The Engine

The Target Analytics Dashboard is Revilico’s unified platform for comprehensive protein analysis, designed to help you understand therapeutic targets from sequence to structure. It integrates multiple computational modules, including Structural Analysis, Melting Temperature Prediction, and Stability (ΔΔG) Calculation, to characterize a protein’s conformation, flexibility, and thermodynamic behavior.

Users can upload their protein sequences or PDB structures to automatically generate an interactive report on target druggability, binding site architecture, and mutation sensitivity, all in a single streamlined interface.

The Algorithm

The dashboard unifies several specialized computational pipelines:

1. Structural Analysis Engine: Quantifies conformational differences across wild-type and mutant structures via Ramachandran plots, contact maps, solvent-accessible surface area (SASA), and RMSD/GDT metrics.

2. Melting Temperature Prediction: Uses deep protein language models to infer stability directly from sequence, predicting the temperature at which half the protein unfolds (Tm).

3. Stability Calculation (ΔΔG): Estimates the thermodynamic effect of mutations on folding energy using structure-based energy decomposition and all-atom scoring.

All results are visualized through intuitive, interactive plots and downloadable data tables, enabling rapid integration into broader modeling and screening workflows.

Algorithm Validation

Each module of the Target Analytics Dashboard is validated against experimental and literature benchmarks:

• Structural Analysis correlates with crystallographic and cryo-EM reference datasets, reproducing RMSD and GDT-TS measures consistent with homology model accuracy.

• Melting Temperature predictions are benchmarked against proteins with known Tm values, using pretrained language models such as ProtBERT and ESM to achieve robust generalization across target classes.

• Stability (ΔΔG) predictions are aligned with experimentally derived mutagenesis and thermal shift assay data, achieving strong qualitative agreement in direction (stabilizing vs destabilizing).

These validations ensure each output, from conformational flexibility maps to thermal stability estimates, reflects real-world target behavior.

Scientific Impact

The dashboard enables new kinds of analyses that link protein biophysics to druggability, including:

• Mapping mutation-specific effects on stability and binding site geometry.

• Quantifying structural flexibility for ensemble docking and induced-fit modeling.

• Integrating thermodynamic and conformational data to improve ligand binding predictions.

• Identifying cryptic or allosteric pockets through surface exposure and contact-map analytics.

By uniting thermal, structural, and energetic dimensions of protein characterization, the Target Analytics Dashboard empowers researchers to make data-driven target selection decisions, accelerating the path from sequence to therapy.

Business Impact

By centralizing protein evaluation into one automated platform, the Target Analytics Dashboard helps teams:

• Accelerate early target triage by identifying unstable or undruggable proteins before experimental validation.

• Reduce costs and timelines associated with repeated wet-lab characterization.

• Enhance structure-based design workflows by selecting targets with favorable stability and flexibility profiles.

• Support cross-functional collaboration between computational, medicinal, and structural biology teams through unified visual reports.

This capability transforms weeks of biophysical characterization into minutes of analysis, a direct advantage for pipeline efficiency and ROI.