基于三维结构图的荧光蛋白量子产率预测新方法
Edge-specific signal propagation on mature chromophore-region 3D mechanism graphs for fluorescent protein quantum-yield prediction
- 构建染色体中心机制图，分区域传播局部信号
- 在531蛋白数据集上达0.772相关系数，优于现有模型
- 可解释性强，适合荧光蛋白设计与筛选研究
荧光蛋白量子产率由成熟发色团及其三维微环境决定，而非仅依赖序列相似性。蛋白质语言模型和发射波段平均值虽能捕捉全局趋势，却无法建模局部物理信号对特定发色团区域的作用。本文提出一种以发色团为中心的机制图算法用于量子产率预测。将每个PDB结构转换为类型化的3D残基图，注册至成熟-CRO状态，划分为苯酚盐、桥接和咪唑啉酮三个区域，并通过通道-信号-区域传播进行变换。表征包含121个富集特征；去除身份捷径后，使用52个非身份特征进行波段特异性ExtraTrees回归。每个特征编码接触通道、初始信号与目标CRO区域，实现内在可解释性。在531蛋白基准测试中，该方法在模型基线中表现最佳（随机交叉验证R = 0.772 ± 0.008，MAE = 0.131 ± 0.002），超过波段均值（R = 0.632）、ESM-C（R = 0.734）和SaProt（R = 0.731），并在明亮筛选中排名第一（Bright P@5 = 0.704）。在远源控制下（<50%相似性），优势最显著（R = 0.697 vs. 0.633, 0.575, 0.408），整体亮/暗蛋白Top-K筛选能力最强。稳定选中的特征恢复了波段特异性机制：GFP类蛋白中芳香堆积与钳位不对称性，红色蛋白中电荷/钳位平衡，远红蛋白中柔韧性风险与大体积接触特征。源代码、特征表与评估脚本可通过第一作者获取。
原文摘要 · Abstract (English)
Fluorescent protein quantum yield (QY) is governed by the mature chromophore and its three-dimensional microenvironment rather than sequence identity alone. Protein language models and emission-band averages capture global trends, but do not model how local physical signals act on specific chromophore regions. 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: [email protected]
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