v0.4.0: add backbone PDB download + 3D viewer link

- Predict now also rebuilds backbone PDB via alphadynamics.trajectory_to_pdb
- New File output: Download backbone PDB (50-frame subsample)
- Diagnostic: Rg + end-to-end distance shown alongside basin populations
- Link to online 3Dmol viewer at GitHub Pages

app.py

@@ -215,14 +215,35 @@ def predict(sequence: str, n_ensemble: int, rollout_steps: int):
         model_name="ad_transfer_v2_clean",
     )
 
+    # Generate backbone PDB (NEW v0.4.0)
+    try:
+        from alphadynamics import trajectory_to_pdb, trajectory_diagnostics
+        pdb_path = Path(tempfile.gettempdir()) / f"alphadynamics_{sequence}_backbone.pdb"
+        # Use ensemble member 0, subsample to 50 frames for fast download
+        member = traj[0]
+        if len(member) > 50:
+            idx = np.linspace(0, len(member) - 1, 50).astype(int)
+            member = member[idx]
+        trajectory_to_pdb(member, sequence, str(pdb_path))
+        diag = trajectory_diagnostics(member)
+        diag_md = (
+            f"\n\n**3D backbone diagnostics** (Cα-only, 50 frames):\n"
+            f"- Radius of gyration: {diag['rg_mean']:.2f} ± {diag['rg_std']:.2f} Å\n"
+            f"- End-to-end distance: {diag['end_to_end_mean']:.2f} ± {diag['end_to_end_std']:.2f} Å"
+        )
+    except Exception as e:
+        pdb_path = None
+        diag_md = f"\n\n*(PDB rebuild unavailable: {e})*"
+
     fig = make_ramachandran_figure(traj, sequence)
     info = (
         f"### `{sequence}` — {len(sequence)} residue{'s' if len(sequence) > 1 else ''}\n\n"
         f"**{n_ensemble}** trajectories × **{rollout_steps}** steps "
         f"= **{n_ensemble * rollout_steps * len(sequence):,}** torsion samples\n\n"
         + basin_table_md(traj)
+        + diag_md
     )
-    return fig, info, str(out_path)
+    return fig, info, str(out_path), str(pdb_path) if pdb_path else None
 
 
 # ----------------------------------------------------------------------------
@@ -302,13 +323,19 @@ with gr.Blocks(title="AlphaDynamics") as demo:
             predict_btn = gr.Button("Predict torsion dynamics 🚀", variant="primary")
             info_md = gr.Markdown(label="Basin populations")
             file_out = gr.File(label="Download trajectory (.npz)")
+            pdb_out = gr.File(label="Download backbone PDB (NEW v0.4.0)")
+            gr.Markdown(
+                "💡 **3D viewer:** open the downloaded `.pdb` in "
+                "[PyMOL](https://pymol.org/) / VMD / ChimeraX, or browse online at "
+                "[krisss0mecom.github.io/AlphaDynamics/examples/3d_movie_demo](https://krisss0mecom.github.io/AlphaDynamics/examples/3d_movie_demo/viewer.html)"
+            )
         with gr.Column(scale=2):
             plot_out = gr.Plot(label="Ramachandran density")
 
     predict_btn.click(
         fn=predict,
         inputs=[seq_input, n_ens_input, rs_input],
-        outputs=[plot_out, info_md, file_out],
+        outputs=[plot_out, info_md, file_out, pdb_out],
     )
 
     gr.Examples(