Background: ZIKV has been a well-known global threat, which hits 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 has 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 the identification of ZIKV proteins.
Methods: 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
were achieved while in Jackknife testing, 96.62% accuracy, 94.57% specificity, 97.00% sensitivity
and 0.88 MCC were achieved.
Conclusion: Thus, ZIKVPred-PseAAC can help in predicting the ZIKV proteins efficiently and
accurately and can provide baseline data for the discovery of new drugs and biomarkers against ZIKV.