FOLDING PROTEIN BY LOCALLY-CONSTRAINED MINIMIZATION OF A REDUCED STATISTICAL PO

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 Sosnick组当前的TeraGrid资源分配从2005年8月26日到2006年8月31日。由于我们有望在此时间之前利用我们所有剩余的时间，我们希望请求额外分配30,000小时的发展资源。我们已经使用我们目前的分配来测试我们的程序，通过局部约束最小化减少的统计势来折叠蛋白质。我们对蛋白质结构的简化表示只包括主干重原子和侧链β碳。我们的抽样方法考虑了二面角空间中统计势的离散模拟退火法最小化中的最近邻效应。扭转角被限制在目标构造的自然盆地。由于这种结构限制，我们的折叠算法是测试已知目标结构的设计蛋白质序列的折叠性的理想算法。事实上，我们已经在TeraGrid上使用了我们的折叠例程来比较我们的计算折叠的结果与Ranganathan对设计的WW结构域序列的实验折叠(Socolich等人，自然。2005,437(7058)：486-7)。我们的初步结果非常令人鼓舞，我们需要额外的TeraGrid资源来完成该项目。突显这一需求的重要性的是，花费了大量人力和资源的实验结果是在TeraGrid上以计算方式在很短的时间内用少量的人力完成的。随着持续的分配，我们希望将这种方法应用于更大的蛋白质序列的折叠，我们正在使用前面提到的减少的统计潜力来设计这些序列。我们目前正在生成大量设计的序列，但我们需要计算资源，以便我们可以测试它们是否适合折叠到目标结构中。我们将应用我们的折叠程序来筛选这些序列的折叠能力，然后在实验室中通过制造蛋白质来实验验证任何结果。在蛋白质设计领域，能够快速设计和折叠大量设计的序列将是一项杰出的技术成就。因此，我们继续访问TeraGrid提供的计算资源对这项研究至关重要。

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. The current Teragrid resource allocation for the Sosnick group runs from 08-26-2005 to 08-31-2006. Since we are on track to make use of all of our remaining hours before this time, we would like to request an additional Development Resource Allocation of 30,000 hours. We have used our current allocation to test our program for folding proteins by locally-constrained minimization of a reduced statistical potential. Our reduced representation of protein structure includes only backbone heavy atoms and side chain beta carbons. Our sampling method includes nearest neighbor effects in a discrete simulated-annealing minimization of a statistical potential in dihedral angle space. Torsional angles are constrained to the native basins of the target structure. Due to this structural constraint, our folding algorithm is ideal for testing the foldability of designed protein sequences for which the target structure is known. In fact, we have used our folding routine on the Teragrid to compare the results of our computational folding to Ranganathan's experimental folding of designed WW domain sequences (Socolich et al., Nature. 2005, 437(7058):486-7). Our initial results are extremely encouraging, and we require additional Teragrid resources to complete the project. Highlighting the importance of this need, the experimental results that took many human hours and resources were accomplished computationally on the Teragrid in a short amount of time with modest human effort. With a continuing allocation we would like to apply this method to the folding of larger protein sequences that we are designing using our aforementioned reduced statistical potential. We are currently generating a large number of designed sequences, but we need computational resources so that we can test their suitability to fold into the target structure. We will apply our folding routine to screen these sequences for their ability to fold and then experimentally verify any results by making the proteins in the lab. The ability to rapidly design and fold large numbers of designed sequences in silico would be an outstanding technical accomplishment in the field of protein design. It is thus critical to this research that we have continued access to the computational resources provided by Teragrid.