BETASCAN: probable beta-amyloids identified by pairwise probabilistic analysis.
BETASCAN: probable beta-amyloids identified by pairwise probabilistic analysis.
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DOI：
10.1371/journal.pcbi.1000333
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发表时间：
2009-03
影响因子：
4.3
通讯作者：
Berger B
中科院分区：
文献类型：
--
作者：
Bryan AW Jr;Menke M;Cowen LJ;Lindquist SL;Berger B
淀粉样蛋白和蛋白是临床上和生物学上重要的β结构，其超二级结构很难通过标准的实验或计算手段来确定。此外，已知或怀疑在许多淀粉样原纤维中存在显著的构象异质性。最近的工作表明，成对概率统计在β结构预测中是有用的。我们在这里发展了一种新的β结构预测策略，强调确定β链和β链对作为β结构的基本单元。我们的程序BETASCAN根据在平行β-Sheet中观察到的相关性计算潜在β链和链对的似然分数。然后，该程序确定对于该序列的所有潜在β结构具有最大局部似然性的链和对。BETASCAN建议多种交替折叠模式，并仅基于氨基酸序列、概率表和预先选择的参数来分配相对先验概率。在β结构预测和淀粉样蛋白倾向预测方面，该算法与以前的算法(BetaPro、意大利面、Salsa、Tango和Zyggregator)的结果相比是有利的。对于实验确定的淀粉样β结构，一组已知的β聚集体，以及平行的β螺旋的β链，淀粉样球蛋白，都证明了准确的预测。BETASCAN不仅能够以更高的灵敏度检测β链，而且能够在丰富的类似β的序列中检测β链的边缘。对于两种蛋白质(Aβ和HET-S)，存在多组相互矛盾的结构的实验数据；BETASCAN能够将每个竞争结构检测为潜在的结构变体。将多个交替的β结构与实验相关联的能力开启了对Pron菌株和淀粉样蛋白结构异质性的计算研究的可能性。贝塔斯坎公司的网址是：http://betascan.csail.mit.edu.。淀粉样蛋白是一种高度有序的蛋白质聚集形式，可由多种蛋白质形成。虽然最早发现的淀粉样蛋白与全身和神经退行性疾病有关，但最近的发现表明，淀粉样蛋白可能具有从学习和记忆到酵母表观遗传学，再到生物膜和黑色素产生的各种角色和功能。在这项研究中，我们扩大了我们理解淀粉样蛋白特性是如何从其多肽序列中产生的能力的范围和灵活性。通过利用一种特征淀粉样结构-平行β链-的内在属性和来自现有蛋白质结构的数据，我们构建并测试了一种算法，以预测蛋白质的特定部分形成淀粉样蛋白的概率。我们的方法的优点是更准确地检测这些区域的边缘，以及能够考虑和评估多个折叠模式的可能性。
Amyloids and prion proteins are clinically and biologically important β-structures, whose supersecondary structures are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Recent work has indicated the utility of pairwise probabilistic statistics in β-structure prediction. We develop here a new strategy for β-structure prediction, emphasizing the determination of β-strands and pairs of β-strands as fundamental units of β-structure. Our program, BETASCAN, calculates likelihood scores for potential β-strands and strand-pairs based on correlations observed in parallel β-sheets. The program then determines the strands and pairs with the greatest local likelihood for all of the sequence's potential β-structures. BETASCAN suggests multiple alternate folding patterns and assigns relative a priori probabilities based solely on amino acid sequence, probability tables, and pre-chosen parameters. The algorithm compares favorably with the results of previous algorithms (BETAPRO, PASTA, SALSA, TANGO, and Zyggregator) in β-structure prediction and amyloid propensity prediction. Accurate prediction is demonstrated for experimentally determined amyloid β-structures, for a set of known β-aggregates, and for the parallel β-strands of β-helices, amyloid-like globular proteins. BETASCAN is able both to detect β-strands with higher sensitivity and to detect the edges of β-strands in a richly β-like sequence. For two proteins (Aβ and Het-s), there exist multiple sets of experimental data implying contradictory structures; BETASCAN is able to detect each competing structure as a potential structure variant. The ability to correlate multiple alternate β-structures to experiment opens the possibility of computational investigation of prion strains and structural heterogeneity of amyloid. BETASCAN is publicly accessible on the Web at http://betascan.csail.mit.edu. Amyloid is a highly ordered form of protein aggregation that a wide variety of proteins can form. While the earliest discovered amyloids were associated with systemic and neurodegenerative diseases, recent findings indicate amyloids may have myriad roles and functions ranging from learning and memory, to yeast epigenetics, to biofilm and melanin production. In this study, we expand the range and flexibility of our ability to understand how amyloid properties arise from their polypeptide sequence. By taking advantage of the intrinsic properties of a characteristic amyloid structure—parallel β-strands—and data from available protein structures, we construct and test an algorithm to predict the probability that particular portions of a protein will form amyloid. Our method has the advantage of more accurate detection of the edges of such zones, as well as the ability to consider and evaluate the likelihood of multiple folding patterns.
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DOI：
10.1038/nsb786
发表时间：
2002-05-01
期刊：
NATURE STRUCTURAL BIOLOGY
影响因子：
--
作者：
DePace, AH;Weissman, JS
通讯作者：
Weissman, JS
DOI：
10.1002/prot.340230412
发表时间：
1995-12-01
期刊：
PROTEINS-STRUCTURE FUNCTION AND GENETICS
影响因子：
--
作者：
Frishman, D;Argos, P
通讯作者：
Argos, P
影响因子：
9.8
作者：
Fowler DM;Koulov AV;Alory-Jost C;Marks MS;Balch WE;Kelly JW
通讯作者：
Kelly JW
影响因子：
14.9
作者：
Chenna, R;Sugawara, H;Thompson, JD
通讯作者：
Thompson, JD
影响因子：
64.8
作者：
Krishnan, R;Lindquist, SL
通讯作者：
Lindquist, SL