StarPep toolbox User Guide
Preface
Welcome to the StarPep toolbox project GitHub repository. Here is where all the components of the project are developed, reviewed, and maintained.
About the Software
StarPep toolbox is a software for studying the antimicrobial peptides’ (AMPs) chemical space with molecular network-based representations and similarity searching models. This application aims to contribute to peptide drug repurposing, development, and optimization.
This tool was developed as a Java desktop application that integrates the functionalities of several open-source projects. The graphical user interface was built on top of the NetBeans Platform, using the Java SE Runtime Environment 8. The graph database structure was implemented with the Neo4j platform. Some visualization features and the calculation of network properties were based on Gephi. The sequence alignment algorithms were implemented using the BioJava API.
The AMPs were collected from a large variety of biological data sources to be organized into an integrated graph database called starPepDB, composed of 45.120 AMPs and their metadata. This integrated graph database is embedded in StarPep toolbox to enable end-user querying, filtering, visualizing, and analyzing the AMPs taking advantage of network-based representations.
The main features of StarPep toolbox are listed below:
AMPs’ chemical space filtering: obtain a subset of AMPs from the StarPepDB using their metadata (function, target pathogen, biological origin, chemical modifications, original database, and cross-referenced entries to PDB, PubMed, and UniProt).
Molecular descriptors: calculate molecular descriptors of the AMPs by applying statistical and aggregation operators on physicochemical amino acid properties (e.g., net charge, isoelectric point, molecular weight, etc.).
Network Science: build different types of networks (metadata, chemical space, and half-space proximal) and calculate global/local properties, centrality metrics, communities, etc.
Similarity searching: create multi-query similarity searching models that can lead to the repurposing of AMPs with novel functional activities.
The Team
This project was developed by members and collaborators of the Grupo de Medicina Molecular y Traslacional (MeM&T) at Universidad San Francisco de Quito, which is lead by Yovani Marrero-Ponce.
Contributing
We encourage your participation as a contributor in this project considering your interest, availability, or skill requirements. Detailed information about ways of collaborating on this project can be found in our contributing guidelines.
License
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Get in touch
If you want to report a problem or suggest an improvement, you should open an issue at this Github repository, and we can follow your questions or suggestions. But, you can also contact Yovani by emailing ymarrero77@yahoo.es.