The resulting pel lets were resuspended in a minimal volume of sucrose buffer a

Often graphic methods are used to give insight, MAPK 活性化 for example dotting a kinome tree, heat maps, or a radius plot, but such methods only allow qualitative comparison of a limited set of com pounds at a time. To make quantitative selectivity comparisons, three notable methods have been proposed. The first is the selectivity score, which simply divides the number of kinases hit at an arbitrary Kd or IC50 value by the number of kinases tested, Figure 1a. A related score is S, which divides the number of kinases hit at 10 times the Kd of the target by the number of kinases tested. The dis advantage of both methods is that 3 uM, or the factor 10, is an arbitrary cut off value. For example, take two inhibitors, one that binds to two kinases with Kds of 1 nM and 1 uM, and another with Kds of 1 nM and 1 nM.

Both are ranked equally specific by both S and S, whereas the first compound is clearly more specific. A less arbitrary parameter for selectivity is the Gini score. This uses % inhibition data at a single inhibi tor concentration. These data are rank ordered, summed and normalized to arrive at a cumulative fraction inhibition MK-1775 plot, after which the score is calcu lated by the relative area outside the curve. Though this solves the problem with the selectivity score, it leaves other disadvantages. One is that the Gini score has no conceptual or thermodynamic meaning such as a Kd value has. Another is that it performs sub optimally with smaller profiling panels. In addition, the use of % inhibition data makes the value more dependent on experimental conditions than a Kd based score.

For instance, profiling with 1 uM inhibitor concentration results in higher percentages inhibition than using 0. 1 uM of inhibitor. The 1 uM test therefore yields a more promiscuous Gini value, requiring the arbitrary 1 uM to be mentioned when MS-275 HDAC 阻害剤 calculating Gini scores. The same goes for concentrations of ATP or other co factors. This is confusing and limits compari sons across profiles. A recently proposed method is the partition index. This selects a reference kinase, and calculates the fraction of inhibitor molecules that would bind this kinase, in an imaginary pool of all panel kinases. The partition index is a Kd based score with a thermodynamical underpinning, and performs well when test panels are smaller.

However, this score is still not ideal, since it doesnt characterize the complete inhibitor distribu tion in the imaginary kinase mixture, but just the frac tion bound to the reference enzyme. Consider two inhibitors, A binds to 11 kinases, one with a Kd of 1 nM and ten others at 10 nM. Inhibitor B binds to 2 kinases, seen as containing more information about which active site to bind than a promiscuous inhibitor. The selectivity difference between the inhibitors can therefore be quan tified by information entropy. The distribution of a compound across energy states is given by the Boltzmann formula, both with Kds of 1 nM. The partition index would score the second is intuitively more specific. Another down side is the necessary choice of a reference kinase.