Author: Shashank Kashyap
Emerging viral threats like SARS-CoV-2 and persistent pathogens like Influenza A Virus (IAV) share a dependency on host cellular machinery. This project utilizes a comparative systems biology approach to identify "Conserved Host Dependency Factors" (HDFs)—host proteins essential for the replication of both viruses.
By integrating high-confidence AP-MS interactome data with the human physical interactome, this study identifies novel therapeutic targets that could serve as the basis for broad-spectrum antivirals.
The study followed a multi-stage computational workflow utilizing Python (Pandas, Scipy) for data processing and NetworkX for topological analysis.
- Data Harmonization: High-confidence interactomes (Gordon et al. for SARS-CoV-2; Shapira et al. for IAV) were mapped to UniProt IDs.
- Comparative Analysis: Identification of direct overlap (conserved targets) and statistical validation using hypergeometric testing.
- Network Topology Analysis: Development of a custom algorithm to identify "Bridge Proteins"—hidden connectors in the human PPI network linking disparate viral targets.
- Functional Enrichment: Pathway analysis using g:Profiler (GO, KEGG, Reactome).
- Druggability Assessment & Docking: Screening via DrugBank/ChEMBL and molecular docking simulation using AutoDock Tools.
Figure 1: Computational pipeline for the identification of conserved virus-host factors.
Despite the differences in viral families, the analysis identified 4 highly conserved host factors shared by both viruses: HOOK1, MIPOL1, EXOSC8, and TCF12.
- Statistical Significance: Hypergeometric test p-value = 0.051.
Figure 2: Overlap of high-confidence host factors between SARS-CoV-2 and Influenza A.
A novel network analysis revealed 13 Bridge Proteins (e.g., TRIM28, PABPC1) that do not directly interact with both viruses but serve as functional connectors between the two viral interactomes. This creates a hidden signaling hub centered on PI3K/AKT and mTOR signaling.
Figure 3: Conceptual network model showing Bridge Proteins connecting unique viral targets.
Conserved and bridge proteins converged on critical biological processes, specifically RNA metabolic processes and Nuclear Pore transport, highlighting the viral strategy of hijacking host manufacturing systems.
Figure 4: Dot plot showing distinct biological themes for bridge and virus-specific proteins.
Based on tractability scores (OpenTargets) and chemical validation (ChEMBL), TCF12 and EXOSC8 were prioritized as top therapeutic candidates.
Molecular Docking Result:
A docking simulation of TCF12 (PDB: 1W76) with a known small-molecule modulator revealed a stable, high-affinity interaction.
- Binding Energy: -6.8 kcal/mol
- Mechanism: Stable binding within a defined pocket on the protein surface.
Figure 5: 2D Interaction map and 3D binding pose of the ligand within the TCF12 active site.
This repository contains an overview of the analysis and key visualizations.
As this is a formal project report submitted for the award of Bachelor of Engineering, the full thesis document and code scripts are not publicly available in this repository.
Recruiters & Academic Collaborators:
If you wish to review the full project report, detailed statistical analysis, or discussion on the "Bridge Protein" algorithm, please contact me directly:
📧 Email: [email protected]
🔗 LinkedIn: https://www.linkedin.com/in/shashank-kashyap-805309238/
- Data Sources: BioGRID, STRING DB v12.0, UniProt.
- Libraries: Python (NetworkX, Matplotlib, Seaborn, Pandas).
- Structural Tools: AutoDock Tools, UCSF ChimeraX, Discovery Studio Visualizer.