APPLES

Allosteric Protein-protein interaction Pocket Likelihood Evaluation System (APPLES)

1. Introduction

Allosteric effect, as the "second code of life", is a direct and effective way for protein macromolecular machines to regulate their own functions, and will become a research hotspot in the post-AlphaFold era. Based on our previous research results, this project intends to focus on the allosteric mechanism of protein complexes at the level of structural systems biology, and comprehensively use a variety of theoretical calculation methods to study the allosteric mechanism for targeting PPIs. Integrating the sequence conservation and coevolutionary information, as well as the topological and dynamic properties of network, we built APPLES - a computing platform for the systematic study of allosteric mechanism. We hoped that the completion of this project can provide theoretical guidance and bioinformatics tools for the design of allosteric drugs targeting the protein-protein interactions.

The workflow of APPLES is shown below:

2. Usage

1. Anaconda is recommended for the APPLES and only Unix/Linux/MacOS operating systems are allowed.
2. External software to install: ChromeDriver
3. Python packages in need: os, re, string, sys, time, numpy, scipy, pandas, prody, wget, selenium
4. R packages in need: NACEN
5. Python language version: >= 3.7
6. R language version: >= 3.2.0
7. NACEN package can be downloaded from the website: http://sysbio.suda.edu.cn/NACEN/NACEN.rar. NACEN requires DSSP program for building AAN (Amino Acid Network) which can be installed with command:

conda install -c salilab dssp

8. The input of the program is a PDB file containing multiple chains and users can choose the chains they need. Before running Run_APPLES.py, please modify line 39, line 40 for PDB chain identifiers and line 41 for PDB files. Then, change the working directory into codes folder and run the following command.

python3 Run_APPLES.py

3. Examples

• Example PDB input file can be referred to PPI.pdb.

• The intermediate files obtained during the calculation are detailed in OUTPUTS folder.

• Key output file with P values and APPLES Score can be referred to APPLES_PPI.csv.

  For questions and data requirements, please contact yzhu99@stu.suda.edu.cn.

4. Reference

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• UniProt BLAST (https://www.uniprot.org/blast/)
• Clustal Omega Web Server (https://www.ebi.ac.uk/Tools/msa/clustalo/)
• Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., … SciPy 1.0 Contributors. (2020). SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17, 261–272.