Background: In various biological processes and cell functions, Post Translational
Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM,
which occurs following protein synthesis. The experimental determination of hydroxyproline sites in
an uncharacterized protein sequence requires extensive, time-consuming and expensive tests.
Methods: With the torrential slide of protein sequences produced in the post-genomic age, certain
remarkable computational strategies are desired to overwhelm the issue. Keeping in view the
composition and sequence order effect within polypeptide chains, an innovative in-silico predictor via
a mathematical model is proposed.
Results: Later, it was stringently verified using self-consistency, cross-validation and jackknife tests
on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values
are superior to the values predicted by previous methodologies.
Conclusion: This new mathematical technique is the most appropriate and encouraging as compared
with the existing models.