AI4AMP_predictor

AI4AMP is a sequence-based antimicrobial peptides (AMP) predictor based on PC6 protein encoding method [link] and deep learning.

AI4AMP (web-server) is freely accessible at http://symbiosis.iis.sinica.edu.tw/PC_6/

Here we give a quick demo and command usage of our AI4AMP model.

1. quick demo of our PC6 model

For quick demo our model, run the command below

bash AI4AMP_predictor/test/example.sh

The input of this demo is 10 peptides (test/example.fasta) in FASTA format.

The prediction result (test/example_output.csv) below shows prediction scores and whether the peptide is an AMP in table.

2. command usage

Please make sure your working directory access to PC6/PC6_predictor.py and execute command like the example below

python3 PC6_predictor.py -f [input.fasta] -o [output.csv]

-f : input peptide data in FASTA format

-o : output prediction result in CSV

AI4AMP deep neural network model architecture

The model architecture consists of one convolution layer, one long short-term memory (LSTM) layer, and one dense layer, which is a typical architecture in natural language processing (NLP) tasks.

The figure above shows AI4AMP model architecture. After PC6 encoding, protein sequences will pass through one convolution layer, one LSTM layer, and one dense layer.