Linse Björn, Linse Sara
Lund University, Chemical Centre, Department of Biochemistry, P O Box 124, SE-221 00 Lund, Sweden.
Mol Biosyst. 2011 Jul;7(7):2296-303. doi: 10.1039/c0mb00321b. Epub 2011 May 17.
Severe conditions and lack of cure for many amyloid diseases make it highly desired to understand the underlying principles of formation of fibrillar aggregates (amyloid). Here, amyloid formation from peptides was studied using Monte Carlo simulations. Systems of 20, 50, 100, 200 or 500 hexapeptides were simulated. Association kinetics were modeled equal for fibrillar and other (inter- and intra-peptide) contacts and assumed to be faster the lower the effective contact order, which represents the distance in space. Attempts to form contacts were thus accepted with higher probability the lower the effective contact order, whereby formation of new contacts next to preexisting ones is favored by shorter physical separation. Kinetic discrimination was invoked by using two different life-times for formed contacts. Contacts within amyloid fibrils were assumed to have on average longer life-time than other contacts. We find that the model produces fibrillation kinetics with a distinct lag phase, and that the fibrillar contacts need to dissociate on average 5-20 times slower than all other contacts for the fibrillar structure to dominate at equilibrium. Analysis of the species distribution along the aggregation process shows that no other intermediate is ever more populated than the dimer. Instead of a single nucleation event there is a concomitant increase in average aggregate size over the whole system, and the occurrence of multiple parallel processes makes the process more reproducible the larger the simulated system. The sigmoidal shape of the aggregation curves arises from cooperativity among multiple interactions within each pair of peptides in a fibril. A governing factor is the increasing probability as the aggregation process proceeds of neighboring reinforcing contacts. The results explain the very strong bias towards cross β-sheet fibrils in which the possibilities for cooperativity among interactions involving neighboring residues and the repetitive use of optimal side-chain interactions are explored at maximum.
许多淀粉样疾病的病情严重且缺乏治愈方法，这使得深入了解纤维状聚集体（淀粉样蛋白）形成的潜在原理成为迫切需求。在此，我们使用蒙特卡罗模拟研究了肽形成淀粉样蛋白的过程。对由20、50、100、200或500个六肽组成的系统进行了模拟。对于纤维状接触和其他（肽间和肽内）接触，将缔合动力学建模为相等，并假设有效接触顺序越低（有效接触顺序代表空间距离），缔合动力学越快。因此，有效接触顺序越低，形成接触的尝试被接受的概率越高，由此，在预先存在的接触旁边形成新接触更有利于缩短物理距离。通过对已形成的接触使用两种不同的寿命来引入动力学判别。假设淀粉样纤维内的接触平均寿命比其他接触更长。我们发现该模型产生具有明显滞后阶段的纤维化动力学，并且为了使纤维状结构在平衡时占主导地位，纤维状接触平均解离速度需要比所有其他接触慢5 - 20倍。对聚集过程中物种分布的分析表明，没有其他中间体的数量比二聚体更多。不是单个成核事件，而是整个系统中平均聚集体尺寸伴随增加，并且多个平行过程的发生使得模拟系统越大，该过程越具可重复性。聚集曲线的S形源于纤维中每对肽内多个相互作用之间的协同作用。一个主导因素是随着聚集过程的进行，相邻增强接触的概率增加。这些结果解释了对交叉β-折叠纤维的强烈偏好，在这种纤维中，涉及相邻残基的相互作用之间的协同可能性以及最佳侧链相互作用的重复使用得到了最大程度的探索。
