EAGER: Exploring the biochemical principle of allostery for algorithm development

EAGER：探索变构的生物化学原理用于算法开发PI：Judith Klein-Seetharaman，结构生物学系，爱丁堡大学Co-PI：Christopher J. Langmead，计算机科学系，卡内基梅隆大学项目摘要动机：计算机科学和生物学通过类比相互启发，导致了新的算法类别，如神经网络和遗传算法，以及新的领域，如计算生物学和生物计算（使用生物分子的计算）。日常生活以及生物学中不断增加的数据流通常以网络为特征，例如互联网、电话网络、疾病传播网络、社交网络等。网络由边连接的节点组成，只有节点随应用领域而变化。网络结构是保守的：边缘允许通信和信息流。由于此类网络的规模、复杂性和动态性，其控制具有挑战性。随着环境的变化，这些网络的结构也会发生变化，并受到许多干扰和故障的影响。自然界面临着这些相同类型的挑战，并已发展出强大的策略，以确保信息的传输和系统适当地响应环境的变化：例如，血液中的氧转运蛋白，血红蛋白，改变其对氧的亲和力，以响应小分子配体，有利于在需要时释放氧气。机会：变构是一个生物化学术语，指的是生物分子，特别是蛋白质，通过一个小的局部扰动，在原子网络中实现远距离作用的能力。 蛋白质可以被看作是在三维空间中相互作用的原子网络。Allostery是一个经典的教科书的例子，实验研究和牢固建立的机制，控制这种原子网络。在这里，PI提出了一个假设，即人们可以将变构的生物化学原理与其他领域分享，如疾病传播，社交网络，经济学，监控应用和云计算。 了解大自然如何在分子水平上进行信息的获取、传输和处理，可能会导致未来在其他领域的技术。智力优势：虽然提出的假设可能具有变革性，但深入研究需要获得概念验证，概述（1）蛋白质中可能存在哪些机制可以转移到其他领域，以及（2）了解这种转移的要求。虽然蛋白质的变构是一个既定的生物化学原理，但人们对它是如何工作的以及如何预测它知之甚少。不幸的是，没有简单的性质来决定一个给定的蛋白质是否是（或可以）变构调节。虽然实验方法为变构提供了直接证据，但它们通常无法揭示其详细的物理和生物学机制。PI建议通过计算和实验相结合来揭示这些机制：通过破坏这条路径，可以验证或反驳两个遥远位点之间的预测通信路径。这项工作的成果将是一系列蛋白质变构的基本原理，并分析它们对将来扩展到非蛋白质相关网络的适用性。更广泛的影响：这笔赠款将支持研究人员和培训研究生从计算机科学，化学，生物学和生物医学领域。蛋白质变构建模和网络控制之间的技术融合有望加速许多学科的科学进步。因此，未来人们可能能够推动生物计算领域的发展，预测疾病爆发或在经济网络中确定远距离行动。

EAGER: Exploring the biochemical principle of allostery for algorithm developmentPI: Judith Klein-Seetharaman, Department of Structural Biology, University of PittsburghCo-PI: Christopher J. Langmead, Department of Computer Science, Carnegie Mellon UniversityProject AbstractMotivation: Computer science and biology have inspired each other by drawing analogies leading to new classes of algorithms such as neural networks and genetic algorithms and new fields such as computational biology and biocomputing (computing using biomolecules). The ever increasing data streams in everyday life as well as biology are most often characterized by networks, such as the internet, telephone network, disease transmission networks, social networks to name just a few. Networks consist of nodes connected by edges and only the nodes vary with the application areas. The network structures are conserved: the edges allow communication and information flow. Due to the size, complexity and dynamic nature of such networks, their control is challenging. As environments change, the structures of these networks change and are subject to numerous perturbations and failures. Nature faces these same types of challenges and has evolved robust strategies for ensuring that information is transmitted and that the system appropriately responds to changes in the environment: for example, the oxygen transport protein in the blood, hemoglobin, changes its affinity to oxygen in response to small molecule ligands favoring oxygen release where needed. The strategy that Nature employs in hemoglobin is called allostery.Opportunity: Allostery is a biochemical term that refers to the ability of biomolecules, in particular proteins, to achieve action at a distance in the atomic network through a small, localized perturbation. Proteins can be viewed as networks of atoms interacting in three-dimensional space. Allostery is a classical text-book example of an experimentally well studied and firmly established mechanism of control of this atomic network. Here, PIs propose the hypothesis that one can share the biochemical principle of allostery with other domains such as disease transmission, social networks, economics, surveillance applications and cloud computing. Understanding how Nature performs acquisition, transmission and processing of information at the molecular level may lead to future enabling technologies in other domains. Intellectual Merit: While the proposed hypothesis is potentially transformative, in-depth pursuit requires obtaining a proof-of-concept outlining (1) what kinds of mechanisms might exist in proteins that could be transferred to other domains and (2) develop an understanding of what are the requirements for such a transfer. Although allostery in proteins is an established biochemical principle, little is known how it works and how to predict it. Some proteins are regulated through allostery and others are not. Unfortunately, there is no simple property that determines whether a given protein is (or can be) allosterically regulated. While experimental methods provide direct evidence for allostery, they generally do not reveal the detailed physical and biological mechanisms for it. PIs propose to reveal these mechanisms through the combination of computation and experiments: a predicted path of communication between two distant sites can be validated or refuted by disrupting this path. The deliverables of this work will be a list of fundamental principles of allostery in proteins, and an analysis of their suitability for future extension to non-protein related networks. Broader Impact: This grant will support investigators and train graduate students from the areas of computer science, chemistry, biology & biomedicine. Convergence of technologies, here between protein allostery modeling and network control, is expected to speed up scientific progress in potentially many disciplines. Thus, one may in the future be able to push the field of biocomputing forward, predict disease outbreaks or identify action at a distance in economic networks.