Background: ZIKV has been a well-known global threat, which hit almost all of the
American countries and posed a serious threat to the entire globe in 2016. The first
outbreak of ZIKV was reported in 2007 in the Pacific area followed by another severe
outbreak, which occurred in 2013/2014 and subsequently, ZIKV spread to all other
Pacific islands. A broad spectrum of ZIKV associated neurological malformations in
neonates and adults have driven this deadly virus into the limelight. Though tremendous
efforts have been focused on understanding the molecular basis of ZIKV, the viral
proteins of ZIKV have still not been studied, extensively.
Objectives: Herein, we report
the first and the novel predictor for identification of ZIKV proteins.
Method: We have
employed Chou’s pseudo amino acid composition (PseAAC), statistical moments and
various position-based features.
Results: The predictor is validated through 10-fold
cross-validation and Jackknife testing. In 10-fold cross-validation, 94.09% accuracy,
93.48% specificity, 94.20% sensitivity and 0.80 MCC was achieved, while in Jackknife
testing, 96.62% accuracy, 94.57% specificity, 97.00% sensitivity and 0.88 MCC was
Conclusion: Thus, ZIKVPred-PseAAC can help in predicting the ZIKV proteins
in an efficient and accurate way and can provide baseline data for the discovery of new
drugs and biomarkers against ZIKV.