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中文摘要
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描述(由申请人提供):本提案的重点是开发新的方法和策略来发现金属蛋白抑制剂。金属蛋白是一类重要的药物靶点,与治疗多种疾病有关,包括癌症、关节炎、细菌感染和许多其他疾病。大多数抑制金属蛋白的治疗方法使用金属结合基团(MBG)与活性位点金属离子结合。尽管这些mbg很重要,但很少有研究开发出方法来鉴定、优化和了解对于特定金属蛋白来说,什么mbg是最好的。本提案旨在回答金属蛋白抑制剂中使用的MBGs的“什么,为什么和如何”,即:a)什么MBGs最好地抑制给定的金属蛋白?b)为什么某些MBGs对某种金属蛋白的抑制效果最好?c)如何加速MBGs的发现、评价和开发,从成功到领先?回答这些问题将解决药物化学和生物无机化学交叉的一个基本问题。我们的研究小组在金属蛋白抑制剂领域经验丰富,我们已经在回答上述问题方面取得了实质性进展。从根本上说,我们的实验室正在寻求一种基于片段的先导物发现(FBLD)方法来开发抑制剂,其中金属螯合剂首次被用作片段,将探索靶向结合金属蛋白活性位点的化学空间。在实施这种方法的过程中,我们开发了一个螯合物片段文库(CFL),可以很容易地筛选金属蛋白,以确定哪些MBGs与给定靶标结合最好。我们还确定了金属蛋白活性位点的MBG的结构,以了解MBG与活性位点高亲和力结合的原因。接下来,我们将使用生物无机模型复合物和计算对接方法相结合来开发改进的方法,以确定如何将发现的MBG片段开发成铅抑制剂。最后,我们结合了上述所有研究,制备了螯合剂亚库,提供了更先进的片段命中探测金属离子活性位点之外。在我们正在进行的研究中,我们将针对大量金属蛋白(Aim 1, Aim 4)筛选我们的文库,但将重点研究两个特定的Zn2+依赖系统(Aim 2, Aim 3),基质金属蛋白酶(MMPs)和碳酸酐酶(CAs)。这些金属蛋白具有共同的金属活性位点基序,但不同的MBG偏好,将作为测试我们的想法和比较和对比MBG结合细节的优秀系统。我们建议:1。开发和筛选螯合剂片段文库(cfl)针对广泛的金属蛋白靶标。利用现有的和新的cfl,将对十多种不同的金属酶进行筛选,以揭示mbg与各种靶标的最佳结合。2. 对蛋白质进行结构和热力学研究,从分子上理解为什么给定的MBG与给定的金属蛋白活性位点紧密结合。利用MMP-3和hCAI检测cfl的命中点,其中:a)共结晶mbg的晶体结构测定将揭示mbg -金属蛋白结合的关键特征,b)通过等温滴定量热法进行热力学研究将提供结合常数和相关能量参数。3. 在MMP和CA活性位点建立MBG片段模型,与蛋白质晶体学获得的结构数据进行比较。合成的生物无机模型化合物将结晶化,提供MBG不受约束结合模式的结构数据,而计算对接研究将用于预测MBG与金属蛋白之间的整体构象和第二配位球相互作用。通过结合生物无机模型和计算对接,我们将尝试准确地概括晶体学数据。4. 将制备含有MBG衍生物的子库,以使这些支架从hit变为lead。MBG支架的精加工将产生含有化合物的亚文库,这些化合物可以针对金属蛋白进行筛选,以提供更先进的铅结构。这些将用于MMPs和CAs,以及各种其他具有药用价值的金属蛋白。
英文摘要
DESCRIPTION (provided by applicant): This proposal is focused on developing new approaches and strategies to the discovery of metalloprotein inhibitors. Metalloproteins are an important class of medicinal targets that are relevant to treating numerous diseases including cancer, arthritis, bacterial infections, and many others. Most therapeutics that inhibit metalloproteins use a metal-binding group (MBG) to bind to the active site metal ion. Despite the importance of these MBGs, very few studies have developed methods to identify, optimize, and understand what MBGs are best for a given metalloprotein of interest. This proposal seeks to answer the 'what, why, and how' about the MBGs used in metalloprotein inhibitors, namely: a) WHAT MBGs best inhibit a given metalloprotein? b) WHY some MBGs give the best inhibition against a certain metalloprotein? c) HOW can the discovery, evaluation, and development of MBGs be accelerated from hit-to-lead? Answering these questions will address a fundamental problem at the intersection of medicinal and bioinorganic chemistry. Our research group is experienced in the field of metalloprotein inhibitors, and we have made substantial progress toward answering the aforementioned questions. Fundamentally, our laboratory is pursuing a fragment-based lead discovery (FBLD) approach to inhibitor development, where for the first time, metal chelators are being used as fragments that will explore chemical space targeted to binding metalloprotein active sites. In implementing this approach we have developed a chelator-fragment library (CFL) that can be readily screened against metalloproteins to identify what MBGs bind best to a given target. We have also determined the structure of an MBG in the active site of a metalloprotein to understand why the MBG binds with high affinity to the active site. Next, we have used and combination of bioinorganic model complexes and computational docking approaches to develop improved methods to determine how the discovery of MBG fragments can be developed into lead inhibitors. Finally, we have combined all of the aforementioned studies to prepare chelator sublibraries that provide more advanced fragment hits that probe beyond the metal ion active site. In our ongoing studies we will screen our libraries against a large number of metalloproteins (Aim 1, Aim 4), but will focus our more detailed studies on two specific Zn2+dependent systems (Aim 2, Aim 3), the matrix metalloproteinases (MMPs) and carbonic anhydrases (CAs). These metalloproteins, which share a common metal active site motif, but different MBG preferences, will serve as excellent systems against which to test our ideas and compare and contrast the details of MBG binding. We propose to: 1. Develop and screen chelator fragment libraries (CFLs) against a wide range of metalloprotein targets. Using existing and new CFLs, screens against more than ten different metalloenzymes will be performed to reveal what MBGs bind best to various targets. 2. Perform structural and thermodynamic studies with proteins to obtain a molecular understanding of why a given MBG binds tightly to a given metalloprotein active site. Hits from CFLs will be examined with MMP-3 and hCAI, where: a) crystallographic structure determinations with co-crystallized MBGs will reveal key features of MBG-metalloprotein binding, and b) thermodynamic studies via isothermal titration calorimetry will provide binding constants and relevant energetic parameters. 3. Model MBG fragments in the MMP and CA active site to compare with structural data obtained from protein crystallography. Synthetic bioinorganic model compounds will be crystallized providing structural data on the unrestrained mode of MBG binding, while computational docking studies will be used to predict the overall conformation and second coordination sphere interactions between the MBG and the metalloprotein. By combining bioinorganic modeling and computational docking we will try to accurately recapitulate the crystallographic data. 4. Sublibraries containing MBG derivatives will be prepared to advance these scaffolds from hit- to-lead. Elaboration of MBG scaffolds will produce sublibraries containing compounds that can be screened against metalloproteins to provide more advanced lead structures. These will be developed for the MMPs and CAs, as well as a variety of other metalloproteins of medicinal interest. PUBLIC HEALTH RELEVANCE: The inhibition of metalloproteins is important for the treatment of pathologies ranging from cardiac disease to cancer. This project seeks to discover novel compounds and new approaches to the identification of metalloprotein inhibitors. Improved understanding and optimization of the interactions between the inhibitor and the metal ions in the enzyme active site will be realized.
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