Modeling Project

项目摘要：建模项目 我们的总体目标是开发、应用和分发预测个人活动的计算工具 对于酶和在生化途径中共同发挥作用的多个酶。我们整合概念 并从比较蛋白质结构建模、基于结构的配基对接、综合 结构生物学、化学信息学和系统生物学。具体目标1.一个主要焦点是 基于结构的未知酶底物预测方法的开发与应用 功能；当实验结构不可用时，我们已经证明了比较蛋白质 模型可以被高效地使用。虽然我们已经取得了很大的成功，但关键的挑战仍然是 常规的、成功的应用，包括：对共价和非共价中间体进行采样，扩大 从简单的底物预测到跨代谢途径的活动预测，而基本缺乏 在我们的对接库中找到合适的代谢物。1A.我们将探索一种新的共价对接方法，使 对两个非共价中间体进行采样，因为这可能适用于许多酶家族。1B.我们将拓宽 我们的努力从对接潜在底物到对接单一目标，到对接候选成员 整个代谢途径；这将是代谢途径综合建模的关键信息。1C。致信地址 代谢物丢失的问题，我们将使用化学信息学来推断代谢物从对接 合成文库，它跨越更大的化学空间，比现有的代谢物有更少的间隙 图书馆。具体目标2.我们的目标是开发、应用和分发一种绘制代谢途径图的方法 这将确定一个途径中的酶和配体以及它们的顺序。目标将通过以下方式实现 整合结构和系统信息，如来自虚拟筛选、化学信息学、基因组学的数据 背景、配体结合实验和代谢组学。具体目标3.新陈代谢项目(由 The Protein Core)将测试代谢物对接单个酶的预测，以及 代谢途径的综合图谱，为评估和改进这些方法提供关键的反馈。 配基发现项目将为综合测绘提供数据，结构确定工作将 促进比较蛋白质建模，并在选定的情况下测试蛋白质-配体复合体的预测 代谢物对接产生的结构。具体目标4.我们将使我们的工具得到广泛应用，包括 如果可能，由非专业科学家进行。因此，我们将自动化并分发我们的开放源码包Web 服务器、数据库、基准测试和示例应用程序。这些将包括优化的代谢物库 以可对接的形式和用于对接这些代谢物的优化工具、共价对接工具、内部工具 锌系列程序和数据库，用于寻找类似合成分子的代谢物，并 优化特定的库，以及用于集成路径的开源IMP包。

PROJECT SUMMARY: MODELING PROJECT Our overall aim is to develop, apply, and distribute computational tools that predict the activities for individual enzymes and for multiple enzymes that function together in a biochemical pathway. We integrate concepts and methods derived from comparative protein structure modeling, structure-based ligand docking, integrative structural biology, chemoinformatics, and systems biology. Specific Aim 1. A major focus has been the development and application of structure-based approaches to predict substrates for enzymes of unknown function; when experimental structures are unavailable, we have demonstrated that comparative protein models can be productively used. While we have had substantial success, key challenges remain to enable routine, successful application, including: sampling both covalent and non-covalent intermediates, expanding from simple substrate prediction to predicting activities across a metabolic pathway, and an elementary lack of the right metabolites in our docking libraries. 1a. We will explore a new covalent-docking method to allow sampling both non-covalent intermediates as may be suitable for many enzyme families. 1b. We will broaden our efforts from docking potential substrates against a single target, to doing so against candidate members of an entire pathway; this will be key information to integrative modeling of metabolic pathways. 1c. To address the problem of missing metabolites, we will use chemoinformatics to infer metabolites from the docking of synthetic libraries, which span a much larger chemical space, and have fewer gaps, than the extant metabolite libraries. Specific Aim 2. We aim to develop, apply, and distribute a method for mapping metabolic pathways that will identify the enzymes and ligands in a pathway as well as their order. The goal will be achieved by integrating structural and systems information, such as data from virtual screening, cheminformatics, genomic context, ligand binding experiments, and metabolomics. Specific Aim 3. The Metabolism Project (supported by the Protein Core) will test predictions of metabolite docking on individual enzymes, and predictions of integrative mapping for metabolic pathways, providing crucial feedback to evaluate and improve the methods. The Ligand Discovery Project will provide data for integrative mapping, and structure determination efforts will facilitate comparative protein modeling and, in select cases, test predictions of protein-ligand complex structures generated by metabolite docking. Specific Aim 4. We will make our tools widely used, including, when possible, by non-expert scientists. Thus, we will automate and distribute our open source packages, web servers, databases, benchmarks, and sample applications. These will include optimized libraries of metabolites in dockable forms and an optimized tool for docking these metabolites, a tool for covalent docking, tools within the ZINC family of programs and databases to seek metabolites that resemble synthetic molecules, and to optimize specific libraries, and well as the open source IMP package for integrative pathway.