Elastic Network Model (ANM) normal-mode analysis and iMODFIT-style normal-mode-biased flexible fitting for protein flexibility and cryo-EM-style morphing.
Elastic Network Model (ANM) normal-mode analysis and iMODFIT-style normal-mode-biased flexible fitting for protein flexibility and cryo-EM-style morphing. Treats a protein as one bead per residue (Ca) joined by identical springs within a cutoff, builds the 3N x 3N Anisotropic Network Model Hessian (Atilgan 2001 / Tirion 1996), diagonalises it (cyclic Jacobi - the same modal eigen-primitive as the seismic plugin), and reports the low-frequency collective modes (hinge / domain motions), the per-residue mobility / theoretical B-factor profile, and each mode collectivity. Flexible fitting then morphs an initial model toward a target the way iMODFIT does (Lopez-Blanco & Chacon, J. Struct. Biol. 2013): a Monte-Carlo search in normal-mode space that picks low-frequency modes (biased toward lower-frequency, higher-amplitude ones), deforms, and accepts on an improved score - staying in the smooth low-frequency subspace so it avoids the heavy distortions of unrestrained fitting. A built-in synthetic two-lobe structure (with a known hinge motion) validates the method: the fit recovers a deformation of known size. Honest scope: Cartesian ANM (not iMod internal-coordinate NMA), fitting to a target conformation / simulated density (not a real cryo-EM MRC map), larger proteins via a deflated Lanczos low-mode solver (validated to match Jacobi), sub-second on CPU at N~500 so no GPU is needed. Deterministic, in-browser, no AI / network / key; GeoNum trust on the eigensolve conditioning.
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