Drug-Target Binding Affinity Classification (PWDR) L1-521

Computational ChemistryQuantum-chemistry binding-energy estimation with affinity-class categorical readoutδ=5 · advancedL_DAG = 7📋 Stub — not mineable

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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.

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Forward model E

S t a g e 1 (L 1 - 294 + M D / F E P) : d r ug + t a r g e t \to e q u i l ib r i u m e n se mb l e \to D e l t a - G_{b} in d in g v ia t h er m o d y nami ccy c l e . S t a g e 2 : a f f ini t y_{c} l a ss = s t e p (D e l t a - G_{b} in d in g a t [- 11, - 9, - 7, - 5] k c a l / m o l) .

Drug-Target Binding Affinity Classification (PWDR): wraps L1-294 DFT analytical core with established medicinal-chemistry affinity-class thresholds. Stage 1 (analytical, from L1-294): compute drug-target binding free energy Delta-G_binding via FEP / TI / MM-PBSA / DFT-corrected docking using DFT-derived atomic charges and force-field parameters. Stage 2 (deterministic threshold): apply standard medicinal-chemistry thresholds at Delta-G = {-5, -7, -9, -11} kcal/mol to assign categorical label. Difficulty tier delta = 5. Mismatch parameters: force_field_uncertainty, sampling_convergence_error, water_model_uncertainty, protein_flexibility_truncation, drug_protonation_state, conformational_search_incompleteness.

L-DAG

L.molecular_topology -> L.dft_charge_calculation -> L.force_field_parameterization -> L.molecular_dynamics -> L.fep_thermodynamic_cycle -> L.binding_free_energy -> L.affinity_threshold_classifier -> int.ensemble

L.molecular_topologyL.dft_charge_calculationL.force_field_parameterizationL.molecular_dynamicsL.fep_thermodynamic_cycleL.binding_free_energyL.affinity_threshold_classifierint.ensemble

Well-posedness W

Existence:: true
Uniqueness:: conditional
Stability:: conditional
κ:: 100

Existence guaranteed within Omega bounds. Uniqueness conditional on adequate sampling (typically ≥100 ns of FEP for druglike ligands) and convergent thermodynamic cycle. Stability dominated by force_field_uncertainty (~1-2 kcal/mol systematic error) and sampling_convergence_error. Joint Hadamard well-posedness for the coupled DFT + MD + FEP + threshold forward established by Wang 2015 (FEP+ benchmark), Mey 2020 (best practices for FEP), Cournia 2020 (relative binding free energy review), Lipinski 1997 (Rule of 5), Veber 2002 (drug-likeness rules), Hopkins 2004 (ligand efficiency).

Solvability C

Solver class:: linear-operator + statistical sampling [FEP / TI / replica-exchange MD] + categorical-readout [affinity threshold] | machine-learned [deep neural force fields, Schrodinger FEP+] | linear-operator + deep neural [DeepBind, AtomNet]
Convergence rate q:: 0.5
Complexity:: O((N_atoms_drug + N_atoms_target)^2 * simulation_time_ns * N_lambda_windows) for FEP; expensive for large complexes

Specs (0)

No L2 specs registered yet for this principle.