Drug/discovery/structural biology

1

• Done. I ran the new ALDH + NAD + metabolite panel and the GSTM2 + GSH + 5-S-cysteinyl-DOPAC deep-damage extension,
then folded everything into one combined note at C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-
3398%20(1).vcf/gene_sequences/aldehyde_and_conjugation_branch_panel.md.

For the aldehyde side, all six jobs completed: ALDH1A1/ALDH2 + NAD + DOPAL/DOPAC/DOPEGAL. The main output is C:/Users/
User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-3398%20(1).vcf/gene_sequences/boltz2_aldh/results/
boltz2_aldh_branch_note.md with metrics in C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-
3398%20(1).vcf/gene_sequences/boltz2_aldh/results/boltz2_aldh_branch_metrics.tsv. DOPAL ranked strongest in both
ALDH1A1 and ALDH2, DOPEGAL was next, and DOPAC was weakest. The important caveat is that all ALDH states had very
large complex_ipde values, so this is useful as branch triage, not a clean docking-style answer.

For the conjugation side, I reused the existing GSTM2 jobs, added GSTM2 + GSH + 5-S-cysteinyl-DOPAC, and reran the
structure-level analysis. The updated note is C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-
3398%20(1).vcf/gene_sequences/boltz2_gstm2/results/boltz2_gstm2_gsh_structure_note.md, with tables in C:/Users/
User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-3398%20(1).vcf/gene_sequences/boltz2_gstm2/results/
boltz2_gstm2_gsh_structure_metrics.tsv and C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-
3398%20(1).vcf/gene_sequences/boltz2_gstm2/results/boltz2_gstm2_gsh_structure_samples.tsv. The ranking is now:

  1. GSTM2 + GSH + 5-S-cysteinyl-dopamine
  2. GSTM2 + GSH + aminochrome
  3. GSTM2 + GSH + 5-S-cysteinyl-DOPAC
  4. GSTM2 + GSH + dopamine o-quinone

New scripts are C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-3398%20(1).vcf/
run_boltz_aldh_branch_jobs.py, C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-3398%20(1).vcf/
analyze_boltz_aldh_branch.py, and C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-3398%20(1).vcf/
run_boltz_gstm2_gsh_deeper_damage_jobs.py. I did not run AKR1C yet; that stayed out of scope for this pass.

› so how well does GSTM2 rescue these dopamine metabolites

• GSTM2 looks plausible for the conjugation and downstream-damage branch, but I would not call it a proven “rescue” yet.

What the current Boltz panel says:

  • Best GSTM2-side state is GSTM2 + GSH + 5-S-cysteinyl-dopamine: binding_confidence 0.616673, complex_ipde 0.731850,
    with coherent GSH geometry and a moderately recurring probe family. That is the strongest structural support for GSTM2
    participating after quinone trapping, not before it.
  • GSTM2 + GSH + aminochrome is decent by score (0.603468) but structurally looser. The probe RMSD is large (9.327 Å),
    so it looks less like a clean recurring handled state.
  • GSTM2 + GSH + 5-S-cysteinyl-DOPAC is actually quite clean geometrically: binding_confidence 0.498895, complex_ipde
    0.601556, probe RMSD 0.614 Å. It looks like a believable deeper-damage/conjugate branch state, but weaker overall than
    5-S-cysteinyl-dopamine.
  • GSTM2 + GSH + dopamine o-quinone is the weakest practical “rescue” read. The probe is very consistent, but it sits
    farther from GSH, which makes it look more like association than active conjugation coupling.

So the honest read is:

  • GSTM2 looks good for handling downstream conjugated dopamine-oxidation damage.
  • It looks less convincing as the primary answer for upstream free dopamine quinones.
  • If you want “rescue of dopamine metabolites,” the strongest GSTM2 case is 5-S-cysteinyl-dopamine, then 5-S-
    cysteinyl-DOPAC, then aminochrome, then raw dopamine o-quinone.

The relevant outputs are C:/Users/User.codex/alex_chen_nucleus_dna_download_vcf_NU-PGIK-3398%20(1).vcf/gene_sequences/
boltz2_gstm2/results/boltz2_gstm2_gsh_structure_note.md and the combined summary C:/Users/User.codex/
alex_chen_nucleus_dna_download_vcf_NU-PGIK-3398%20(1).vcf/gene_sequences/aldehyde_and_conjugation_branch_panel.md.

If you want the shortest conclusion: GSTM2 probably helps mop up the conjugated damage branch, but NQO1 and ALDH still
look more relevant for the earlier upstream toxic intermediates.

2


Ash Jogalekar


@curiouswavefn

·

7h

While impressive in its own right, it’s worth remembering that predicting protein-drug interactions is like 0.01% of the drug discovery and development pipeline and the spare change part of it. Saying that that’s revolutionizing the process is like convincing someone, in Derek

Show more

Quote

Ian Miles Cheong

@ianmiles

·

Mar 31

Demis Hassabis: If you know the structure of a protein, the real question becomes—where will your drug bind, and what will it actually do? That’s where the next wave of AI comes in. Not just predicting structures, but modeling interactions, outcomes, and real biological impact.


Hang Zheng


@HangZheng855161

Exactly. Structure prediction is solved enough for most practical purposes, but the bottleneck was never the structure — it’s the biology downstream. PK, toxicity, formulation, clinical translation. AI is making real contributions in pockets (FEP, generative chemistry), but the 0.01% framing is a healthy corrective.

4:20 AM · Apr 1, 2026

·


584
Views

3

Atropisomers matter for drugs when the molecule’s hindered rotation is slow enough that the “left-twisted” and “right-twisted” forms behave like different drugs, not just different poses in the same wriggly chemical noodle. :test_tube:

The useful rule:

Atropisomers matter when their interconversion time is comparable to storage, dosing, assay, metabolism, or receptor-binding timescales.

The three practical regimes

Type Interconversion Drug-development consequence
Fast rotamers / Class 1 seconds or faster Usually just conformers. They can affect binding pose, but you usually do not dose separate atropisomers.
Intermediate / Class 2 minutes to months/years The annoying danger zone. Isomer ratios may change during formulation, storage, assays, or inside the body. Tiny spinning bond, giant paperwork avalanche.
Stable atropisomers / Class 3 years-scale Treat like separate stereoisomers/enantiomers. They may have different potency, toxicity, PK, clearance, off-targets, etc.

LaPlante-style classifications commonly use racemization half-life at 37 °C: Class 1 < 60 s, Class 2 between 60 s and 4.5 years, and Class 3 > 4.5 years. (American Chemical Society Publications)

When they matter most

1. One atropisomer binds much better than the other

Proteins are chiral, so they can strongly prefer one axial twist. This is the most obvious case: one isomer is the eutomer and the other is the distomer, like ordinary enantiomers but caused by bond rotation instead of a point stereocenter. Reviews note that atropisomeric compounds can show drastically different biological activities. (PubMed)

Sotorasib is the poster child. It is a KRAS G12C inhibitor developed as a single-atropisomer drug; the atropisomeric axis produced configurationally stable forms with about a 10-fold potency difference, so Amgen had to control the stereochemistry seriously rather than shrugging like a sophomore with a melting-point tube. (PMC)

2. The “wrong” atropisomer has different toxicity or off-targets

Even if both forms hit the intended target, they may differ at other receptors, ion channels, CYPs, transporters, hERG, etc. FDA stereoisomer guidance is not atropisomer-specific, but the logic is the same: stereoisomers are often distinguished by biological systems and may differ in PK, metabolism, and activity. (U.S. Food and Drug Administration)

3. The isomers interconvert during dosing

This is the Class 2 horror show. Imagine you purify one atropisomer, formulate it, ship it, store it, dose it, and then it slowly becomes a mixture. Spectacularly irritating. In that case, you need to know:

  • racemization half-life at body temperature

  • pH dependence

  • heat/light stability

  • whether enzymes or binding pockets accelerate interconversion

  • whether each isomer has different clearance or tissue distribution

A Class 2 atropisomer may be too slow to ignore but too fast to market cleanly as a single stable species. Chemistry’s way of saying “good luck, nerd.”

4. The molecule has a high-risk scaffold

Atropisomerism is most likely to matter in drugs with:

  • biaryls

  • heterobiaryls

  • benzamides

  • anilides

  • diarylamines

  • sulfonamides

  • big ortho-substituted aromatic systems

  • macrocycles / constrained natural products

Modern reviews specifically flag heterobiaryls, benzamides, diarylamines, and anilides as pharmaceutically relevant atropisomeric scaffolds. (American Chemical Society Publications)

5. The drug is meant to be ultra-selective

Atropisomerism becomes more important when tiny changes in 3D pose decide selectivity: kinase inhibitors, KRAS inhibitors, GPCR ligands, protein-protein interaction inhibitors, PROTACs, macrocycles, and beyond-rule-of-five compounds. For these, axial twist can decide whether the molecule lines up with a deep pocket, avoids a steric clash, or reaches a covalent warhead position.

6. Manufacturing and quality control depend on it

If a stable atropisomer exists, regulators and process chemists need to know whether the active ingredient is:

  • a single atropisomer

  • a racemic atropisomer mixture

  • an equilibrating mixture

  • contaminated with an inactive/toxic atropisomer

  • prone to isomerization during synthesis or storage

Lesinurad is a useful example: it was marketed as a 1:1 racemic mixture of atropisomers, and its configurational stability was recognized postlaunch. (ResearchGate)

When they don’t matter much

Atropisomers usually do not matter clinically when:

  • rotation is very fast at 37 °C

  • the receptor only “sees” one conformation and the rest equilibrates quickly

  • both atropisomers have similar activity/toxicity

  • the rotational barrier is too low for isolation

  • the “atropisomer” claim is just someone overdecorating ordinary conformational analysis with a fancy word, because chemistry apparently needed more Victorian furniture terms

The shortest useful answer

Atropisomers matter for drugs when bond rotation is slow enough to create distinct, persistent 3D species, and those species differ in target binding, selectivity, metabolism, toxicity, exposure, storage stability, or manufacturability.

The worst/best cases are stable Class 3 atropisomers like sotorasib, where the axial stereochemistry is part of the drug identity. The most annoying cases are Class 2 atropisomers, where the molecule slowly changes its stereochemical identity on real biological or manufacturing timescales.