Merge commit 'aa4f7334ea2380489dd1dae40b3866ed36531a5c' into development

CITATION.cff

@@ -11,7 +11,7 @@ authors:
   given-names: "Kohulan"
   orcid: "https://orcid.org/0000-0003-1066-7792"
 title: "cheminformatics-python-microservice"
-version: v0.1.0 - prerelease
-doi: 10.5281/zenodo.7745988
+version: v0.3.0 - prerelease
+doi: 10.5281/zenodo.7747862
 date-released: 2023-03-16
 url: "https://github.com/Steinbeck-Lab/cheminformatics-python-microservice"

README.md

@@ -9,6 +9,7 @@
 ![Workflow](https://github.com/Steinbeck-Lab/cheminformatics-python-microservice/actions/workflows/dev-build.yml/badge.svg)
 [![framework](https://img.shields.io/badge/Framework-FastAPI-blue?style)](https://fastapi.tiangolo.com/)
 [![FastAPI Documentation](https://img.shields.io/badge/docs-fastapi-blue)](https://api.naturalproducts.net/docs#/)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7747862.svg)](https://doi.org/10.5281/zenodo.7747862)
 ## Overview of Cheminformatics Micro Services
 
 This set of essential and valuable microservices is designed to be accessed via API calls to support cheminformatics. Generally, it is designed to work with SMILES-based inputs and could be used to translate between different machine-readable representations, get Natural Product (NP) likeliness scores, visualize chemical structures, and generate descriptors. In addition, the microservices also host an instance of [STOUT](https://github.com/Kohulan/Smiles-TO-iUpac-Translator) and another instance of [DECIMER](https://github.com/Kohulan/DECIMER-Image_Transformer) (two deep learning models for IUPAC name generation and optical chemical structure recognition, respectively).
@@ -47,6 +48,10 @@ This set of essential and valuable microservices is designed to be accessed via
   ```fastapi
   https://api.naturalproducts.net/chem/depict?smiles=CN1C=NC2=C1C(=O)N(C(=O)N2C)C&generator=rdkit&width=256&height=256&rotate=75
   ```
+  - Visualize molecule in 3D
+  ```fastapi
+  https://api.naturalproducts.net/chem/depict3D?smiles=CN1C=NC2=C1C(=O)N(C(=O)N2C)C
+  ```
 
 > **Note**
 > For detailed documentation on how to use the API check [here](https://api.naturalproducts.net/docs#/)
@@ -57,7 +62,7 @@ This project is licensed under the MIT License - see the [LICENSE](https://githu
 
 ## Citation
 
-Venkata, C., Sharma, N., & Rajan, K. (2023). cheminformatics-python-microservice (Version v0.1.0 - prerelease) [Computer software]. https://doi.org/10.5281/zenodo.7745988
+Venkata, C., Sharma, N., & Rajan, K. (2023). cheminformatics-python-microservice (Version v0.3.0 - prerelease) [Computer software]. https://doi.org/10.5281/zenodo.7747862
 
 ## Maintained by
 

app/main.py

@@ -27,7 +27,7 @@
 
 @app.get("/", include_in_schema=False)
 async def docs_redirect():
-    return RedirectResponse(url='/docs')
+    return RedirectResponse(url="/docs")
 
 
 def custom_openapi():

app/modules/descriptor_calculator.py → app/modules/rdkitmodules.py

@@ -1,5 +1,5 @@
 from rdkit import Chem
-from rdkit.Chem import Descriptors, QED, Lipinski, rdMolDescriptors, rdmolops
+from rdkit.Chem import AllChem, Descriptors, QED, Lipinski, rdMolDescriptors, rdmolops
 
 
 def checkRo5Violations(mol):
@@ -20,7 +20,7 @@ def checkRo5Violations(mol):
     return num_of_violations
 
 
-def GetBasicDescriptors(smiles):
+def getBasicDescriptors(smiles):
     """Take an input SMILES and generates a selected set of molecular
     descriptors as a dictionary
     Args (str): SMILES string
@@ -62,3 +62,21 @@ def GetBasicDescriptors(smiles):
     }
 
     return AllDescriptors
+
+
+def get3Dconformers(smiles):
+    """Convert SMILES to Mol with 3D coordinates
+    Args (str): SMILES string.
+    Returns (rdkil.mol): A mol object with 3D coodinates
+    optimized with MMFF94 forcefield.
+
+    """
+    mol = Chem.MolFromSmiles(smiles)
+    if mol:
+        AllChem.Compute2DCoords(mol)
+        mol = Chem.AddHs(mol)
+        AllChem.EmbedMolecule(mol, randomSeed=0xF00D)
+        AllChem.MMFFOptimizeMolecule(mol, maxIters=200)
+        return Chem.MolToMolBlock(mol)
+    else:
+        return None

app/routers/chem.py

@@ -8,11 +8,10 @@
 from fastapi.responses import Response, HTMLResponse
 from rdkit.Chem.Scaffolds import MurckoScaffold
 from app.modules.npscorer import getnp_score
-from app.modules.descriptor_calculator import GetBasicDescriptors
 from app.modules.classyfire import classify, result
 from app.modules.cdkmodules import getCDKSDGMol
 from app.modules.depict import getRDKitDepiction, getCDKDepiction
-from app.modules.depict3D import get3Dconformers
+from app.modules.rdkitmodules import getBasicDescriptors, get3Dconformers
 
 from fastapi.templating import Jinja2Templates
 
@@ -77,7 +76,7 @@ async def smiles_descriptors(smiles: str):
     - **smiles**: required (query)
     """
     if smiles:
-        return GetBasicDescriptors(smiles)
+        return getBasicDescriptors(smiles)
 
 
 @router.get("/npscore")
@@ -137,12 +136,10 @@ async def depict_molecule(
 async def depict3D_molecule(
     request: Request,
     smiles: str,
-    width: Optional[int] = 512,
-    height: Optional[int] = 512,
-    style: Optional[str] = "stick",
 ):
     if smiles:
-        return templates.TemplateResponse("mol.html", {"request": request, "molecule": Chem.MolToMolBlock(get3Dconformers(smiles))})
+        content = {"request": request, "molecule": get3Dconformers(smiles)}
+        return templates.TemplateResponse("mol.html", content)
 
 
 # @app.get("/molecules/", response_model=List[schemas.Molecule])

app/templates/mol.html

@@ -15,7 +15,7 @@
 $(document).ready(function() {
     var viewer = $3Dmol.createViewer("viewer");
     viewer.setBackgroundColor(0xffffff);
-    viewer.addModel(`{{ molecule }}`, "sdf");
+    viewer.addModel(`{{ molecule }}`, "mol");
     viewer.setStyle({stick:{}});
     viewer.zoomTo();
     viewer.render();

requirements.txt

@@ -16,5 +16,4 @@ efficientnet
 tensorflow==2.10.0
 pyheif==0.7.1
 selfies>=2.1.1
-py3Dmol
 jinja2