a PDB file\n",
"new.to_pdb(\"our_first_molecule.pdb\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With that we have reached already the end of this first little introduction into what biobuild can do, and how it feels to work with biobuild. Thanks a lot for reading this far! And good luck with whatever you may do with biobuild in your projects!"
]
}
],
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