Metadata-Version: 2.1
Name: mol-properties
Version: 1.0.2
Summary: CLI tool to calculate molecular properties and drug-likeness
Home-page: https://github.com/yourusername/mol-properties
Author: Your Name
Author-email: your.email@example.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: LICENSE.txt
Requires-Dist: pandas

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# mol-properties

**mol-properties** is a Python CLI tool to calculate molecular properties and evaluate drug-likeness rules (Lipinski & Veber). It also predicts approximate aqueous solubility (logS) using the ESOL model.

## Features

- Calculate key molecular descriptors:
  - Molecular Weight (MW)
  - LogP
  - H-bond donors (HBD)
  - H-bond acceptors (HBA)
  - Topological Polar Surface Area (TPSA)
  - Rotatable Bonds (RotB)
  - LogS (aqueous solubility)
- Check Lipinski and Veber rules for drug-likeness.
- Accepts **single SMILES** or **file containing multiple SMILES**.
- Optional strict Lipinski mode: any violation fails.



## Installation

This package requires [RDKit](https://www.rdkit.org/), which is not always available on PyPI.  
Please install RDKit first:

- Using conda (recommended):
  ```bash
  conda install -c conda-forge rdkit

``` 
or via pip (Linux / macOS only):
```bash
pip install rdkit
```

then install mol-properties
```bash
pip install mol-properties
