CompBio: A Novel Computational Framework for Docking of Flexible Proteins

蛋白质是生命的基本组成部分。 它们在每个生物的细胞内执行许多重要功能。 这些功能包括信号传导、代谢、运输和繁殖。 蛋白质通过与细胞内的其他蛋白质或分子相互作用来发挥其功能。 这种相互作用可导致两个分子结合形成复合物，或导致这种复合物分离成其组分。 在蛋白质之间的相互作用过程中，每个分子可能不得不改变其三维形状以适应与另一个分子的结合。 这是可能的，因为许多蛋白质具有固有的灵活性。 人们普遍认为，蛋白质的三维形状及其改变其形状的能力独特地决定了蛋白质的生物学功能。了解细胞中蛋白质的生物学功能将有助于详细了解细胞内发生的复杂过程。 这种理解还将有助于设计新的药物，以影响这些过程，如果它们在疾病的情况下受到影响。 仅从生物实验中获得这样的理解是非常昂贵和耗时的。 因此，准确模拟柔性生物分子之间相互作用的能力有望促进计算药物设计的科学进步，并代表了一个重要的计算工具，以扩大我们对细胞过程的理解。 作为对这一目标的重大贡献，研究人员建议开发一种新的计算框架，用于计算效率和生物学上准确的柔性protein.The蛋白质对接的问题是计算上具有挑战性的，即使在简化的假设下，两个机构是内部刚性的。 然而，忽略蛋白质的内部柔性被认为是当前对接方法的缺点。 该算法框架利用机器人学的方法对蛋白质的内部柔性进行了有效的分析和建模，并在此基础上有效地适应对接过程中发生的构象变化。 由此产生的计算框架可以被看作是一个新的算法基础，有效的和生物准确的计算对接的柔性蛋白质。

Proteins are the basic building blocks of life. They perform many important functions within the cells of each living being. These functions include signaling, metabolism, transport, and reproduction. A protein performs its function by interacting with other proteins or molecules inside the cell. Such an interaction may result in the binding of two molecules to form a complex, or in the separation of such a complex into its components. During the interactions among proteins, each molecule may have to change its three-dimensional shape in order to accommodate the binding with another molecule. This is possible because many proteins are inherently flexible. It is generally accepted that the three-dimensional shape of a protein and its ability to change its shape uniquely determine the protein's biological function. An understanding of the biological function of proteins in the cell would allow a detailed understanding of the complex processes that happen inside a cell. Such an understanding would also facilitate the design of new drugs to influence these processes, should they be affected in the case of a disease. To gain such an understanding from biological experiments alone is very costly and time-consuming. The ability to accurately simulate interactions among flexible biomolecules therefore promises to facilitate scientific advances in computational drug design and represents an important computational tool to expand our understanding of cellular processes. As a significant contribution towards this objective, the investigators propose to develop a novel computational framework for computationally efficient and biologically accurate docking of flexible proteins.The problem of protein docking is computationally challenging, even under the simplifying assumption that both bodies are internally rigid. However, ignoring the internal flexibility of a protein is recognized as a shortcoming in current docking approaches. The proposed algorithmic framework uses methods from robotics to effectively analyze and model the internal flexibility of a protein.Based on this analysis, conformational changes occurring during the docking process can be accommodated effectively. The resulting computational framework can be seen as a new algorithmic foundation for efficient and biologically accurate computational docking of flexible proteins.