STRUCTURE MODELING OF HUMAN GPCRS AND DEVELOPMENT OF GPCR-TASSER

这个子项目是许多利用 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 G蛋白偶联受体（GPCR）是最大的膜蛋白家族，负责将生理和化学信号转导为细胞反应。这些蛋白质的功能障碍经常导致疾病，使它们成为一类重要的药物靶标。然而，基于结构的药物设计一直受到缺乏GPCR的原子水平蛋白质结构信息的阻碍。到目前为止，只有两个GPCR结构，牛视紫红质（1）和2-肾上腺素能受体（2）已被解决。之前，我们使用TASSER（Threading ASSEmbly Refinement）算法（3）来生成人类基因组中907个推定GPCR的结构预测（http：//cssb.biology.gatech.edu/skolnick/files/gpcr/gpcr.html）。由于TASSER使用基于蛋白质模型的简化的Ca和侧链质量中心，因此估计这些GPCR模型中的大多数对于骨架Ca原子具有3-6范围内的与天然的均方根偏差（RMSD），这是对拓扑分析和一定水平的生物功能推断有用的准确度（4）。该研究旨在开发新的计算方法，用于生成高分辨率的GPCR模型，使用复合GPCR特异性和I-TASSER势，该复合势包括来自GPCR文献和实验数据的基于知识的势，还包括用于TM螺旋正确取向的疏水矩项。结合实验约束的建模将显着提高这些模型的生物学实用性。参考文献：（1）Palczewski K，Kumasaka T，Hori T，Behnke CA，Motoshima H，Fox BA，Le Trong I，Teller DC，Okada T，Stenkamp RE，Yamamoto M，Miyano M.视紫红质的晶体结构：一种G蛋白偶联受体。Science 2000;289（5480）：739-745. (2)Cherezov V，Rosenbaum DM，Hanson MA，Rasmussen SG，Thian FS，Kobilka TS，Choi HJ，Kuhn P，Weis WI，Kobilka BK，Stevens RC.一个工程化的人β 2-肾上腺素能G蛋白偶联受体的高分辨率晶体结构。Science 2007;318（5854）：1258-1265. (3)Zhang Y，Skolnick J.在基因组规模上弱同源蛋白质的自动结构预测。美国国家科学院院刊2004;101：7594-7599。(4)Zhang Y，Devries ME，Skolnick J.人类基因组中所有已鉴定的G蛋白偶联受体的结构建模。PLoS Comput Biol 2006;2（2）：e13

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. G protein coupled receptors (GPCRs) comprise the largest family of integral membrane proteins and are responsible for transduction of physiological & chemical signals into a cellular response. Malfunctioning of these proteins frequently causes a diseased condition, making them an important class of drug targets. However, structure-based drug design has been hampered by the lack of atomic-level protein structure information for GPCRs. Until now, only two of the GPCR structures, bovine rhodopsin(1) and 2-adrenergic receptor(2) have been solved. Previously, we employed TASSER (Threading ASSEmbly Refinement) algorithm (3) to generate structure prediction for 907 putative GPCRs in human genome (http://cssb.biology.gatech.edu/skolnick/files/gpcr/gpcr.html). Because TASSER uses a reduced Ca and side chain center of mass based protein models, most of these GPCRs models are estimated to have a root mean square deviation (RMSD) from native in the range of 3-6 for the backbone Ca atoms an accuracy useful for topology analysis and some level of biological function inference (4). The proposed study seeks to develop new computational methodologies for the generation of high resolution GPCR models using a composite GPCR specific and I-TASSER potential.This composite potential would include a knowledge based potential derived from literature and experimental data of GPCRs and also include a hydrophobic moment term for proper orientation of TM-helix. Modeling incorporated with experimental constraints will significantly enhance the biological usefulness of these models. References: (1) Palczewski K, Kumasaka T, Hori T, Behnke CA, Motoshima H, Fox BA, Le Trong I, Teller DC, Okada T, Stenkamp RE, Yamamoto M, Miyano M. Crystal structure of rhodopsin: A G proteincoupled receptor. Science 2000;289(5480):739-745. (2) Cherezov V, Rosenbaum DM, Hanson MA, Rasmussen SG, Thian FS, Kobilka TS, Choi HJ, Kuhn P, Weis WI, Kobilka BK, Stevens RC. High-resolution crystal structure of an engineered human beta2-adrenergic G protein-coupled receptor. Science 2007;318(5854):1258-1265. (3) Zhang Y, Skolnick J. Automated structure prediction of weakly homologous proteins on a genomic scale. Proceedings of the National Academy of Sciences of the United States of America 2004;101:7594-7599. (4) Zhang Y, Devries ME, Skolnick J. Structure modeling of all identified G protein-coupled receptors in the human genome. PLoS Comput Biol 2006;2(2):e13