targetaa 1.0.0
Targeting amino acids for precise interaction detection in docking results with integrated PyMOL visualization
License: MIT
Requires Python: >=3.7

# TargetAA

```text
==================================================================
|     _____  _    ____   ____ _____ _____     _        _         |
|    |_   _|/ \  |  _ \ / ___| ____|_   _|   / \      / \        |
|      | | / _ \ | |_) | |  _|  _|   | |    / _ \    / _ \       |
|      | |/ ___ \|  _ <| |_| | |___  | |   / ___ \  / ___ \      |
|      |_/_/   \_\_| \_\\____|_____| |_|  /_/   \_\/_/   \_\     |
|                                                                |
|   [TARGET AMINO ACIDS]             VERSION - 1.0.0             |
|                                                                |
|   (Targeting amino acids for precise interaction detection.)   | 
|                                                                |
|   For more tools visit: https://github.com/alpha-horizon       |
|                                                                |
==================================================================  
```
<h1 style="font-weight:800; font-size:1.7em;">
    "A high-throughput tool that screens docking results to identify residue-specific interactions across multiple chains with automated PyMOL visualization."
</h1>

  For more tools visit: https://github.com/alpha-horizon

---
**TargetAA** (Target Amino Acids) is a high-throughput filtering tool for molecular docking workflows. It allows researchers to identify best ligand(s) that form direct contacts with specific residues of interest. This allows users to identify ligands that bind specifically within the receptor's pocket.

## Features

- Residue-Specific Filtering: Target specific chains and residue IDs (e.g., A:86,96).
- Processing: Automatically screens *_.pdbqt files (standard Vina/AutoDock output).
- PyMOL Integration: Generates a .pml file to instantly load all "hits" into PyMOL with optimized visualization settings (cartoon receptor, sticks for ligands, and pocket zoom).
- Data Export: Summarizes results in a clean docking_results.csv including Vina scores, contact counts, and specific residues involved.

## Input Requirements
1. Receptor File (.pdb)

    Format: Standard Protein Data Bank (.pdb) file.

    Requirement: Must contain valid Chain IDs (e.g., A, B) and Residue Numbers that match your search criteria.

2. Docking Results (.pdbqt)

    Format: AutoDock Vina-compatible _out.pdbqt files.

3. Residue Specifications

    Format: Chain:ResID (e.g., A:101 or A:101,102 B:55,56).

4. Distance Cutoff

    Default: 5.0 Å.

---
## pip Installation

To install targetaa, you can use the command mentioned below.

        pip install targetaa
---

## Command Line Usage

This tool supports full argument-based execution for automation and pipelines:

        targetaa --rec receptor.pdb --res A:86,96,102 --dir ./output_pdbqt --dist 5.0

Options:

        --rec: Path to your receptor file (PDB format).

        --res: Space-separated list of residues in Chain:ResID format (e.g., A:12,15 B:45).

        --dir: The folder containing your docking .pdbqt files (defaults to out_pdbqt).

        --dist: The distance cutoff in Ångströms for a "hit" (defaults to 5.0).
---  
## Output

- INFO: A real-time preview of ligands hitting your target site.

- docking_results.csv: A spreadsheet containing:

- Ligand ID

- Best Pose Model Number

- Vina Binding Affinity (Score)

- Number of contacts made

- Specific residues contacted

"view_hits.pml - A PyMOL file for visualization."
---
## Visualizing Results

To view all identified hits in 3D, simply run:
        
        pymol view_hits.pml

---
## Contribution

For more tools or to report issues, visit the official GitHub repository:

GitHub: https://github.com/alpha-horizon

---