A ML classification model is created to find potential ligand molecules for NS2B/NS3 proteins to inhibiting Zika virus replication
- The NS2B and NS3 proteins are essential components of the viral protease complex in Flaviviruses, which includes Zika virus and Dengue virus. The
NS3 protein acts as the catalytic subunit
, while theNS2B protein acts as a cofactor
, forming a tightly associated complex that is responsible for the proteolytic processing of the viral polyprotein. - The NS2B/NS3 protease complex of Zika virus and Dengue virus share a
high degree of structural similarity
, with the overall fold and arrangement of thetwo proteins being highly conserved
. Theactive site residues
and thesubstrate-binding pockets
are also verysimilar
, which allows forthe development of pan-Flavivirus inhibitors that can target both Zika and Dengue viruses
.
- Machine Learning classification model building and screening of DrugBank
- Virtual screening of potential active molecules using Maestro
- Perform MD Simulation of selected molecules using Gromacs
- NS3 protein bioactivity data collection from CHEMBL
- Selecting data on the basis of IC50 values
- Pre-processing data (handling missing values, removing invalid smiles, converting smiles to canonical smiles)
- Dividing molecules into active and inactive on the basis of IC50 values (IC50<=5000nM --> Active, IC50>=10000nM ----> Inactive)
- Generating Morgan fingerprints using rdkit
- Applying PCA to reduce dimesnion of data
- Training various machine learning classification models and selecting the best ones
- Screening drug bank molecules uing trained models to get potential active molecules
- Result: 213 potentially active molecules were obtained and were used for virtual screening
Virtual screening was performed on 213 obtained molecules
-
Docked Molecules
-
- DB17692
-
- DB18036