Understanding Essential Protein Dynamics through the Anharmonic Properties of Thermally Excited Vibrations

正构药物的选择性通常受到其在同源异构体中结合位点的结构相似性的限制。 蛋白质，而变构结合位点远不那么保守。这使得变构药物能够结合靶蛋白 具有更高的选择性，这降低了副作用的可能性并降低了药物毒性。然而，变构 药物发现一直局限于偶然的观察，因为合理的变构药物设计 战略面临着若干固有的挑战。这些挑战直接关系到目前在 蛋白质构象波动和集体动力学的可预测性是核心的机制 变构药物的作用。该项目的目标是发展计算方法，以促进 通过预测蛋白质构象波动和集体动力学合理设计变构药物 全原子模拟的结果 原则上，全原子分子动力学模拟可以直接探索蛋白质构象动力学， 对于药理学感兴趣的系统，需要以毫秒到秒的时间尺度进行采样。即使有 最先进的增强采样技术、相关的计算成本和硬件要求 （专用计算机、国家超级计算机、大型分布式计算网络）限制了此类 适用于少数系统。该项目旨在通过计算机发现变构 在大多数研究中， 实验室和大学。为此，为该项目开发的方法最大限度地利用了以下信息： 可以从分子动力学模拟中提取的固有蛋白质动力学。 这些方法最初将用于鉴定基质金属蛋白酶（MMP）中的变构机制， 其代表参与细胞外基质降解的结构同源蛋白质家族， 矩阵MMP家族的几个成员已被确定为慢性炎症背景下的药物靶标。 炎性疾病和癌症转移。MMPs具有高度保守的催化中心，这导致 正构小分子抑制剂对单个MMP的选择性低，限制了它们的治疗用途。 该项目旨在确定MMPs中的变构机制，从而实现高度靶向的发展。 选择性变构MMP抑制剂作为潜在的候选药物。 为该项目开发的方法是通用的，而不是特定于MMPs。因此，它们将适用于 在其他药物靶蛋白中识别变构机制，并将作为开放的， 源软件。

The selectivity of orthosteric drugs is often limited by the structural similarity of their binding sites in homologous proteins, while allosteric binding sites are far less conserved. This allows allosteric drugs to bind a target protein with higher selectivity, which reduces the potential for side-effects and lowers drug toxicity. However, allosteric drug discoveries have been limited to serendipitous observations because rational allosteric drug design strategies face several inherent challenges. These challenges are directly related to current limits in the predictability of protein conformational fluctuations and collective dynamics that are central to the mechanisms of allosteric drugs. The objective of this project is the development of computational methods to facilitate the rational design of allosteric drugs via predictions of protein conformational fluctuations and collective dynamics from all-atom simulations. In principle, all-atom molecular dynamics simulations can directly explore protein conformational dynamics but require sampling on timescales of milliseconds to seconds for systems of pharmacological interest. Even with state-of-the-art enhanced sampling techniques, the associated computational costs and hardware requirements (special purpose computers, national supercomputers, large distributed computing networks) limit such applications to a small number of systems. This project aims to make the computational discovery of allosteric mechanisms in proteins more efficient and achievable with computer hardware available in most research laboratories and universities. To this end, the methods developed for this project maximize the information on inherent protein dynamics that can be extracted from molecular dynamics simulations. These methods will initially be applied to identify allosteric mechanisms in matrix metallo-proteinases (MMPs), which represent a family of structurally homologous proteins involved in the degradation of the extracellular matrix. Several members of the MMP family have been identified as drug targets in the context of chronic inflammatory disease and cancer metastasis. MMPs feature a highly conserved catalytic center, which results in a low selectivity of orthosteric small molecule inhibitors for individual MMPs and limits their therapeutic use. This project aims to identify allosteric mechanisms in MMPs that enable the targeted development of highly selective allosteric MMP inhibitors as potential drug candidates. The methods developed for this project are general and not specific to MMPs. They will thus be applicable for the identification of allosteric mechanisms in other drug target proteins and will be made available as open- source software.