APE-Gen2.0: Expanding Rapid Class I Peptide–Major Histocompatibility Complex Modeling to Post-Translational Modifications and Noncanonical Peptide Geometries

The recognition of peptides bound to class I major histocompatibility
complex (MHC-I) receptors by T-cell receptors (TCRs) is a determinant
of triggering the adaptive immune response. While the exact molecular
features that drive the TCR recognition are still unknown, studies
have suggested that the geometry of the joint peptide–MHC (pMHC)
structure plays an important role. As such, there is a definite need
for methods and tools that accurately predict the structure of the
peptide bound to the MHC-I receptor. In the past few years, many pMHC
structural modeling tools have emerged that provide high-quality modeled
structures in the general case. However, there are numerous instances
of non-canonical cases in the immunopeptidome that the majority of
pMHC modeling tools do not attend to, most notably, peptides that
exhibit non-standard amino acids and post-translational modifications
(PTMs) or peptides that assume non-canonical geometries in the MHC
binding cleft. Such chemical and structural properties have been shown
to be present in neoantigens; therefore, accurate structural modeling
of these instances can be vital for cancer immunotherapy. To this
end, we have developed APE-Gen2.0, a tool that improves upon its predecessor
and other pMHC modeling tools, both in terms of modeling accuracy
and the available modeling range of non-canonical peptide cases. Some
of the improvements include (i) the ability to model peptides that
have different types of PTMs such as phosphorylation, nitration, and
citrullination; (ii) a new and improved anchor identification routine
in order to identify and model peptides that exhibit a non-canonical
anchor conformation; and (iii) a web server that provides a platform
for easy and accessible pMHC modeling. We further show that structures
predicted by APE-Gen2.0 can be used to assess the effects that PTMs
have in binding affinity in a more accurate manner than just using
solely the sequence of the peptide. APE-Gen2.0 is freely available
at https://apegen.kavrakilab.org.

T细胞受体（T-cell receptors, TCRs）识别与I类主要组织相容性复合体（class I major histocompatibility complex, MHC-I）受体结合的肽段，是触发适应性免疫应答的决定性因素。尽管驱动TCR识别的确切分子特征仍未明确，但已有研究表明，肽段-MHC复合物（peptide–MHC complex, pMHC）的整体空间构象发挥着重要作用。因此，亟需能够精准预测与MHC-I受体结合的肽段结构的方法与工具。近年来，涌现出多款pMHC结构建模工具，多数情况下可生成高质量的建模结构。但免疫肽组中存在大量非经典案例，多数现有pMHC建模工具无法处理，其中最突出的是带有非标准氨基酸、翻译后修饰（post-translational modifications, PTMs）的肽段，或是在MHC结合凹槽中呈现非经典构象的肽段。研究表明，这类化学与结构特征存在于新抗原中，因此对这些案例的精准结构建模对于癌症免疫治疗至关重要。为此，我们开发了APE-Gen2.0，这一工具在建模精度与非经典肽段案例的建模覆盖范围上，均优于其前代工具及其他pMHC建模工具。其改进之处包括：（i）可对带有多种类型翻译后修饰的肽段进行建模，例如磷酸化、硝化及瓜氨酸化；（ii）新增并优化了锚点识别流程，能够识别并建模带有非经典锚点构象的肽段；（iii）搭建了Web服务器，为便捷获取pMHC建模服务提供平台。我们进一步证实，相较于仅使用肽段序列，利用APE-Gen2.0预测的结构能够更准确地评估翻译后修饰对结合亲和力的影响。APE-Gen2.0可通过https://apegen.kavrakilab.org免费获取使用。