Pauling executes -- upload a protein, screen millions of compounds, run MD simulations, get validated drug candidates back. Google Co-Scientist generates research hypotheses and experimental plans using Gemini. It's a thinking tool, not a doing tool. Hypotheses are cheap. Computational validation is what moves projects forward.
| Category | Pauling | Google Co-Scientist |
|---|---|---|
| Hypothesis generation | Data-driven -- hypotheses emerge from simulation results | Core strength -- generates novel research hypotheses via Gemini |
| Experimental design | Focused on computational experiment setup and execution | Designs multi-step experimental plans with literature backing |
| Molecular docking | UniDock (GPU-accelerated Vina) with explicit scoring | Cannot execute docking -- suggests docking as an experiment step |
| MD simulation | Full GROMACS MD with save/resume, ACPYPE parameterization | Cannot run MD -- may recommend MD in a research plan |
| ADMET profiling | Integrated ADMET pipeline on computed hits | Can suggest ADMET studies, cannot run them |
| Virtual screening | 10M+ compounds via Cloud Dataflow auto-scaling | No compound screening capability |
| Binding validation | MM-PBSA binding energies from explicit MD trajectories | Cannot compute binding energies |
| Computational execution | Real simulations on cloud GPUs -- every result is computed | None -- generates plans and ideas, does not execute computation |
| Pose quality control | PoseBusters + MolProbity validation on all outputs | No structural validation |
| Data ownership | Private molecule catalogs (owner_id), full file access | Google-hosted -- data handling governed by Google policies |
| Complementarity | Could act on hypotheses generated by Co-Scientist | Could generate hypotheses that Pauling then validates |