Introduction: The human tau protein is a key protein involved in various neurodegenerative disease (NDs) including Parkinson’s disease (PD). The protein has high tendency to aggregate into oligomers, subsequently generating insoluble mass in the brain. Symptoms of PD include tremor, bradykinesia, rigidity, and postural instability. Currently drugs for PD treatment are only symptom-targeted while effective therapeutic treatment remains a challenge. The objective of this study is to identify novel promising anti-PD drugs using computational techniques. Method: ligand-based (LB) receptor modelling was conducted using LigandScout, validated and subjected to Glide XP docking, virtual screening, ADMET, and molecular dynamics predictions. Results: The adopted LB modelling generated pharmacophoric features of 5 hydrogen bond donors, 1 aromatic rings, and 7 hydrogen bond acceptors. The validation result indicated GH score of 0.73 and EF of 36.30 as validation protocols, probing it to be an ideal model. Using 3D query of the modelling a total of 192 compounds were retrieved from interbioscreen database containing 70,436 natural compounds. Interestingly, ligands 1, 2, 3, 4 and 5 orderly indicated higher binding affinities to the receptor with Glide XP docking of -7.451, -7.368, -7.101, -6.878, and -6.789 compared to a clinical drug Anle138b with -4.552 kcal/mol respectively. Furthermore, molecular dynamics and pkCSM pharmacokinetics demonstrated ligands 1, 2, & 4 having better stability and low toxicity profiles compared to the reference. Conclusion: In summary, the study pave way for discovery of small molecules that could be recommended as adjuvant /single candidate as ant-PD candidates upon further translational study.