Edwards David A
Department of Mathematical Sciences, University of Delaware, Newark, DE 19716-2553, USA.
J Math Biol. 2004 Sep;49(3):272-92. doi: 10.1007/s00285-004-0270-x. Epub 2004 Apr 23.
When estimating rate constants using the BIAcore surface plasmon resonance (SPR) biosensor, one must have an accurate mathematical model to interpret sensogram data. Several models of differing complexity are discussed, including the effective rate constant (ERC) approach. This model can be shown formally to be good within O(Da) in the limit of small Damköhler number Da, which is the ratio of the reaction rate to the rate of transport to the surface. Numerical results are presented that show that except for very slow reactions, parameter estimates from the ERC model are very close to those estimated using a more complicated model. The BIAcore measures the behavior of an evanescent wave whose signal strength decays as it penetrates into the device. It is shown that this decay does not appreciably affect the sensogram readout at low Da, but at moderate Da can lead to situations where two vastly different rate constants can produce the same short-time sensogram data.
使用BIAcore表面等离子体共振(SPR)生物传感器估算速率常数时,必须有一个准确的数学模型来解释传感图数据。文中讨论了几种不同复杂度的模型,包括有效速率常数(ERC)方法。在小达姆科勒数Da(即反应速率与向表面传输速率之比)的极限情况下,该模型在O(Da)范围内形式上是良好的。给出的数值结果表明,除了非常缓慢的反应外,ERC模型的参数估计值与使用更复杂模型估计的值非常接近。BIAcore测量倏逝波的行为,其信号强度在穿透设备时会衰减。结果表明,在低Da时,这种衰减不会明显影响传感图读数,但在中等Da时,可能会出现两种截然不同的速率常数产生相同短时传感图数据的情况。