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Database Commons

a catalog of worldwide biological databases

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General information

Full name:
Description: The Phospho-DB Database presents the well curated information of the phosphorylation sites of different proteins of Plasmodium genus species. Based on the availability, the phosphosites data has been mined from published literature studies of the mass-spectrometry based phosphosite identification experiments covering different life stages of the parasite.
Year founded: 2023
Last update:
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Country/Region: India

Contact information

University/Institution: National Institute of Immunology
Address: National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi - 110067, India
Country/Region: India
Contact name (PI/Team): Debasisa Mohanty
Contact email (PI/Helpdesk):


Pf-Phospho: a machine learning-based phosphorylation sites prediction tool for Plasmodium proteins. [PMID: 35753700]
Priya Gupta, Sureshkumar Venkadesan, Debasisa Mohanty

Even though several in silico tools are available for prediction of the phosphorylation sites for mammalian, yeast or plant proteins, currently no software is available for predicting phosphosites for Plasmodium proteins. However, the availability of significant amount of phospho-proteomics data during the last decade and advances in machine learning (ML) algorithms have opened up the opportunities for deciphering phosphorylation patterns of plasmodial system and developing ML-based phosphosite prediction tools for Plasmodium. We have developed Pf-Phospho, an ML-based method for prediction of phosphosites by training Random Forest classifiers using a large data set of 12 096 phosphosites of Plasmodium falciparum and Plasmodium bergei. Of the 12 096 known phosphosites, 75% of sites have been used for training/validation of the classifier, while remaining 25% have been used as completely unseen test data for blind testing. It is encouraging to note that Pf-Phospho can predict the kinase-independent phosphosites with 84% sensitivity, 75% specificity and 78% precision. In addition, it can also predict kinase-specific phosphosites for five plasmodial kinases-PfPKG, Plasmodium falciparum, PfPKA, PfPK7 and PbCDPK4 with high accuracy. Pf-Phospho ( outperforms other widely used phosphosite prediction tools, which have been trained using mammalian phosphoproteome data. It also has been integrated with other widely used resources such as PlasmoDB, MPMP, Pfam and recently available ML-based predicted structures by AlphaFold2. Currently, Pf-phospho is the only bioinformatics resource available for ML-based prediction of phospho-signaling networks of Plasmodium and is a user-friendly platform for integrative analysis of phospho-signaling along with metabolic and protein-protein interaction networks.

Brief Bioinform. 2022:23(4) | 1 Citations (from Europe PMC, 2023-09-16)



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Created on: 2023-08-28
Curated by:
Yue Qi [2023-09-12]
Yuanyuan Cheng [2023-09-06]
Jane Young [2023-08-28]