Case Study 1 — GDC-0834 Solubility Rescue: Structure-Based Benchmarking Against REINVENT 4 and Ligand-Based Optimization

Case Study 1 includes two workflows: ligand-based and structure-based. Both use the “Improve solubility while maintaining target engagement” strategy.

A. Structure-Based Workflow

1. Project Setup

a) Select “Improve solubility while maintaining target engagement.”
b) Choose “Pareto Front.”
c) Select “2D fingerprint match” and upload IN.smi from the Case1-structure-based folder.
d) Select the reference 2D structure and click Save selections.
e) Keep default transformations.

2. Add Additional Scoring Functions

h) Add:
 • Drug-likeness score (QED)
 • AI-predicted synthesis ease
 • Solubility Level (LogS)
i) Leave transformations at default.

3. Configure Structure-Based Docking

j) Under structure-based settings, choose “Pharmacophore-Based Docking.”
k) Upload BTK.pdb and BTK.ph4 from the Case1-structure-based directory, then click Save & configure.
l) Keep default energy and pharmacophore transformations.

4. Training Parameters

m) Click Next.
n) Set AIMEDCRAFT Core Parameters as:
 • Batch size: 256
 • Training steps: 1000

Simulations take approximately 2 days with these settings.

5. Run & Analyze

o) Click Next, then Submit.
p) After completion, open the job via the Completed Jobs tab.
q) View detailed results through Analysis, where all generated molecules can be filtered and visualized.
r) Use Pareto Analysis to view multi-objective performance and select top analogues.

B. Ligand-Based Workflow

1. Project Setup

a) Select “Improve solubility while maintaining target engagement.”
b) Choose “Pareto Front” as the optimization method.
c) Select “2D fingerprint match” and upload IN.smi from the Case1-ligand-based folder.
d) Select the reference 2D structure and click Save selections.
e) Leave default transformations.

2. Add Pharmacophore Fit

f) Select “3D pharmacophore fit”, click&n