Pauling runs physics-based computational chemistry -- docking with UniDock, molecular dynamics with GROMACS, ADMET profiling, structure validation with MolProbity and PoseBusters. Every result is a real simulation on actual molecular structures, not a language model prediction. BiOmni applies LLMs to biological research -- useful for reasoning across datasets, but it cannot dock a molecule or compute a binding energy.
| Category | Pauling | BiOmni |
|---|---|---|
| Biological data analysis | Focused on small-molecule and protein structure data | Core strength -- LLM reasoning across biological datasets |
| Multi-omics integration | Not in scope -- focused on computational chemistry | Can reason across genomics, proteomics, transcriptomics data |
| Molecular docking | UniDock (GPU-accelerated Vina) with explicit scoring functions | Cannot run molecular docking |
| MD simulation | Full GROMACS MD with save/resume, ACPYPE ligand parameterization | No molecular dynamics capability |
| Virtual screening | 10M+ compounds via Cloud Dataflow auto-scaling | Cannot screen compound libraries |
| ADMET profiling | Integrated ADMET prediction pipeline | Cannot compute ADMET properties |
| Structure validation | PoseBusters pose QC + MolProbity structure checks | No structural validation tools |
| Binding energy calculation | MM-PBSA from explicit MD trajectories | Cannot compute binding energies |
| Computational pipelines | End-to-end: P2Rank pocket detection, docking, MD, ADMET | LLM-based analysis only -- no simulation execution |
| Drug discovery focus | Purpose-built for computational drug discovery | Broad biological research -- not specialized for drug discovery |
| File format handling | Automatic PDB, PDBQT, SDF, MOL2, CIF, SMILES conversion | Cannot parse molecular structure files |
| Infrastructure | Cloud GPUs, auto-scaling workers, no installation or licenses | LLM inference -- no HPC or molecular software |