Sakoda M, Hiromi K
J Biochem. 1976 Sep;80(3):547-55. doi: 10.1093/oxfordjournals.jbchem.a131310.
The best-fit values of the Michaelis constant (Km) and the maximum velocity (V) in the Michaelis-Menten equation can be obtained by the method of least squares with the Taylor expansion for the sum of squares of the absolute residual, i.e., the difference between the observed velocity and the corresponding velocity by calculation. This method makes it possible to determine the values of Km and V not in a trial-and-error manner but in a deductive and unique manner after some iterative procedures starting from arbitrary approximate values of Km and V. These values can be said to be uniquely determined for a set of data as the finally converged values are no longer dependent upon the initial approximate values of Km and V. It is also very important to obtain initial approximate values of parameters for the application of the method described above. A simple method is proposed to estimate the approximate values of parameters involved in fractional functions. The method of rearrangement after canceling of denominator of a fractional function can be utilized to obtain approximate values, not only for cases of two unknown parameters such as the Michaelis-Menten equation, but also for cases with more than two unknowns.
米氏方程中米氏常数(Km)和最大速度(V)的最佳拟合值,可以通过对绝对残差平方和进行泰勒展开的最小二乘法来获得,即观测速度与计算得到的相应速度之间的差值。该方法使得确定Km和V的值无需反复试验,而是从Km和V的任意近似值开始经过一些迭代过程后,以演绎且唯一的方式确定。对于一组数据而言,这些值可以说是唯一确定的,因为最终收敛的值不再依赖于Km和V的初始近似值。对于上述方法的应用,获取参数的初始近似值也非常重要。本文提出了一种简单的方法来估计分数函数中参数的近似值。分数函数分母消去后的重排方法不仅可以用于获得两个未知参数(如米氏方程)情况下的近似值,还可以用于两个以上未知参数的情况。