afpropred 0.4

A tool to predict anti-freezing proteins

AfProPred

A computational method to predict the Anti-Freezing proteins based on evolutionary profiles

Introduction

AfProPred is a tool developed by Raghva-Lab in 2024. It is designed to predict whether a protein is Anti-Freezing or not. It utilizes both amino-acid compositions and PSSM as features to make predictions using an ExtraTrees Classifier. AfProPred is also available as web-server at https://webs.iiitd.edu.in/raghava/afpropred. Please read/cite the content about the AfProPred for complete information including algorithm behind the approach.

PIP Installation

PIP version is also available for easy installation and usage of this tool. The following command is required to install the package

pip install afpropred

To know about the available option for the pip package, type the following command:

afpropred -h

Standalone

The Standalone version of AfProPred is written in python3 and following libraries are necessary for the successful run:

• scikit-learn==1.3.0
• argparse
• biopython
• numpy
• pandas

Minimum USAGE

To know about the available option for the standalone, type the following command:

python afpropred.py -h

To run the example, type the following command:

python afpropred.py -i example_input.fa

This will predict the probability whether a submitted sequence will localize to the cytoplasm or nucleus. It will use other parameters by default. It will save the output in "outfile.csv" in CSV (comma separated variables).

Full Usage

usage: afpropred.py [-h] -i INPUT [-o OUTPUT] [-t THRESHOLD] [-m {1,2}] [-d {1,2}]
                    [-wd WORKING]

Please provide following arguments.

options:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Input: protein or peptide sequence in FASTA format
  -o OUTPUT, --output OUTPUT
                        Output: File for saving results by default outfile.csv
  -t THRESHOLD, --threshold THRESHOLD
                        Threshold: Value between 0 to 1 by default 0.48
  -m {1,2}, --model {1,2}
                        Model: 1: AAC feature based ExtraTrees Classifier , 2: AAC + PSSM
                        feature based ExtraTrees Classifier, by default 1
  -d {1,2}, --display {1,2}
                        Display: 1:AFP, 2: All peptides, by default 2
  -wd WORKING, --working WORKING
                        Working Directory: Temporary directory to write files

Input File: It allow users to provide input in the FASTA format.

Output File: Program will save the results in the CSV format, in case user does not provide output file name, it will be stored in "outfile.csv".

Threshold: User should provide threshold between 0 and 1, by default its 0.5.

Display type: This option allow users to display only Anti-Freezing proteins or all the input proteins.

Working Directory: Directory where intermediate files as well as final results will be saved

AfProPred Package Files

It contains the following files, brief description of these files given below

INSTALLATION : Installations instructions

LICENSE : License information

README.md : This file provide information about this package

model : This folder contains two pickled models

afpropred.py : Main python program

possum : This folder contains the program POSSUM, that is used to calculate PSSM features

ncbi-blast-2.15.0+ : This folder contains the BLAST executables (not provided). Kindly download the BLAST executables from the following link based on your OS. The blast directory should be in the same folder as afpropred.py

example_input.fasta : Example file containing protein sequences in FASTA format

example_output.csv : Example output file for the program