antifp2 1.1.0
AntiFP2: A tool for prediction of Antifungal Proteins
Requires Python: >=3.12

# AntiFP2

**AntiFP2** is a Python toolkit for predicting antifungal proteins using multiple approaches:

* **ESM2** (fine-tuned language model)
* **Machine Learning (PAAC features)**
* **BLAST** (sequence similarity adjustment)
* **MERCI** (motif adjustment)

It provides both one-by-one protein prediction and batch processing.

> ⚠️ Note: For genome or metagenome pipelines (requiring Prokka integration), please refer to the [GitHub repository](https://github.com/raghavagps/antifp2) or the [Docker version](https://hub.docker.com/repository/docker/pratik0297/antifp2/).

---

## 🚀 Features

* Fine-tuned **ESM2** model for protein sequence prediction
* Hybrid ML-based predictions using PAAC features
* Post-prediction adjustments:

  * **BLAST**: Sequence similarity to known antifungal/negative examples
  * **MERCI**: Motif enrichment detection
* One-by-one and batch prediction modes
* Logging of rejected or invalid sequences

---

## 📦 Installation

Install via PyPI:

```bash
pip install antifp2
```

> **Requires Python ≥ 3.12**.

Ensure BLAST+ and MERCI binaries are properly configured if using BLAST/MERCI adjustments.

---

## 📁 Project Structure

```
antifp2/
│
├── antifp2.py               # Master script
├── antifp2_esm2.py          # ESM2-only predictions
├── antifp2_esm2_hybrid.py   # ESM2 + BLAST + MERCI hybrid predictions
├── antifp2_ml_hybrid.py     # ML + BLAST + MERCI hybrid predictions
├── blast_db/                # Preformatted BLAST database
├── MERCI/                   # MERCI motif files
├── envfile                  # Config file for BLAST/MERCI paths
├── README.md
└── setup.py
```

---

## 🧭 Usage

All pipelines are launched using the **master script**:

```bash
python3 antifp2.py --method <method-name> [options]
```

### Available Methods

| Method Name   | Description                                  |
| ------------- | -------------------------------------------- |
| `esm2`        | ESM2-only predictions (protein sequences)    |
| `esm2-hybrid` | ESM2 + BLAST + MERCI hybrid predictions      |
| `ml-hybrid`   | ML (PAAC) + BLAST + MERCI hybrid predictions |

> For genome/metagenome pipelines using Prokka, see GitHub or Docker version.

---

### 1️⃣ ESM2 Only — `esm2`

Predict antifungal proteins using the fine-tuned **ESM2** model.

#### Arguments:

| Flag           | Description                                |
| -------------- | ------------------------------------------ |
| `--input`      | Input protein FASTA file                   |
| `--output`     | Path to output CSV file                    |
| `--threshold`  | Optional probability cutoff (default: 0.5) |
| `--no-cleanup` | Optional: keep intermediate files          |

#### Example:

```bash
python3 antifp2.py --method esm2 --input proteins.fasta --output esm2_predictions.csv
```

---

### 2️⃣ ESM2 + BLAST + MERCI — `esm2-hybrid`

Hybrid prediction combining **ESM2**, **BLAST**, and **MERCI** adjustments.

#### Arguments:

| Flag           | Description                                |
| -------------- | ------------------------------------------ |
| `--input`      | Input protein FASTA file                   |
| `--outdir`     | Output directory                           |
| `--threshold`  | Optional probability cutoff (default: 0.5) |
| `--envfile`    | Path to `envfile` with BLAST/MERCI paths   |
| `--no-cleanup` | Optional: keep intermediate files          |

#### Example:

```bash
python3 antifp2.py --method esm2-hybrid --input proteins.fasta --outdir esm2_hybrid_results
```

---

### 3️⃣ ML Hybrid — `ml-hybrid`

Predict antifungal proteins using **ML (PAAC features)** with BLAST and MERCI adjustments.

#### Arguments:

| Flag           | Description                                |
| -------------- | ------------------------------------------ |
| `--input`      | Input protein FASTA file                   |
| `--outdir`     | Output directory                           |
| `--threshold`  | Optional probability cutoff (default: 0.6) |
| `--envfile`    | Path to `envfile` with BLAST/MERCI paths   |
| `--no-cleanup` | Optional: keep intermediate files          |

#### Example:

```bash
python3 antifp2.py --method ml-hybrid --input proteins.fasta --outdir ml_hybrid_results
```

---

## 📂 Outputs

| File / Directory            | Description                              |
| --------------------------- | ---------------------------------------- |
| `*_predictions.csv`         | Main predictions (probabilities, labels) |
| `*_antifp2.fasta`           | Predicted antifungal protein sequences   |
| `blast_out.csv`, `*.locate` | Intermediate BLAST/MERCI results         |
| `rejected_log.txt`          | Invalid or rejected sequences log        |

---



## 💾 Model Files

ESM2 models are automatically loaded from the package or can be downloaded from Hugging Face.

---

## ✅ Citation

If you use **AntiFP2** in your research, please cite it appropriately.

---

## 👨‍💻 Support

* GitHub: [https://github.com/raghavagps/antifp2](https://github.com/raghavagps/antifp2)
* Email: [raghava@iiitd.ac.in](mailto:raghava@iiitd.ac.in)

---