# GPSE

**Repository Path**: zhaoy2020/GPSE

## Basic Information

- **Project Name**: GPSE
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-01-16
- **Last Updated**: 2022-01-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# GPSE
Genome-scaled Prediction of Substrate-specific Enzymes

**With breadkthrough made by AlphaFold2, this repo is about to be updated as a "plugin" of AlphaFold, for more accurate enzyme discovery!**

The workflow:

![img](/img/GASSER.svg)

##### The philosophy:

In the post-genomic era, genome mining has been one of the most powerful tools leading to the discovery of new enzymes with properties of interest, and the combination of biological features like thermophilic and the sequence-based method like BLAST is the dominant approach. In this way, numerous enzymes have been found out and some of them have industrial applications. Also, with the development of structure-related computational methods involving docking and modeling, rational design and even de novo design of new enzymes have become a reality.

The accumulation of sequences ensures us unlimited biomineral and the development of structure-related computational methods endue us powerful tools to mine more effectively and completely.

##### Usage:  
Before run GPSE to a genome or a dataset of sequences, users should carefully modify the `GPSEcfg.py` file and change every path according to the system!  
```
python3 GPSE.py proteins.fasta ligand.pdb EC_number

GPSE: Genome-scale Prediction of Substrate-specific Enzymes

positional arguments:
  input           input a seqence in fasta format and we highly suggest that
                  you make the head linesimple
  ligand          ligand or substrate in pdb
  EC_number       the EC_number in form of x_x_x (e.g. 3_1_1 for 3.1.1.
                  carboxylic-ester hydrolase)

optional arguments:
  -h, --help      show this help message and exit
  -nos NOS        Max Number Of Structures you wish to be predicted for each
                  sequence, defult is 1
  -nt NT          Number of Threads used to run BLAST, default is 8
  -evalue EVALUE  E-Value cutoff for structure template, default is 1e-5
  -ic IC          the Identity Cutoff for structure prediction, default is 30
```
##### Reference:  
Sun J, Xia Y and Ming D (2020) Whole-Genome Sequencing and Bioinformatics Analysis of Apiotrichum mycotoxinivorans: Predicting Putative Zearalenone-Degradation Enzymes. Front. Microbiol. 11:1866. doi: 10.3389/fmicb.2020.01866