药物结构优化中如何设置活性期望值
本帖最后由 dejunchem 于 2013-8-23 11:17 编辑Setting expectations in molecular optimizations: strengths and limitations of commonly used composite parameters
AbstractOver the past 15 years there have been extensive efforts to understand and reduce the high attrition rates of drug candidates with an increased focus on physicochemical properties. The fruits of this labor have been the generation of numerous efficiency indices, metric-based rules and visualization tools to help guide medicinal chemists in the design of new compounds with more favorable properties. This deluge of information may have had the unintended consequence of further obfuscating molecular optimizations by the inability of these scoring functions, rules and guides to reach a consensus on when a particular transformation is identified as beneficial. In this manuscript, several composite parameters, or efficiency indices, are examined utilizing theoretical and experimental matched molecular pair analyses in order to understand the basis for how each will perform under varying scenarios of molecular optimizations. In contrast to empirically derived composite parameters based on heavy atom count, lipophilic efficiency (LipE) sets consistent expectations regardless of molecular weight or relative potency and can be used to generate consistent expectations for any matched molecular pair.
药化出身的同学对配体效率（ligand efficiency, LE）和亲脂性效率（lipophilic efficiency, LipE）肯定不会陌生，这大概是继Lipinski规则后最重要的两个概念了。8月13日，诺华的资深药物化学研究员（组长）Michael D. Shultz发表了一篇paper（Bioorg Med Chem Lett. 2013, doi: 10.1016/j.bmcl.2013.08.029.），分析药物设计中各种参数的局限性。
文章第一段罗列了从分子量、亲脂性、Pka、分子体积、极性表面积等初级参数到LE、LipE、LELP、SILE等高级参数，总共大约有40种，都标有参考文献，值得收藏备用。作者引用了Lazebnik Y的一句话“sometimes the more facts we learn, the less we understand”，真是让人感概万千。
在高级参数中，最著名的毫无疑问是LE、LipE、LELP三个，公式如下：
LE=ΔG/HAC=-RTInKd/HAC≈1.37pIC50/HAC
LipE=pIC50-cLogP
LELP= cLogP/LE=/1.37pIC50
LE只考虑重原子数（heavy atom count, HAC），LipE只考虑亲脂性，LELP则同时考虑重原子数和亲脂性。
Michael D. Shultz认为将重原子数与化合物活性联系起来有很大的局限性，他作了一个简单有趣的比喻：体重指数（BMI=体重/身高^2）常用于评估人体肥胖程度，但遇到练健身的人就会失真，因为BMI将肌肉当做脂肪计算在内；同理，LE也无法区分化合物的肌肉与脂肪，拿这个参数去决定是否给化合物减肥没有意义。
LELP同时考虑重原子数和亲脂性，看似很完美却也有问题，LogP的权重太大：对于高LogP的化合物，活性稍有增加就会引起LELP的急剧下降；而对于低LogP的化合物，生物活性即便很低，LELP也高不到哪去。
LipE应该是三个参数中最靠谱的，完全抛弃分子量对活性的影响，只考虑化合物的亲脂性。如果要维持LipE值不变（结构修饰有意义，增加的基团是肌肉而不是脂肪），将H替换为叔丁基必须产生50倍的活性才行，而如果引入亲水性基团，即便活性下降也是可以接受的，因为你可以在其他地方引入亲脂性结构将活性补回来。
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sometimes the more facts we learn, the less we understand 真的是深有感触啊 有种历经沧桑的感觉 太经典了。收藏！
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