Anesthesia Pipeline — Network-State Validation

Thesis

General anesthesia is a network-level state transition driven by coordinated partial perturbation at conserved targets (SNARE release, Complex I, K2P channels, nAChR, NCA leak, GABA-A potentiation), not a single-target binding event. Mutants in any one target give partial phenotypes; non-immobilizers like hexafluoroethane fail despite engaging some of the same targets. Specificity emerges from the integrated network response, not the molecular fit.

The validator operationalises this directly. Per-anesthetic Hill-curve perturbation profiles are built from primary literature EC50/IC50 measurements, applied to the Cook 2019 C. elegans hermaphrodite connectome via a 300-neuron Brian2 LIF brain, and read out as quiescent-state enrichment in the locomotion command-interneuron set.

Interactive: V3 ensemble explorer

Five tabs over the V3 worm ensemble + V4 fly cross-species ensemble. Pick a volatile to see its Hill-shaped dose-response against the published worm EC50; toggle a mutant to see the Hill curve shift left (hypersensitive) or right (resistant); compare the three Eger compounds side-by-side to see why the conserved-substrate model distinguishes anesthetics from non-immobilizers; open the perturbation profile to see which mechanism classes each compound engages with primary literature anchors; or open the Cross-Species tab to compare the same architecture’s predictions on the C. elegans (Cook 2019, 300 neurons) and Drosophila larva (Winding 2023, 2,952 neurons) connectomes side-by-side.

Architecture

  literature-grounded perturbation table  ──▶   300-neuron Brian2 LIF brain   ──▶   network-state metrics
  (per-(anesthetic, target_class)               (Cook 2019 connectome,                   • quiescent fraction
   EC50, max effect, Hill n,                     Loer & Rand 2022 NT identity,            • command-interneuron mean rate
   primary-PMID-anchored)                        per-edge CeNGEN Glu sign overlay)        • population state autocorrelation

• Perturbation profiles for 9 compounds × 8 mechanism classes built from Mihic 1997, Patel & Honoré 1999, Forman 1996, Stewart 2000, Hanley 2002, Lu 2007, Belelli 1997, plus Eger 2001 for non-immobilizers. Each row carries a primary PMID; missing (anesthetic, class) cells are explicit DEFERRED (not imputed).
• Mutant baseline shifts (Complex I rate factor for gas-1, gas-2, nduf-6, ndus-8, nuo-1 per Kayser 2001; NCA leak factor for unc-79, unc-80 per Sedensky 1992; synaptic weight scaling for Gαo loss-of-function in goa-1, dgk-1 per Lackner 1999, Nurrish 1999).
• One free calibration parameter (α = 0.13), tuned only against halothane WT (Crowder 1996, EC50 = 340 µM aqueous). All downstream gates use the same locked α.
• Ensemble protocol: 60 s simulation × 5 seeds per (anesthetic, dose, genotype). 545 sims total; 8-core parallel; 23 min wall on RTX 4060 Ti host.

Validation gates

Calibration uses one anchor and one parameter. Held-out tests then run with no further tuning.

Mutant directional accuracy — Gate 3 detail

WBPhenotype anchors: WBPhenotype:0001611 (halothane hypersensitive), WBPhenotype:0001618 (halothane resistant). Citation paths preserved per gene. The two RESISTANT predictions land squarely in their published literature ranges; the seven HYPER predictions are all directionally correct with magnitudes slightly less extreme than published (within 1.5× of upper bound).

Eger non-immobilizer specificity — Gate 4 detail

The Eger 2001 panel was designed to falsify lipophilic-pocket-fit theories of anesthesia: hexafluoroethane and trans-1,2-dichloroethylene have appropriate lipid solubility for Meyer-Overton anesthetics but produce no immobilization in mammals. Cis-1,2-dichloroethylene, the stereoisomer, is an anesthetic. Single-pose docking pipelines cannot distinguish them. The network-state validator can:

Same architecture, same α, no compound-specific tuning. The non-immobilizers’ command-interneuron firing rates do drop monotonically with dose (any partial K2P engagement contributes), but neither crosses the immobilization threshold across four orders of magnitude (30 µM → 30 mM).

What this replaces

An earlier project iteration built a binding-occupancy → kinetic-shift → network → behavior chain driven by AutoDock Vina docking against AlphaFold structures of 30 C. elegans anesthetic targets. That pipeline failed three diagnostic tests:

• Vina ΔG was dominated by ligand chemistry: per-target regression of log(predicted Kd) on (clogP, MW) across 14 ligands gave median R² = 0.735 — the docking step contributed ~7 percentage points of pooled variance over chemistry alone.
• Predicted Kd was anti-correlated with worm-behavioral EC50 on the clean primary-anchor subset (Pearson r = -0.84, n=4, wrong sign).
• Anesthetic vs Eger non-immobilizer discrimination was 91% chemistry: regressing out (clogP, MW) collapsed Cohen’s d from -1.18 to -0.11 (Mann-Whitney p went from < 0.0001 to 0.50). Meyer-Overton beat the pipeline as a worm-potency predictor.

The diagnostic work also surfaced architectural failures downstream: a max()-aggregation in the perturbation manager collapsed 5 of 6 anesthetics to within 4 pA of each other at 1× EC50 despite EC50s spanning four orders of magnitude, and the Phase F gas-1 prediction was structurally invariant to the anesthetic-specific input (the block_factor term cancels analytically in the d_WT / d_g1 ratio).

The network-state validator above replaces that chain entirely: literature EC50s instead of Vina-derived occupancies, the full 300-neuron Cook connectome instead of a 50-neuron LIF demo, and direct network-state metrics instead of max()-aggregation followed by classifier-bank pattern matching. Calibration uses one anchor and one parameter; everything else is held-out.

Three-organism validation (V4 + V6) on a substrate-agnostic LIF integrator

The architecture transfers to Drosophila larva (Winding 2023 connectome, 2,952 neurons) and Mus musculus (generic LIF random graph, 3,000 neurons — no mammalian connectome required per V5 M2). Three independent organisms, three single-anchor calibrations.

What survived adversarial controls — V5 + V5+ findings

V5 M2 (connectome permutation) and V5+ (no-integration sign-only baseline + Meyer-Overton baseline) jointly narrow what’s actually load-bearing in the architecture:

The substrate is largely interchangeable. V5 M2: fly result transfers to fully randomized graphs (P1, P2, P3 all pass Gate 1 at frozen α). Mouse V6 uses a generic random graph by design. Worm V3 needs at minimum cell-type-aggregate connectivity (P3 passes; P1, P2 fail). The “cross-phylum” framing was over-claiming organism-specific structural recovery.

Gate 3 directional accuracy is largely sign-propagation. A no-integration sign-only baseline matches the validator on 32/35 mutants (91% — identical to the validator). Network dynamics are decorative for the direction of mutant predictions; the perturbation table’s sign convention does the work.

Cross-organism MAC similarity at ~340-350 µM is largely Meyer-Overton. A lipid:water-partition baseline calibrated on halothane predicts halothane MAC perfectly (by definition) and matches the validator at order-of-magnitude across phyla. The “striking conservation” claim collapses to “lipid biophysics conserves across cells” (Meyer-Overton 1899).

Where the architecture genuinely beats Meyer-Overton:

Honest single-line claim, post-controls

A literature-anchored conserved-target Hill perturbation table, integrated through a generic LIF substrate (no specific connectome required), recovers held-out volatile EC50s ~3× tighter than Meyer-Overton, predicts mutant magnitudes inside literature bands for several mutants in each organism, and correctly classifies Eger non-immobilizers across worm, fly, and mouse with one free parameter calibrated per organism.

The architecture is largely substrate-agnostic. The mechanism map is what does the work. Cross-organism MAC similarity is consistent with Meyer-Overton (lipid biophysics) and not strong evidence of conserved targets on its own. The architecture’s distinctive contribution is within-organism precision on held-out volatiles, mutant magnitude, and Eger discrimination — places where Meyer-Overton fails.

V6 mouse scope: LRR / immobilization phenotype only. Higher-order mammalian features (cortical EEG burst suppression, NREM-like slow oscillations, gamma suppression, consciousness disruption) are NOT in the architecture and not claimed.

Use the Cross-Species tab to compare worm + fly + mouse halothane / isoflurane curves side-by-side.

Adversarial controls (V5) — what survives, what doesn’t

Honest follow-on testing reveals where the V3/V4 result is genuinely structural and where it is over-determined:

Bootstrap 95% CIs (1000 resamples on 5-seed ensembles): predictions are precise but tight. The worm-isoflurane held-out test (predicted 291 µM, 95% CI [276, 310] µM) sits inside its CI containing the published 290 µM — the strongest of the four EC50 predictions. The other three EC50s sit just outside their 95% CIs (worm halothane CI [297, 334] vs published 340; fly halothane CI [343, 373] vs 340; fly iso CI [315, 328] vs 290). Fold-errors of 1.06–1.11× are real but not statistically consistent with published values to within seed noise.

Connectome permutation tests (Erdős-Rényi rewiring, configuration-model degree-preservation, cell-type block shuffle):

The “connectome-constrained” framing was over-claiming. The worm result requires at minimum cell-type-level structural connectivity (random rewiring breaks it; cell-type-block-preserving rewiring doesn’t). The fly result is NOT connectome-dependent — random graphs of comparable density also pass. The Eger specificity result is NOT a connectome claim in either organism — it’s a perturbation-table sparseness story.

The conserved-substrate hypothesis itself survives: the perturbation-table + network-integration architecture recovers behavioral phenotypes from molecular pharmacology in both organisms. What’s narrower than the original claim: the specific Cook 2019 / Winding 2023 wiring is NOT the load-bearing structural feature in either organism.

Status

• V3 worm ensemble shipped + V4 fly cross-species ensemble shipped. All four gates pass in both organisms.
• Repo: AnestheticSimulator/ (public). Built at $0 external spend on an RTX 4060 Ti.
• Open work: per-mutant Complex I factor refinement (currently nduf-6 / ndus-8 / nuo-1 share an estimate; per-gene primary-literature factors would differentiate them); FlyBase driver-line NT data integration to replace V1’s cell-type heuristic; full adult Drosophila (FlyWire ~140K neurons) substrate as a follow-on.