konnect2prot: a web application to explore the protein properties in a functional protein–protein interaction network

Author:

Kumar Shivam1,Sarmah Dipanka Tanu1,Asthana Shailendra2,Chatterjee Samrat1ORCID

Affiliation:

1. Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster , Faridabad 121001, India

2. Non-communicable Disease Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster , Faridabad 121001, India

Abstract

Abstract Motivation The regulation of proteins governs the biological processes and functions and, therefore, the organisms’ phenotype. So there is an unmet need for a systematic tool for identifying the proteins that play a crucial role in information processing in a protein–protein interaction (PPI) network. However, the current protein databases and web servers still lag behind to provide an end-to-end pipeline that can leverage the topological understanding of a context-specific PPI network to identify the influential spreaders. Addressing this, we developed a web application, ‘konnect2prot’ (k2p), which can generate context-specific directional PPI network from the input proteins and detect their biological and topological importance in the network. Results We pooled together a large amount of ontological knowledge, parsed it down into a functional network, and gained insight into the molecular underpinnings of the disease development by creating a one-stop junction for PPI data. k2p contains both local and global information about a protein, such as protein class, disease mutations, ligands and PDB structure, enriched processes and pathways, multi-disease interactome and hubs and bottlenecks in the directional network. It also identifies spreaders in the network and maps them to disease hallmarks to determine whether they can affect the disease state or not. Availability and implementation konnect2prot is freely accessible using the link https://konnect2prot.thsti.in. The code repository is https://github.com/samrat-lab/k2p_bioinfo-2022.

Funder

Department of Biotechnology

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference43 articles.

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