Pauling vs. Schrodinger

Pauling delivers docking, MD, ADMET, and pocket detection through a conversational interface on cloud infrastructure -- no licenses, no tokens, no desktop installation, minutes from signup to first result. Schrodinger is powerful -- Glide and FEP+ are industry gold standards -- but it's $35,000+/year per workstation with token-based licensing and a steep learning curve.

Category Pauling Schrodinger
Docking engineUniDock (GPU-accelerated Vina) -- fast, validated scoringGlide (SP/XP) -- industry-gold-standard pose prediction and enrichment
Free energy perturbationNot yet availableFEP+ -- best-in-class relative binding free energy, widely validated
MD simulationsGROMACS with auto ligand parameterization (ACPYPE), checkpoint save/resumeDesmond -- highly optimized, GPU-accelerated, tight Maestro integration
ADMET profilingIntegrated into conversational workflowQikProp -- established ADMET prediction, but separate module
Pocket detectionP2Rank (ML-based, automatic)SiteMap -- physics-based, accurate, requires manual setup
Pose quality controlPoseBusters (automatic, physics-based QC)Visual inspection in Maestro; no automated QC equivalent
Cost modelPay-per-compute, no license fees$35K+/year per seat; token-based for cloud jobs
LicensingNone -- browser-based accessPer-seat or token-based; enterprise negotiations required
InterfaceConversational AI -- describe what you want in natural languageMaestro GUI -- powerful but steep learning curve
Cloud scalingAuto-scales to hundreds of workers on Google Cloud DataflowLiveDesign/Cloud available but adds significant cost
Setup timeMinutes (sign up and run)Days to weeks (installation, license server, configuration)
Learning curveLow -- guided by conversationHigh -- Maestro, command-line tools, scripting for automation
File format handlingAutomatic conversion (PDB, SDF, MOL2, SMILES, CIF, PDBQT)Maestro handles formats but workflows require manual prep steps
Structure validationMolProbity integratedProtein Preparation Wizard -- comprehensive, well-validated