Integrating Experiment and Theory to Characterize Diagnostic Antibody Specificity

描述(由申请人提供)：许多疾病的诊断试剂是基于抗体试剂紧密结合的能力，特别是与细胞表面的糖结合的能力，这些糖是疾病的标志。了解这些相互作用的3D结构有助于优化试剂并有助于确认其特异性，然而传统的实验方法往往不适合处理大的柔性糖。因此，替代的高通量技术，如根据固定的糖链阵列筛选蛋白质或抗体试剂，已经成为识别结合伙伴的流行方法。然而，阵列筛选不提供有关3D结构的任何信息，并且容易产生假阴性或非特异性结果。这项建议的主要目的是开发一个强大的高通量计算平台来预测碳水化合物-抗体(或一般蛋白质)复合体的3D结构，该平台将整合来自糖链微阵列筛选的数据以确定观察到的结合特异性的来源，最终目标是帮助开发高特异性诊断试剂。这项工作将通过以下阶段进行：1)开发用于对接最小糖链结合基序的自动化工具，叠加共享该基序的实验筛选数据集中的每个糖链，以及确定实验上一致的3D姿势2)开发用于碳水化合物的计算评分函数，这项工作融合了GLYCAM碳水化合物力场的势能函数3)创建了一项年度竞赛，以预测涉及理论和实验糖学社区的糖-蛋白质3D结构4)创建了一套基于网络的工具，允许用户上传他们的蛋白质结构和糖链阵列数据，并执行碳水化合物线程，以生成他们的碳水化合物-蛋白质复合体的实验一致的3D模型这项工作在整合高通量计算和实验技术方面具有很高的创新性，以生成实验上一致的3D模型，否则很难表征分子复合体。值得注意的是，该方法建立在每种方法的优势之上，同时有助于识别阵列筛选和理论配基对接中常见的错误。 与公共卫生相关：高特异性诊断试剂的开发将极大地受益于研究其3D结构的能力；然而，传统的实验方法往往不太适合与一些典型的疾病相关标记物一起工作，如大的柔性糖。因此，高通量实验技术，如针对固定化的复合糖(多糖)阵列筛选诊断试剂，已成为识别结合伙伴的流行方法；但仅凭阵列筛选不能提供任何3D信息。这项建议的主要目的是开发和整合理论3D结构预测方法和来自糖链阵列筛选的数据，以生成帮助开发高特异性诊断试剂的计算工具。

DESCRIPTION (provided by applicant): Diagnostic agents for many diseases are based on the ability of antibody reagents to bind tightly and specifically to sugars on cell surfaces that are markers for the disease. Knowledge of the 3D structure of these interactions helps to optimize the reagent and aids in confirming its specificity, however traditional experimental methods are often poorly suited to working with large flexible sugars. Consequently, alternative high- throughput techniques, such as screening the protein or antibody reagent against immobilized arrays of glycans have become popular for identifying the binding partners. Array screening does not however provide any information on the 3D structure, and can be prone to false negative or non-specific results. The principle aim of this proposal is to develop a robust high-throughput computational platform for predicting the 3D structure of carbohydrate-antibody (or protein in general) complexes, which will integrate data from glycan microarray screening to define the origin of the observed binding specificity, with the ultimate goal of aiding in the development of high-specificity diagnostic agents. This work will proceed through the following stages 1) The development of automated tools for docking the minimal glycan binding motifs, superimposing each of the glycans from the experimental screening data set that share the motif, and determining experimentally- consistent 3D poses 2) The development of a computational scoring function that is tuned for use with carbohydrates, and that incorporates the potential energy functions from the GLYCAM carbohydrate force field 3) The creation of an annual competition to predict glycan-protein 3D structures involving the theoretical and experimental glycoscience communities 4) The creation of a web-based set of tools that allows users to upload their protein structure and glycan array data and perform Carbohydrate Threading to generate an experimentally-consistent 3D model for their carbohydrate-protein complex This work is highly innovative in integrating high-throughput computational and experimental techniques to generate experimentally-consistent 3D models for otherwise hard to characterize molecular complexes. Notably the approach builds on the strengths of each method and concurrently aids in identifying the errors commonly found in array screening and theoretical ligand docking. PUBLIC HEALTH RELEVANCE: The development of highly specific diagnostic agents would benefit greatly from the ability to study their 3D structures; however traditional experimental methods are often poorly suited to working with some typical disease-associated markers, such as large flexible sugars. Consequently, high-throughput experimental techniques, such as screening the diagnostic reagent against immobilized arrays of complex sugars (glycans) have become popular for identifying the binding partners; but array screening alone does not provide any 3D information. The principle aim of this proposal is to develop and integrate theoretical 3D structure prediction methods with data from glycan array screening to generate computational tools to aid in the development of high-specificity diagnostic agents.