Infinite Synthesis: Amortized O(1) Protein Folding via 6DoF Manifold Projection

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Authors: Brendan Lynch
Cited by: 0

Abstract

Conventional protein folding methods rely on computationally intensive molecular dynamics or iterative optimization heuristics. This work introduces the Chimera framework, which employs a fast 6-degree-of-freedom (6DoF) geometric resolver to map the manifold of physically allowed backbone rotations. A specialized Transformer is trained on high-fidelity “Geometric Truth” extracted from 37 high-resolution PDB structures. The resulting model solves protein structures including unknown segments (“Z-gaps”) in amortized constant time (≈2 ms per protein on consumer Apple Silicon hardware) with sub-ångström backbone precision (motive MSE ≈ 0.0197 on benchmark structures). We demonstrate high throughput (∼43 million proteins/day), effective de-novo bridge sequence design via geometric smoothness and clash scoring, and strong generalization on synthetic chimeric sequences. The approach reframes folding as deterministic manifold projection rather than search, offering a scalable path toward real-time structural biology and therapeutic protein design. Source code and the trained UFT-Global-Brain-V2 weights are provided to ensure full reproducibility of the $O(1)$ benchmark.

Fields of Study & Subjects

Protein Structure and Dynamics Machine Learning in Bioinformatics RNA and protein synthesis mechanisms

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 February 2026