Software tools for structure elucidation of synthetic and natural product peptide mixtures by LC-IM-MS

多肽是一种生物分子，由由化学键连接的氨基酸链组成。多肽在生物学中有许多至关重要的作用，包括作为防御分子、激素和允许免疫系统识别受感染的细胞。大脑中肽簇的积累与阿尔茨海默病有关。因此，多肽通常用于旨在了解基本生物学和疾病机制的研究，以及作为新疗法的起点。肽类药物已经被批准用于治疗从癌症到便秘的各种疾病，而且近年来进入市场的肽类药物数量也在不断增加。多肽可以通过适当生物的自然发酵生产用于实验和治疗，尽管在实验室用氨基酸化学方法生产多肽通常更方便。这两种途径提供的材料不仅包含所需的肽，而且通常还包含其他分子，这些分子可能与感兴趣的分子具有非常相似的化学结构。当用化学方法制造多肽时，许多其他副产物的结构可以通过对反应和副反应的了解来预测。虽然净化程序有助于去除许多杂质，但这会增加时间和费用，浪费样品，并且永远不会100%有效。不幸的是，肽杂质本身可能具有非常强烈的生物活性，如果实验人员不知道它们的存在，可能会引起混淆和误解。因此，对肽样品进行仔细分析是非常必要的，以确定究竟存在什么，并且确实是用于药物的肽质量控制的必要部分。现代仪器对多肽样品的分析包括几个阶段。在第一阶段，根据多肽的物理性质尽可能地分离水溶液中的多肽。然后，溶液通过高压针，形成喷雾，溶剂蒸发，留下含有带电荷的肽分子的气体。然后，这些带电荷的肽根据它们的大小和电荷进行分类，然后进行最后一步，将它们分解成碎片并测量它们的质量。由于每个样本可能包含许多不同的肽，这些实验产生了大量的数据，挑战在于将这些数据与肽结构联系起来，根据它们包含的氨基酸类型和这些氨基酸连接在一起的顺序。我们建议的目标是编写新的计算机软件，通过自动标记可检测肽的身份来简化这项任务。为此，该软件将模拟多肽及其副产品的合成，对其分析特性进行预测，并将这些预测与实验数据进行比较。该软件将在典型的实验室和办公室计算机上运行，并将具有友好的图形用户界面。它将采用模块化设计，使我们能够在未来根据工业界和学术界的需求添加和改进功能。我们最初将免费提供核心功能集，但随后将为商业用户提供付费的增强版本，以支持未来的开发。

Peptides are biological molecules that are composed of chains of amino acid building blocks linked by chemical bonds. Peptides have many crucial roles in biology, including as defensive molecules, hormones, and allowing the immune system to recognise infected cells. Accumulation of clusters of peptides in the brain is implicated in Alzheimer's disease. Therefore peptides are commonly employed in research aimed at understanding basic biology and mechanisms of disease, as well as acting as starting points for new therapeutics. Peptide drugs have already been approved for conditions ranging from cancer to constipation and the number of peptides coming to market has accelerated in recent years.Peptides can be produced for experiments and therapies through natural fermentation of appropriate organisms, although it is often more convenient to produce them chemically from amino acids in the laboratory. Both routes afford material that contains not just the desired peptide but typically also other molecules which may have very similar chemical structures to the one of interest. When making peptides chemically, the structures of many of these other by-products can be predicted from knowledge of the reactions and side-reactions taking place. Although purification procedures help to remove many impurities, this adds time and expense, wastes sample and is never 100% effective. Unfortunately, the peptide impurities may themselves have very intense biological activity which can cause confusion and misunderstanding if experimenters are unaware of their presence. Careful analysis of peptide samples is therefore highly desirable to determine exactly what is present, and indeed is a required part of the quality control for peptides destined to be used as drugs.Peptide sample analysis on modern instruments involves several stages. In the first stage, peptides in an aqueous solution are separated as well as possible according to their physical properties. This solution then passes through a high voltage needle which leads to a spray from which the solvent evaporates to leave a gas containing the peptide molecules with an electrical charge. These charged peptides are then sorted by their size and electric charge, before undergoing a final step in which they are broken into pieces and their masses are measured. As each sample may contain many different peptides, these experiments produce huge quantities of data and the challenge is to relate this to the peptide structures in terms of the types of amino acid that they contain and the order in which these amino acids are connected together. The goal of our proposal is to write new computer software to simplify this task by automatically labelling the data with the identities of the peptides that can be detected. To do this, the software will simulate the synthesis of peptides and their by-products, make predictions about their analytical properties and compare these predictions with the experimental data. The software will run on typical laboratory and office computers and will feature a friendly graphical user interface. It will have a modular design that will allow us to add and refine features in the future in response to the demands of industry and academia. We will initially make a core set of features available for free, but subsequently offer enhanced versions catering for commercial users for a fee that will support future development.