Pupstruct: Prediction of pupylated lysine residues using structural properties of amino acids

Vineet Singh, Alok Sharma, Abdollah Dehzangi, Tatushiko Tsunoda

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Post-translational modification (PTM) is a critical biological reaction which adds to the diversification of the proteome. With numerous known modifications being studied, pupylation has gained focus in the scientific community due to its significant role in regulating biological processes. The traditional experimental practice to detect pupylation sites proved to be expensive and requires a lot of time and resources. Thus, there have been many computational predictors developed to challenge this issue. However, performance is still limited. In this study, we propose another computational method, named PupStruct, which uses the structural information of amino acids with a radial basis kernel function Support Vector Machine (SVM) to predict pupylated lysine residues. We compared PupStruct with three state-of-the-art predictors from the literature where PupStruct has validated a significant improvement in performance over them with statistical metrics such as sensitivity (0.9234), specificity (0.9359), accuracy (0.9296), precision (0.9349), and Mathew’s correlation coefficient (0.8616) on a benchmark dataset.

Original languageEnglish (US)
Article number1431
Pages (from-to)1-13
Number of pages13
Issue number12
StatePublished - Dec 2020

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)


  • Amino acids
  • Lysine pupylation
  • Post-translational modification (PTM)
  • Prediction
  • Protein sequences
  • Structural features


Dive into the research topics of 'Pupstruct: Prediction of pupylated lysine residues using structural properties of amino acids'. Together they form a unique fingerprint.

Cite this