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Protein Folding Energy Landscape Inversion L1-412

Computational BiologyStructural biologyδ=50 · frontierL_DAG = 6.5📋 Stub — not mineable
📋

Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

To claim it as a Bounty #7 contribution: open a PR adding (1) a reference solver, (2) ≥1 dataset pinned to IPFS, (3) updates to the L3 manifest with dataset CIDs. After verifier-agent triple-review, the founders' 3-of-5 multisig signs PWMRegistry.register() and the Principle becomes mineable.

Forward model E

Protein Folding Energy Landscape Inversion: Protein structure determination: recover 3D atomic coordinates from cryo-EM density map or experimental NMR restraints. The forward operator produces the measurement through a 3-node primitive DAG (M.energy.force_field…); recovery is posed as a nonlinear_inverse problem. Difficulty tier delta=50 with effective condition number kappa_eff~10000000.0; conformational_heterogeneity, solvent_contribution_neglect set the accuracy floor at the Omega boundary. See the forward_model field for the closed-form equation.

L-DAG

N.pointwise -> S.md.molecular_dynamics -> O.rmsd.structure_comparison
N.pointwiseS.md.molecular_dynamicsO.rmsd.structure_comparison

Well-posedness W

Existence:
true
Uniqueness:
true
Stability:
conditional
κ:
10000000000

Existence of the recovered 3D_protein_structure is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 10000000.0); conformational_heterogeneity dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Shot poisson sets the irreducible data-fidelity floor.

Solvability C

Solver class:
classical [PHENIX_real_space_refinement or HADDOCK or AlphaFold2_structure_prediction]
Convergence rate q:
2
Complexity:
O(N_atoms * N_iterations) for MD refinement; O(N_atoms ** 2) for energy evaluation

Specs (0)

No L2 specs registered yet for this principle.