发表机构
University of Central Florida（中佛罗里达大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出ORBIT-FMIB诊断框架，通过Walsh分解和神经依赖估计探究ESM-2是否保留高阶上位性信息，重复实验表明证据不足，方向性问题仍待解决。
AI 中文摘要
蛋白质基础模型支持突变效应和结构预测，但仅凭预测性能并不能揭示模型深度中哪些形式的生物交互信息仍然可访问。我们探究ESM-2在其表示层级中是否像保留一阶和二阶信息一样强地保留高阶上位性信息，为此引入ORBIT-FMIB，一个结合Walsh交互分解与子集条件神经依赖估计的诊断框架。该方法在具有已知交互结构的合成景观上得到验证，随后应用于使用冻结ESM-2表示的密集四位点GB1适应度景观。初步生产运行表明，ESM-2保留高阶上位性信息的能力不如低阶信息（$\Delta_{\mathrm{HO-LO}}=-0.107$）。在匹配的GPU硬件和相同critic种子下，对完整测量网格进行的独立重复实验大幅缩小了这一对比（$\Delta_{\mathrm{HO-LO}}=-0.017$），且其符号在应用于相同训练critics的其他合理评估配对选择中不稳定（从$-0.011$到$+0.015$）。因此，我们目前没有有力证据表明ESM-2选择性地丢失高阶上位性信息，也没有证据表明各阶信息保留程度相同；方向性问题仍然悬而未决。测量协议本身，包括其记录的去除池化critics中位置子集捷径的方法，仍然有效且不受此发现影响。ORBIT-FMIB作为探测蛋白质基础模型中交互结构的诊断框架被提供；本研究自身的重复结果说明了为何在将此类探测输出视为生物学发现之前，需要充分有力的可重复性检查。
英文摘要
Protein foundation models support mutation-effect and structural prediction, but predictive performance alone does not reveal which forms of biological interaction information remain accessible through model depth. We ask whether ESM-2 retains higher-order epistatic information as strongly as first- and second-order information across its representation hierarchy, introducing ORBIT-FMIB, a diagnostic framework combining Walsh-based interaction decomposition with subset-conditioned neural dependence estimation. The method is validated on synthetic landscapes with known interaction structure before being applied to the dense four-site GB1 fitness landscape using frozen ESM-2 representations. An initial production run suggested ESM-2 retains higher-order epistatic information less well than lower-order information ($Δ_{\mathrm{HO-LO}}=-0.107$). An independent replication of the complete measurement grid, under matched GPU hardware and identical critic seeds, substantially reduced this contrast ($Δ_{\mathrm{HO-LO}}=-0.017$), and its sign was unstable across otherwise-defensible evaluation-pairing choices applied to the same trained critics ($-0.011$ to $+0.015$). We therefore do not currently have robust evidence that ESM-2 selectively loses higher-order epistatic information, nor that retention is equal across orders; the directional question remains open. The measurement protocol itself, including its documented removal of a positional-subset shortcut in pooled critics, remains validated and is unaffected by this finding. ORBIT-FMIB is offered as a diagnostic framework for probing interaction structure in protein foundation models; this study's own replication result illustrates why such probing requires adequately-powered reproducibility checks before its output is treated as a biological finding.
