Structural Genomics of Pathogenic Protozoa

描述（由申请人提供）：病原体的结构基因组学 原生动物（SGPP）财团旨在实现高通量测定 来自病原性原生动物的蛋白质结构，具有重大的全球医学意义。 其中包括几种锥虫，负责睡眠 疾病、南美锥虫病以及皮肤、内脏和皮肤粘膜 利什曼病和恶性疟原虫，致命疟疾的病原体 每年有数亿例病例和一两百万例死亡， 主要是儿童。这些生物与其他物种只有远亲关系 并具有许多独特的生物学特征。我们的目标是确定一个 NN可溶性、异源多聚体和膜蛋白的总量。 拟议研究的特点是： 1.利用蛋白质结构预测方法和医学相关性研究靶点 选择; 2.快速评估数千种蛋白质的表达水平和溶解度， 通过来自不同菌株的乱序序列获得的蛋白质变体; 3.用双杂交方法发现和求解可溶性 异源多聚体; 4.通过双杂交，显著强调膜蛋白的发现 方法和Fv噬菌体文库，相互作用的可溶性伴侣蛋白， 用于共结晶和MAD定相; 5.机器人在结晶、晶体镶嵌、数据处理中的密集使用 收集步骤; 6.含溴共晶化合物库的研制 7.探索晶体退火在改善镶嵌性和 决议; 8.蛋白质结构预测在电子密度解释中的应用 9.使用配体对接程序，深度序列家族比对和非常 弱结构同源性，从结构中推导出功能; 10.创建SGPP网站和SGPP关系数据库， 用于蛋白质表达、纯化、结晶和结构 确定，以及坐标和结构因素是可用的 向公众

DESCRIPTION (provided by applicant): The Structural Genomics of Pathogenic Protozoa (SGPP) consortium aims to achieve high-throughput determination of protein structures from pathogenic protozoa of major global medical relevance. These include several species of Trypanosomatids, responsible for sleeping sickness, Chagas' disease, and cutaneous, visceral and mucocutaneous leishmaniasis; and Plasmodium falciparum, the causative agent of lethal malaria with several hundred million cases annually and one to two million deaths, mainly children. These organisms are only distantly related to other species and characterized by many unique biological features. We aim to determine a total of NN soluble, heteromultimeric and membrane proteins. Special characteristics of the proposed research are: 1. Using protein structure prediction methods and medical relevance in target selection; 2. Rapid evaluation of expression levels and solubility of thousands of variants of proteins obtained by scrambled sequences from different strains; 3. Using two-hybrid methods to discover and solve structures of soluble heteromultimers; 4. Significant emphasis on membrane proteins with discovery, by two-hybrid methods and Fv phage libraria,of interacting soluble partner proteins to be used for co-crystallization and MAD phasing; 5. Intensive use of robotics in the crystallization, crystal mounting, data collection steps; 6. Development of bromine-containing co-crystallant libraries; 7. Exploring the power of crystal annealing in improving mosaicity and resolution; 8. Using predicted protein structures in electron density interpretation; 9. Using ligand docking procedures, deep sequence family alignments and very weak structural homologies to derive function from structure; 10. Create a SGPP website and a SGPP relational data base by which protocols for protein expression, purification, crystallization and structure determination, as well as coordinates and structure factors are made available to the public.