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We present a chromophore-centred mechanism graph algorithm for QY prediction. Each PDB structure is converted into a typed 3D residue graph, registered to a mature-CRO state, partitioned into phenolate, bridge and imidazolinone regions, and transformed by channel-signal-region propagation. The representation contains 121 enrichment features; after removing identity shortcuts, 52 non-identity features are used for band-specific ExtraTrees regression. Because each feature encodes a contact channel, seed signal and target CRO region, interpretation is intrinsic rather than post hoc. On a 531-protein benchmark, the method achieved the best random-CV performance among model-based baselines (R = 0.772 +/- 0.008, MAE = 0.131 +/- 0.002), exceeding Band mean (R = 0.632), ESM-C (R = 0.734) and SaProt (R = 0.731), and ranked first in bright screening (Bright P@5 = 0.704). Under homology control, the advantage was clearest in the remote bucket (<50% similarity; R = 0.697 versus 0.633, 0.575 and 0.408), with the strongest overall bright/dark Top-K screening. Stable selected features recovered band-specific mechanisms: aromatic packing and clamp asymmetry in GFP-like proteins, charge/clamp balance in Red proteins, and flexibility-risk/bulky-contact features in Far-red proteins.
Source code, feature tables and evaluation scripts are available from the first author upon request. Contact: yuchenak05@gmail.com
| Comments: | Includes appendix; source code, processed feature tables and evaluation scripts are available from the first author upon reasonable request |
| Subjects: | Machine Learning (cs.LG) |
| Cite as: | arXiv:2605.06644 [cs.LG] |
| (or arXiv:2605.06644v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2605.06644 arXiv-issued DOI via DataCite (pending registration) |
From: Yuchen Xiong [view email]
[v1]
Thu, 7 May 2026 17:51:41 UTC (1,499 KB)
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