Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44106, USA.
Biol Direct. 2009 Dec 9;4:50. doi: 10.1186/1745-6150-4-50.
Ribonucleotide reductase is the main control point of dNTP production. It has two subunits, R1, and R2 or p53R2. R1 has 5 possible catalytic site states (empty or filled with 1 of 4 NDPs), 5 possible s-site states (empty or filled with ATP, dATP, dTTP or dGTP), 3 possible a-site states (empty or filled with ATP or dATP), perhaps two possible h-site states (empty or filled with ATP), and all of this is folded into an R1 monomer-dimer-tetramer-hexamer equilibrium where R1 j-mers can be bound by variable numbers of R2 or p53R2 dimers. Trillions of RNR complexes are possible as a result. The problem is to determine which are needed in models to explain available data. This problem is intractable for 10 reactants, but it can be solved for 2 and is here for R1 and ATP.
Thousands of ATP-induced R1 hexamerization models with up to three (s, a and h) ATP binding sites per R1 subunit were automatically generated via hypotheses that complete dissociation constants are infinite and/or that binary dissociation constants are equal. To limit the model space size, it was assumed that s-sites are always filled in oligomers and never filled in monomers, and to interpret model terms it was assumed that a-sites fill before h-sites. The models were fitted to published dynamic light scattering data. As the lowest Akaike Information Criterion (AIC) of the 3-parameter models was greater than the lowest of the 2-parameter models, only models with up to 3 parameters were fitted. Models with sums of squared errors less than twice the minimum were then partitioned into two groups: those that contained no occupied h-site terms (508 models) and those that contained at least one (1580 models). Normalized AIC densities of these two groups of models differed significantly in favor of models that did not include an h-site term (Kolmogorov-Smirnov p < 1 x 10(-15)); consistent with this, 28 of the top 30 models (ranked by AICs) did not include an h-site term and 28/30 > 508/2088 with p < 2 x 10(-15). Finally, 99 of the 2088 models did not have any terms with ATP/R1 ratios >1.5, but of the top 30, there were 14 such models (14/30 > 99/2088 with p < 3 x 10(-16)), i.e. the existence of R1 hexamers with >3 a-sites occupied by ATP is also not supported by this dataset.
The analysis presented suggests that three a-sites may not be occupied by ATP in R1 hexamers under the conditions of the data analyzed. If a-sites fill before h-sites, this implies that the dataset analyzed can be explained without the existence of an h-site.
核苷酸还原酶是 dNTP 产生的主要控制点。它有两个亚基,R1 和 R2 或 p53R2。R1 有 5 种可能的催化位点状态(空或填充 4 种 NDP 中的 1 种)、5 种可能的 s 位状态(空或填充 ATP、dATP、dTTP 或 dGTP)、3 种可能的 a 位状态(空或填充 ATP 或 dATP)、两种可能的 h 位状态(空或填充 ATP),所有这些都折叠成一个 R1 单体-二聚体-四聚体-六聚体平衡,其中 R1 j-mer 可以被可变数量的 R2 或 p53R2 二聚体结合。因此,可能有数万亿个 RNR 复合物。问题是确定在模型中需要哪些来解释可用数据。对于 10 种反应物,这个问题是无法解决的,但对于 2 种反应物是可以解决的,这里就是 R1 和 ATP。
通过假设完全解离常数是无穷大的和/或二元解离常数是相等的,通过假设来自动生成多达三个(s、a 和 h)ATP 结合位点的数千个 ATP 诱导的 R1 六聚体化模型 R1 亚基。为了限制模型空间大小,假设 s-位点在低聚物中始终填充,在单体中从不填充,并且为了解释模型术语,假设 a-位点先填充 h-位点。将模型拟合到已发表的动态光散射数据。由于 3-参数模型的最低 Akaike 信息准则(AIC)大于 2-参数模型的最低 AIC,因此仅拟合了具有 3 个参数的模型。然后,将均方误差小于最小误差两倍的模型分为两组:一组不包含占据的 h-位点项(508 个模型),另一组包含至少一个 h-位点项(1580 个模型)。这些模型组的归一化 AIC 密度差异显著,不包含 h-位点项的模型更有利(Kolmogorov-Smirnov p < 1 x 10(-15));与此一致,排名前 30 的模型中有 28 个不包含 h-位点项,28/30 > 508/2088,p < 2 x 10(-15)。最后,在 2088 个模型中,没有任何一个具有 ATP/R1 比值>1.5 的项,但在排名前 30 的模型中,有 14 个这样的模型(14/30 > 99/2088,p < 3 x 10(-16)),即在分析的数据集中,R1 六聚体中也不支持存在>3 个 a-位点被 ATP 占据。
提出的分析表明,在分析的数据条件下,R1 六聚体中可能没有 3 个 a-位点被 ATP 占据。如果 a-位点先于 h-位点填充,这意味着分析的数据集可以在没有 h-位点存在的情况下得到解释。