NTxPred2: A large language model for predicting neurotoxic peptides and neurotoxins
Creators: name: Rathore, Anand Singh
name: Jain, Saloni
name: Choudhury, Shubham
name: Raghava, Gajendra P. S.
Publisher: name: Zenodo
Year: 2025
Subjects: subject: Neurotoxins/classification
subject: Neurotoxic Peptides
subject: Protein Language Models
subject: Embeddings
subject: Machine Learning Techniques
subject: WHO Guidelines
subject: Toxicity

description: # NTxPred2


A method for predicting the neurotoxic activity of peptides and proteins.


---


## 📌 Introduction

**NTxPred2** is designed to assist researchers in therapeutic peptide and protein development by providing advanced methods for quantifying and classifying neurotoxic peptides and proteins that target the central nervous system.


It employs large language model word embeddings as features for predicting neurotoxic activity. The final model offers **Prediction, Protein-Scanning, and Design** modules, implemented using machine learning and protein language models.


🔗 Visit the web server for more information: [NTxPred2 Web Server](http://webs.iiitd.edu.in/raghava/ntxpred2)


📖 Please cite relevant content for complete details, including the algorithm behind the approach.


---


## 📚 Reference

**Rathore et al.** _A large language model for predicting neurotoxic peptides and neurotoxins._ **#Journal Name#**


---

### 🖼️ NTxPred2 Workflow Representation

![NTxPred2 Workflow](https://webs.iiitd.edu.in/raghava/ntxpred2/download/NTXPred_flowchart.png)


## 🛠️ Installation


### 🔹 PIP Installation

To install NTxPred2 via PIP, run:

```bash

pip install ntxpred2

```

To check available options, type:

```bash

ntxpred2 -h

```


### 🔹 Standalone Installation

NTxPred2 is written in **Python 3** and requires the following dependencies:


#### ✅ Required Libraries

```bash

python=3.10.7

pytorch

```

Additional required packages:

```bash

pip install scikit-learn==1.5.2

pip install pandas==1.5.3

pip install numpy==1.25.2

pip install torch==2.1.0

pip install transformers==4.34.0

pip install joblib==1.4.2

pip install onnxruntime==1.15.1

Bio (Biopython): 1.81

tqdm: 4.64.1

torch: 2.6.0

```


### 🔹 Installation using environment.yml

1. Create a new Conda environment:

```bash

conda env create -f environment.yml

```

2. Activate the environment:

```bash

conda activate NTxPred2

```


---


## ⚠️ Important Note

- Due to the large size of the model file, the model directory has been compressed and uploaded.

- Download the **zip file** from [Download Page](https://webs.iiitd.edu.in/raghava/ntxpred2/download.html).

- **Extract the file** before using the code or model.


---


## 🔬 Classification

**NTxPred2** classifies peptides and proteins as **neurotoxic or non-neurotoxic** based on their primary sequence.


🔹 **Model Options**

- **ESM2-t30 (Peptide Model):** For sequences **7-50 amino acids** long.

- **ET (Protein Model):** For sequences **≥ 51 amino acids**.

- **ET (Combined Model):** For sequences of **mixed length**.

- **Default Model:** ESM2-t30 (Peptide Model), selected for best performance and efficiency.


---


## 🚀 Usage


### 🔹 Minimum Usage

```bash

ntxpred2.py -h

```

To run an example:

```bash

ntxpred2.py -i example.fasta

```


### 🔹 Full Usage

```bash

usage: ntxpred2.py [-h]

[-i INPUT]

[-o OUTPUT]

[-t THRESHOLD]

[-j {1,2,3,4}]

[-m {1,2,3}]

[-d {1,2}]

[-wd WORKING DIRECTORY]

```

#### Required Arguments

| Argument | Description |

|----------|-------------|

| `-i INPUT` | Input: Peptide or protein sequence (FASTA format or simple format) |

| `-o OUTPUT` | Output file (default: `outfile.csv`) |

| `-t THRESHOLD` | Threshold (0-1, default: `0.5`) |

| `-j {1,2,3,4}` | Job type: 1-Prediction, 2-Protein Scanning, 3-Design, 4-Design all possible mutants |

| `-m {1,2,3}` | Model selection: 1-ESM2-t30 (Peptides), 2-ET (Proteins), 3-ET (Combined) |

| `-wd WORKING` | Working directory for saving results |


---


## 📂 Input & Output Files


### ✅ **Input File Format**

NTxPred2 supports two formats:

1. **FASTA Format:** (Example: `example.fasta`)

2. **Simple Format:** (Example: `example.seq`, each sequence on a new line)


### ✅ **Output File**

- Results are saved in **CSV format**.

- If no output file is specified, results are stored in `outfile.csv`.


---


## 🔍 Jobs & Features


### 🔹 **Job Types**

| Job | Description |

|-----|-------------|

| 1️⃣ **Prediction** | Predicts whether input peptide/protein is neurotoxic or not. |

| 2️⃣ **Protein Scanning** | Identifies neurotoxic regions in a protein sequence. |

| 3️⃣ **Design** | Generates mutant peptides/proteins with a **single amino acid/dipeptide** at a specified position. |

| 4️⃣ **Design All Possible Mutants** | Generates and predicts **all possible mutants**. |


### 🔹 **Additional Options**

| Option | Description |

|--------|-------------|

| `-p POSITION` | Position to insert mutation (1-indexed) |

| `-r RESIDUES` | Mutated residues (single/double letter amino acid codes) |

| `-w {8-20}` | Window length (Protein Scan mode only, default: 12) |

| `-d {1,2}` | Display: 1-Neurotoxic only, 2-All peptides (default) |


---


## 📑 Package Contents


| File | Description |

|------|-------------|

| **INSTALLATION** | Installation instructions |

| **LICENSE** | License information |

| **README.md** | This file |

| **ntxpred2.py** | Python program for classification |

| **example.fasta** | Example file (FASTA format) |


---


## 📦 PIP Installation (Again for Reference)

```bash

pip install ntxpred2

```

Check options:

```bash

ntxpred2 -h

```


---


🚀 **Start predicting neurotoxicity with NTxPred2 today!**


🔗 Visit: [NTxPred2 Web Server](http://webs.iiitd.edu.in/raghava/ntxpred2)