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的一个 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。 当前为Sosnick组分配的Teragrid资源从2005年8月26日运行到2006年8月31日。由于我们正在利用我们所有剩余的时间在这个时候之前，我们想要求额外的发展资源分配30,000小时。我们已经使用我们目前的分配来测试我们的程序折叠蛋白质的局部约束最小化减少的统计潜力。我们简化的蛋白质结构表示仅包括主链重原子和侧链β碳。我们的采样方法包括最近邻效应在二面角空间中的统计势的离散模拟退火最小化。扭转角被约束到目标构造的原生盆地。由于这种结构的限制，我们的折叠算法是理想的测试设计的蛋白质序列的目标结构是已知的可折叠性。事实上，我们已经在Teragrid上使用了我们的折叠程序来比较我们的计算折叠结果与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。为了突出这一需求的重要性，需要花费大量人力和资源的实验结果在Teragrid上以计算方式在短时间内完成，只需少量人力。随着持续的分配，我们希望将这种方法应用于我们正在设计的更大的蛋白质序列的折叠，使用我们前面提到的减少的统计潜力。我们目前正在生成大量的设计序列，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成目标结构。我们将应用我们的折叠程序来筛选这些序列的折叠能力，然后通过在实验室中制造蛋白质来实验验证任何结果。在计算机中快速设计和折叠大量设计序列的能力将是蛋白质设计领域的杰出技术成就。因此，我们继续使用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.