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Konnect2prot has been published in bioinformatics

Curious about proteins and their interactome? Start your journey now.

Protein-protein interactions are central to understanding the functional relationship between proteins. We have curated the available information and augmented with context-specific analysis to ease your research journey.

Glance at konnect2prot

This is an indigenously developed web-based application designed by Dr. Samrat Chatterjee and his group, which can generate context-specific directional PPI networks from the input proteins and detect their biological and topological importance in the network. konnect2prot (k2p) contains data curated from various databases with multidimensional information to build a network relevant to the end user. This platform is also equipped with network algorithms that can further enhance the decision making process.

About Us

Who we are


Dr. Chatterjee's lab

We study biological systems in their entirety or in fragments through the lens of system biology. The former covers topics such as network biology, machine learning-based drug discovery, and so forth, while the latter covers various differential equation based kinetic models. The group is supervised by Dr. Samrat Chatterjee and consists of post doctoral fellows, PhD student and research fellows. They are mainly from mathematical and computational backgrounds keen to work on biological problems in an interdisciplinary environment.

Read More

Some significant recent publications from the group.

Paul, A., Azhar, S., Das, P, N., Bairagi, N., Chatterjee, S., Elucidating the metabolic characteristics of pancreatic β-cells from patients with type 2 diabetes (T2D) using a genome-scale metabolic modeling. Computers in Biology and Medicine, (vol. 144) 105365, (2022).

Halder S., Ghosh S., Chattopadhyay, J., Chatterjee, S., Bistability in cell signalling and its significance in identifying potential drug targets. Bioinformatics, (vol. 37(22)), pp. 4146-4163 (2021).

Sarmah, D T., Bairagi, N., and Chatterjee, S., Tracing the footsteps of autophagy in computational biology. Briefings in Bioinformatics, 22(4), bbaa286, (2021).


Features that makes us different


All the interactions of k2p are causal, i.e. directed.


The user can construct context-specific networks using various filters like cellular localization, biological process, molecular functions, and pathways.


Using voterank algorithm, k2p identifies spreaders in the network.

Network topology

Various topological measures are used in k2p to identify important proteins such as bottlenecks, hubs etc.

Structural information

Structural information like co-crystal details,exeriment type, resolution,PDB ID and ligand information is available.

Enrichment analysis

Using Enrichr, k2p does ontological and pathway enrichment.

Disease interactome

The multi-disease landscape of the proteins in the PPI network can be identified.


The information of PTMs of proteins are available.

Protein classes

We have also provided classes of every protein in PPI network.


Chevaliers behind konnect2prot

Dr. Samrat Chatterjee

Associate professor

He is a Mathematician. He uses mathematical modelling and system biology to understand biological problems. He formulated and supervised the project.

Dr. Shailendra Asthana

Principal Scientist-I

He is a Computational Biophysicist. His main area of research is structural bioinformatics and drug discovery. He helped in the supervision of the project.

Shivam Kumar

PhD Student

He is doing PhD in Computational Biology. His major work domain is to develop pattern recognition algorithms using AI/ML. He designed and developed the web application.

Dipanka Tanu Sarmah

Research Fellow

His research focuses in exploring complexity of biological system using mathematical modeling and network biological approaches. He helped in curation and designing the application.

Other contributers: Ekant Sharma, Komal Sharma, Krishna


We could not make the difference without them

Department of Biotechnology

We would like to thank DBT for proving us the finanical support for this project.

Funding body by Govt. of India


We would like to thank OmniPath for providing directional relationship of protein pairs.

Directional database for PPI

Signor 2.0

We would like to thank signor for providing directional relationship of protein pairs.

Directional database for PPI


We would like to thank disgenet for providing disease information related to protein.

Disease database

Kyoto Encyclopedia of Genes and Genomes (KEGG)

We would like to thank KEGG for providing information of biological pathways associated with proteins.

Biological pathway database

Gene ontology (GO)

We would like to thank GO for providing information of biological process and molecular functions associated with proteins.

Biological ontology database

The Human Protein Atlas (HPA)

We would like to thank HPA for providing information of tissue specific expression and subcellular associated with proteins.

Human Protein Atlas

Translational Health Science and Technology Institute

We would like to thank THSTI for providing the infrastructure to carry out the work.



We would like to thank uniprot for providing detailed information of protein charaterstics including its functions and pathways.

Protein information database


We would like to thank Enrichr for providing enrichment score of pathway, functions and diseases.

Protein enrichment webserver

Protein data bank (PDB)

We would like to thank PDB for providing structure related information.

Protein structure database

The Drug Gene Interaction Database (DGIdb)

We would like to thank DGIdb for providing information of ligands and classes associated with proteins.

Drug target database


We would like to thank signalink for providing information of signalling pathways associated with proteins.

Signalling pathway database

Database of Curated Mutations (DoCM)

We would like to thank DoCM for providing information of disease-causing mutations associated with proteins.

Disease mutation database

We would also like to pass our gratitude to open source software develpers of Flask, Python, Dash (Plotly), MongoDB.


Frequently Asked Questions

What is konnect2prot (k2p)?

k2p is a one-stop junction for identifying the spreaders in a PPI network constructed from user-given inputs. It is a web application of directional PPI which can be filtered according to user-driven context. Currently, context-specificity is defined as filtering the network through the use of localization, pathways, biological processes, molecular functions, and tissue specificity. Additionally, it also displays structural insights into the proteins, their available ligands, and disease-specific mutations.

Which organism k2p covers?

Currently it contains only proteins from human interactome.

From which databases does k2p extract the curated data?

k2p extracts causal information data from the signor and omnipath. The cellular localization and tissue-specificity information is curated from The Human Protein Atlas, information of pathways are taken from the kegg, biological process, and molecular function information is curated from GO, protein class and ligands information is taken from DGIdb, disease-based information is curated from DisGeNet, the structural information is curated from the PDB database and finally the disease mutation data is taken from the D3 distal database.

What is the importance of spreaders?

Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading which are identified using the voterank algorithm. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of the elected spreader will be decreased in subsequent turns. During the investigation, the identified spreaders could be explored for various applications such as potential drug targets.

How can I obtain the complete dataset?

k2p only allows the extraction of various network images and statistical information generated from the network. The complete data is available upon request.

Which tool is used for pathways and ontological enrichment?

k2p has used Enrichr for the enrichment of biological pathways and ontological enrichment.

Is it commercial and copyright protected?

k2p is a non-commercial open-access web application for academic purposes only. It is copyright protected under Indian Copyright Dairy No.: 14303/2020-CO/SW and funded by the Department of Biotechnology (DBT) (Ministry of Science and Technology, Govt. of India). Grant number: BT/PR15426/BRB/10/1459/2015.

Do I need permission to use the result/image of k2p in my publication?

You don't require any permission, however, the citation to our manuscript will be highly appreciated.

How to cite us?

Shivam Kumar, Dipanka Tanu Sarmah, Shailendra Asthana, Samrat Chatterjee, konnect2prot: A web application to explore the protein properties in a functional protein-protein interaction network, Bioinformatics, 2022;, btac815, https://doi.org/10.1093/bioinformatics/btac815

Where can you get the terminologies used in k2p?

Please visit the tutorial page for more details.

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