Do enthalpy and entropy distinguish first in class from best in class?
Do enthalpy and entropy distinguish first in class from best in class?
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DOI：
10.1016/j.drudis.2008.07.005
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发表时间：
2008-10
影响因子：
7.4
通讯作者：
Freire, Ernesto
中科院分区：
文献类型：
--
作者：
Freire, Ernesto
药物分子应该以高亲和力和选择性结合其靶标。由于结合亲和力是结合焓和结合熵的组合函数，因此极高的亲和力要求这两项都有利于结合。然而，众所周知，结合焓比结合熵更难优化，这一事实导致了无法实现最佳效力的化学不平衡分子。事实上，以目前的技术，候选药物的重复优化可能需要数年时间，并且只出现在第二代产品中。在这种情况下，这并不奇怪，明确纳入焓和熵之间的相互作用，并加速优化过程的结构/活性关系（SAR）正在开发和越来越受欢迎。
A drug molecule should bind to its target with high affinity and selectivity. Since the binding affinity is a combined function of the binding enthalpy and the binding entropy, extremely high affinity requires that both terms contribute favorably to binding. The binding enthalpy, however, is notoriously more difficult to optimize than the binding entropy, a fact that has resulted in thermodynamically-unbalanced molecules that do not achieve optimal potency. In fact, with current technologies, the enthalpic optimization of drug candidates may take years and only appear in second-generation products. Within that context, it is not surprising that structure/activity relationships (SAR) that explicitly incorporate the interplay between enthalpy and entropy and accelerate the optimization process are being developed and gaining popularity.
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影响因子：
2.9
作者：
Schon, Arne;Madani, Navid;Freire, Ernesto
通讯作者：
Freire, Ernesto
影响因子：
8
作者：
Sharp, K
通讯作者：
Sharp, K
影响因子：
2.9
作者：
SHARP, KA;NICHOLLS, A;HONIG, B
通讯作者：
HONIG, B
影响因子：
2.9
作者：
Ward, WHJ;Holdgate, GA;Taylor, IWF
通讯作者：
Taylor, IWF
影响因子：
2.9
作者：
LUMRY, R;RAJENDER, S
通讯作者：
RAJENDER, S