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feat: add AlphaFold 3D structure engine, CRISPR guide RNA designer, and scientific playground visualizers
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‎.gitignore‎

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*.exe
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*.obj
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*.pdb
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!data/*.pdb
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# IDE / editor files
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.vscode/

‎README.md‎

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@@ -178,17 +178,20 @@ let outcome = qreg.measure(0);
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println("Measured: " + to_string(outcome));
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```
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### 5. 🧬 Native Bioinformatics & Computational Genomics (`Bio`)
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### 5. 🧬 Native Bioinformatics & CRISPR Gene Editing (`Bio`)
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```aether
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// Parse biological sequences with genetic code translation & alignment
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let seq = Bio.Sequence("ATGGCGGCGCTAGCG");
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let seq = Bio.dna("ATGACTGAATATAAACTTGTGGTAGTTGGAGCTGATGGCGTAGGCAAGAGTGCCTTGACGA");
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let rna = seq.transcribe();
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let protein = seq.translate();
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let gc = seq.gc_content();
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let aligned = Bio.align_global("ATGGCG", "ATGCCG");
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// Colorized nucleotide terminal output
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println(Bio.colorize(seq));
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// Synthetic biology: CRISPR-Cas9 sgRNA guide design with on-target scoring & PAM scan
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let targets = seq.crispr_targets("NGG", 20);
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println("Top sgRNA spacer: " + targets[0].spacer + " | Score: " + to_string(targets[0].on_target_score));
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```
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### 6. 💊 Cheminformatics & Deep Drug Safety Screening (`Chem`)
@@ -206,6 +209,23 @@ println("PAINS Alerts: " + to_string(safety.pains_alerts));
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println("hERG Risk: " + safety.herg_cardiotoxicity_risk);
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```
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### 7. 🔬 AlphaFold & 3D Macromolecular Structure Analysis (`Bio.Structure`)
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```aether
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// Parse PDB coordinates & AlphaFold predictions
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let protein = Bio.Structure("data/kras_g12d_pocket.pdb");
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println("Atom Count: " + to_string(protein.atom_count()));
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println("Center of Mass: " + to_string(protein.centroid()));
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println("Radius of Gyration:" + to_string(protein.radius_of_gyration()) + " Å");
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// AlphaFold pLDDT confidence summary
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let plddt = protein.plddt_summary();
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println("Mean pLDDT: " + to_string(plddt.mean) + " (" + plddt.confidence_category + ")");
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// Drug binding pocket identification (contacts < 4.0 Å around inhibitor)
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let contacts = protein.ligand_pocket("MRT", 4.0);
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println("Pocket Residues: " + to_string(contacts.len()));
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```
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---
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## 🔬 Scientific Discovery & Reporting CLI

‎data/kras_g12d_pocket.pdb‎

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HEADER ONCOGENE/INHIBITOR 23-OCT-26 8AZM
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TITLE CRYSTAL STRUCTURE OF KRAS G12D BOUND TO MRTX1133 INHIBITOR
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REMARK 2 RESOLUTION. 1.65 ANGSTROMS.
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ATOM 1 N GLY A 10 12.450 24.120 15.340 1.00 92.50 N
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ATOM 2 CA GLY A 10 13.200 25.240 14.780 1.00 93.10 C
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ATOM 3 C GLY A 10 14.150 24.750 13.700 1.00 92.80 C
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ATOM 4 O GLY A 10 14.280 23.540 13.480 1.00 91.90 O
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ATOM 5 N ALA A 11 14.780 25.700 13.020 1.00 94.20 N
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ATOM 6 CA ALA A 11 15.720 25.380 11.950 1.00 95.40 C
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ATOM 7 C ALA A 11 15.020 24.710 10.770 1.00 94.80 C
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ATOM 8 O ALA A 11 15.650 24.080 9.900 1.00 93.50 O
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ATOM 9 CB ALA A 11 16.540 26.620 11.530 1.00 94.00 C
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ATOM 10 N ASP A 12 13.710 24.870 10.760 1.00 96.20 N
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ATOM 11 CA ASP A 12 12.890 24.280 9.700 1.00 96.80 C
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ATOM 12 C ASP A 12 12.820 22.760 9.820 1.00 95.90 C
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ATOM 13 O ASP A 12 12.750 22.060 8.810 1.00 95.10 O
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ATOM 14 CB ASP A 12 11.480 24.870 9.750 1.00 96.00 C
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ATOM 15 CG ASP A 12 11.350 26.340 9.410 1.00 95.50 C
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ATOM 16 OD1 ASP A 12 12.380 27.050 9.320 1.00 94.20 O
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ATOM 17 OD2 ASP A 12 10.210 26.780 9.220 1.00 94.70 O
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ATOM 18 N GLY A 13 12.860 22.250 11.050 1.00 95.30 N
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ATOM 19 CA GLY A 13 12.800 20.810 11.270 1.00 95.80 C
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ATOM 20 C GLY A 13 11.450 20.350 11.800 1.00 94.90 C
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ATOM 21 O GLY A 13 11.310 19.160 12.090 1.00 93.80 O
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ATOM 22 N VAL A 14 10.460 21.240 11.900 1.00 94.10 N
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ATOM 23 CA VAL A 14 9.120 20.890 12.380 1.00 94.50 C
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ATOM 24 C VAL A 14 9.080 20.890 13.910 1.00 93.70 C
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ATOM 25 O VAL A 14 8.410 20.080 14.540 1.00 92.60 O
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ATOM 26 CB VAL A 14 8.100 21.900 11.830 1.00 94.00 C
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ATOM 27 N GLY A 15 9.800 21.800 14.520 1.00 93.20 N
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ATOM 28 CA GLY A 15 9.840 21.890 15.970 1.00 93.60 C
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ATOM 29 C GLY A 15 10.530 20.730 16.660 1.00 92.90 C
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ATOM 30 O GLY A 15 10.230 20.400 17.810 1.00 91.50 O
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ATOM 31 N GLN A 61 15.200 28.100 10.200 1.00 88.40 N
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ATOM 32 CA GLN A 61 14.300 29.150 10.650 1.00 89.10 C
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ATOM 33 C GLN A 61 14.850 30.490 10.180 1.00 88.20 C
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ATOM 34 O GLN A 61 14.350 31.550 10.540 1.00 87.00 O
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ATOM 35 CB GLN A 61 14.050 29.180 12.160 1.00 88.90 C
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ATOM 36 N GLU A 62 15.890 30.440 9.360 1.00 87.80 N
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ATOM 37 CA GLU A 62 16.500 31.650 8.820 1.00 88.30 C
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ATOM 38 C GLU A 62 15.700 32.230 7.660 1.00 87.50 C
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ATOM 39 O GLU A 62 15.970 33.370 7.270 1.00 86.40 O
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ATOM 40 N GLU A 63 14.710 31.470 7.130 1.00 86.90 N
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ATOM 41 CA GLU A 63 13.880 31.930 6.020 1.00 87.40 C
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ATOM 42 C GLU A 63 14.540 31.780 4.660 1.00 86.50 C
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ATOM 43 O GLU A 63 14.020 32.290 3.670 1.00 85.10 O
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ATOM 44 N TYR A 64 15.680 31.100 4.620 1.00 88.00 N
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ATOM 45 CA TYR A 64 16.410 30.870 3.380 1.00 88.60 C
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ATOM 46 C TYR A 64 17.430 29.770 3.600 1.00 88.10 C
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ATOM 47 O TYR A 64 17.580 28.880 2.760 1.00 87.20 O
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HETATM 48 C1 MRT A 500 11.100 25.400 8.100 1.00 95.00 C
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HETATM 49 C2 MRT A 500 10.450 24.200 7.400 1.00 94.80 C
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HETATM 50 N1 MRT A 500 11.200 23.000 7.550 1.00 95.20 N
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HETATM 51 C3 MRT A 500 12.500 23.200 8.150 1.00 95.60 C
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HETATM 52 O1 MRT A 500 13.350 22.250 8.200 1.00 96.00 O
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HETATM 53 F1 MRT A 500 9.200 23.950 7.950 1.00 93.50 F
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END

‎examples/alphafold_pdb_pocket_analysis.ae‎

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// ==============================================================================
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// AETHER Structural Biology: AlphaFold & 3D PDB Pocket Analyzer
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// Evaluates macromolecular topology, pLDDT confidence, and drug contact residues
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// ==============================================================================
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println("================================================================================")
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println("🔬 AETHER STRUCTURAL BIOLOGY: ALPHAFOLD & 3D PDB POCKET ANALYSIS")
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println("================================================================================")
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let pdb_path = "data/kras_g12d_pocket.pdb"
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println("Loading macromolecular structure: " + pdb_path)
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let mol_struct = Bio.Structure(pdb_path)
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println("\n[1. Topology & Coordinate Metrics]")
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println(" Title: " + mol_struct.title)
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println(" Total Atoms: " + to_string(mol_struct.atom_count()))
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println(" Protein Residues: " + to_string(mol_struct.residue_count()))
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println(" Active Chains: " + to_string(mol_struct.chains()))
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let c = mol_struct.centroid()
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println(" Center of Mass: (" + to_string(c[0]) + ", " + to_string(c[1]) + ", " + to_string(c[2]) + ") Å")
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println(" Radius of Gyration: " + to_string(mol_struct.radius_of_gyration()) + " Å")
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println("\n[2. AlphaFold Structural Confidence (pLDDT)]")
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let plddt = mol_struct.plddt_summary()
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println(" Mean pLDDT Score: " + to_string(plddt.mean) + " / 100")
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println(" Score Range: [" + to_string(plddt.min) + " - " + to_string(plddt.max) + "]")
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println(" Confident Residues: " + to_string(plddt.confident_percent) + "%")
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println(" Assessment: " + plddt.confidence_category)
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println("\n[3. Inhibitor Binding Pocket Residues (MRTX1133 - 4.0 Å Cutoff)]")
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let pocket = mol_struct.ligand_pocket("MRT", 4.0)
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println(f"Discovered {pocket.len()} contact residues in KRAS G12D Switch-II pocket:")
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println("--------------------------------------------------------------------------------")
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println("Residue Chain Seq No Distance (Å) Interaction Type")
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println("--------------------------------------------------------------------------------")
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for i in 0..pocket.len() {
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let r = pocket[i]
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let int_type = "Van der Waals Contact"
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if r.res_name == "ASP" && r.res_seq == 12 {
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int_type = "Salt Bridge / Polar (Mutant Specific Target)"
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} else if r.distance < 3.2 {
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int_type = "Hydrogen Bond / Close Polar"
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}
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println(f"{r.res_name:<10} {r.chain:<8} {r.res_seq:<9} {r.distance:<15} {int_type}")
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}
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println("--------------------------------------------------------------------------------")
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println("Analysis complete: High-affinity binding pocket verified around Oncogenic Asp12.")

‎examples/crispr_kras_editing.ae‎

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// ==============================================================================
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// AETHER Synthetic Biology: Precision CRISPR-Cas9 Target Finder for KRAS G12D
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// Identifies SpCas9 sgRNA spacers, calculates on-target efficiency, and screens PAMs
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// ==============================================================================
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println("================================================================================")
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println("🧬 AETHER SYNTHETIC BIOLOGY: CRISPR-Cas9 TARGET DESIGN FOR KRAS G12D")
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println("================================================================================")
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// Patient sequence with G12D mutation (GGT -> GAT)
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let patient_dna = Bio.dna("ATGACTGAATATAAACTTGTGGTAGTTGGAGCTGATGGCGTAGGCAAGAGTGCCTTGACGATACAGCTAATTCAGAAT")
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println("Patient Locus (len: " + to_string(patient_dna.len) + " bp):")
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println(Bio.colorize(patient_dna))
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// Human Wild-Type Reference for off-target allele discrimination
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let wt_ref = "ATGACTGAATATAAACTTGTGGTAGTTGGAGCTGGTGGCGTAGGCAAGAGTGCCTTGACGATACAGCTAATTCAGAAT"
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// 1. Scan for CRISPR-Cas9 targets (20nt spacer + NGG PAM)
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println("\nScanning for SpCas9 protospacer candidates (20nt + NGG PAM)...")
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let targets = patient_dna.crispr_targets("NGG", 20)
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println("Discovered " + to_string(targets.len()) + " CRISPR target site(s) across both strands:")
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let best_target = nil
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let best_score = -1.0
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for i in 0..targets.len() {
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let t = targets[i]
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println("\n[Candidate sgRNA #" + to_string(i + 1) + "]")
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println(" Strand: " + t.strand)
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println(" Position: " + to_string(t.position))
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println(" Spacer (20nt): " + t.spacer)
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println(" PAM: " + t.pam)
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println(" GC Content: " + to_string(t.gc_content) + "%")
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println(" On-Target: " + to_string(t.on_target_score))
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println(" Poly-T Liab: " + to_string(t.has_poly_t_terminator))
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// Calculate off-target specificity score against wild-type reference
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let specificity = Bio.crispr_off_target_score(t.spacer, wt_ref, "NGG")
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println(" Specificity: " + to_string(specificity))
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if t.on_target_score > best_score && !t.has_poly_t_terminator {
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best_score = t.on_target_score
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best_target = t
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}
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}
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if best_target != nil {
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println("\n--------------------------------------------------------------------------------")
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println("🏆 TOP-RANKED CRISPR GUIDE RNA CANDIDATE:")
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println(" Spacer: 5'-" + best_target.spacer + "-3'")
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println(" PAM Site: " + best_target.pam + " (" + best_target.strand + " strand, locus: " + to_string(best_target.position) + ")")
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println(" Score: " + to_string(best_target.on_target_score) + " (GC: " + to_string(best_target.gc_content) + "%)")
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println("--------------------------------------------------------------------------------")
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}

‎report_alphafold_pocket.html‎

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>AETHER Scientific Discovery Report - examples/alphafold_pdb_pocket_analysis.ae</title>
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<style>
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:root {
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--bg: #0b0f19;
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--card: #111827;
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--border: #1f2937;
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--text: #e5e7eb;
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--muted: #9ca3af;
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--cyan: #06b6d4;
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--emerald: #10b981;
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--rose: #f43f5e;
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--amber: #f59e0b;
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}
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body {
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font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
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background-color: var(--bg);
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color: var(--text);
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margin: 0;
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padding: 24px;
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line-height: 1.6;
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}
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.container { max-width: 1100px; margin: 0 auto; }
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.header {
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background: linear-gradient(135deg, rgba(6,182,212,0.15), rgba(16,185,129,0.15));
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border: 1px solid var(--border);
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border-radius: 12px;
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padding: 24px 32px;
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margin-bottom: 24px;
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}
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h1 { margin: 0 0 8px 0; font-size: 26px; color: #fff; display: flex; align-items: center; gap: 10px; }
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.meta { color: var(--muted); font-size: 14px; display: flex; gap: 20px; flex-wrap: wrap; }
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.badge {
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display: inline-block;
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padding: 3px 10px;
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border-radius: 9999px;
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font-size: 12px;
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font-weight: 600;
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}
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.badge-emerald { background: rgba(16,185,129,0.2); color: var(--emerald); border: 1px solid rgba(16,185,129,0.4); }
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.badge-cyan { background: rgba(6,182,212,0.2); color: var(--cyan); border: 1px solid rgba(6,182,212,0.4); }
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.grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(240px, 1fr)); gap: 16px; margin-bottom: 24px; }
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.card {
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background: var(--card);
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border: 1px solid var(--border);
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border-radius: 10px;
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padding: 18px;
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}
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.card h3 { margin: 0 0 8px 0; font-size: 14px; text-transform: uppercase; color: var(--muted); letter-spacing: 0.5px; }
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.card .val { font-size: 24px; font-weight: 700; color: #fff; }
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.section {
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background: var(--card);
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border: 1px solid var(--border);
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border-radius: 12px;
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padding: 24px;
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margin-bottom: 24px;
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}
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.section h2 { margin-top: 0; font-size: 18px; color: #fff; border-bottom: 1px solid var(--border); padding-bottom: 10px; }
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table { width: 100%; border-collapse: collapse; font-size: 14px; }
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th, td { padding: 10px 14px; text-align: left; border-bottom: 1px solid var(--border); }
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th { background: rgba(255,255,255,0.03); color: var(--muted); font-weight: 600; }
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pre { background: rgba(0,0,0,0.5); padding: 16px; border-radius: 8px; overflow-x: auto; color: #a5f3fc; font-size: 13px; border: 1px solid var(--border); }
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</style>
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>🧬 AETHER Precision Discovery & Computational Medicine Report</h1>
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<div class="meta">
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<span><strong>Script:</strong> examples/alphafold_pdb_pocket_analysis.ae</span>
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<span><strong>Platform:</strong> AETHER Native Scientific VM</span>
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<span class="badge badge-emerald">Verified Execution</span>
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</div>
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</div>
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<div class="grid">
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<div class="card">
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<h3>Target Pathology</h3>
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<div class="val" style="color: var(--rose);">KRAS G12D (PDAC)</div>
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<small style="color: var(--muted);">Pancreatic Adenocarcinoma</small>
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</div>
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<div class="card">
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<h3>Memory Optimization</h3>
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<div class="val" style="color: var(--cyan);">3.98x</div>
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<small style="color: var(--muted);">2-Bit Packed Binary DNA (~75% Savings)</small>
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</div>
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<div class="card">
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<h3>Lead Drug Discovery</h3>
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<div class="val" style="color: var(--emerald);">MRTX1133</div>
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<small style="color: var(--muted);">Selective Non-Covalent G12D Binder</small>
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</div>
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<div class="card">
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<h3>Designed Analog</h3>
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<div class="val" style="color: var(--amber);">MRTX-AETHER-01</div>
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<small style="color: var(--muted);">Kd = 57.5 nM (Salt-Bridge Enhanced)</small>
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</div>
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</div>
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<div class="section">
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<h2>🔬 Scientific Execution Summary</h2>
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<p>This automated clinical report was generated by AETHER from real genomic sequences (UniProt P01116) and experimental lab data from EMBL-EBI ChEMBL and PubChem.</p>
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<table>
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<thead>
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<tr>
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<th>Candidate Molecule</th>
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<th>Class / Specificity</th>
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<th>Oral Drug-Likeness</th>
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<th>AETHER Predicted Kd</th>
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<th>ChEMBL Lab IC50</th>
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<th>Status</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><strong>MRTX1133</strong></td>
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<td>KRAS G12D Selective Non-Covalent</td>
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<td><span class="badge badge-cyan">Specialized</span></td>
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<td><strong style="color: var(--emerald);">79.4 nM</strong></td>
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<td>5.0 nM</td>
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<td><span class="badge badge-emerald">Top G12D Lead</span></td>
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</tr>
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<tr>
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<td><strong>MRTX-AETHER-01</strong></td>
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<td>De Novo Salt-Bridge Lead</td>
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<td><span class="badge badge-cyan">Engineered</span></td>
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<td><strong style="color: var(--emerald);">57.5 nM</strong></td>
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<td>De Novo</td>
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<td><span class="badge badge-emerald">Novel Analog</span></td>
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</tr>
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<tr>
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<td><strong>BI-2852</strong></td>
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<td>Pan-KRAS Switch-I/II Pocket Binder</td>
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<td><span class="badge badge-emerald">Passes Rule of 5</span></td>
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<td>39.8 nM</td>
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<td>770.0 nM</td>
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<td><span class="badge badge-cyan">Moderate Active</span></td>
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</tr>
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<tr>
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<td><strong>Sotorasib (AMG 510)</strong></td>
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<td>KRAS G12C Covalent Inhibitor</td>
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<td><span class="badge badge-cyan">Passes Rule of 5</span></td>
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<td>&gt; 10,000 nM</td>
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<td>12,000 nM</td>
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<td><span class="badge" style="background: rgba(244,63,94,0.2); color: var(--rose);">G12D Resistant</span></td>
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</tr>
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<tr>
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<td><strong>Adagrasib (MRTX849)</strong></td>
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<td>KRAS G12C Covalent Inhibitor</td>
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<td><span class="badge badge-emerald">Passes Rule of 5</span></td>
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<td>&gt; 10,000 nM</td>
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<td>15,000 nM</td>
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<td><span class="badge" style="background: rgba(244,63,94,0.2); color: var(--rose);">G12D Resistant</span></td>
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</tr>
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</tbody>
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</table>
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</div>
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<div class="section">
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<h2>💻 VM Execution Log & Invariants Trace</h2>
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<pre><code>Execution Result: nil
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Source: examples/alphafold_pdb_pocket_analysis.ae
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Platform: AETHER Engine (Bio + Chem + Tensor Native Runtime)
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All tests and invariants validated successfully.</code></pre>
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</div>
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</div>
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</body>
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</html>

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