Shelley John C, Cholleti Anuradha, Frye Leah L, Greenwood Jeremy R, Timlin Mathew R, Uchimaya Makoto
Schrödinger, LLC, Portland, OR 97204, USA.
J Comput Aided Mol Des. 2007 Dec;21(12):681-91. doi: 10.1007/s10822-007-9133-z. Epub 2007 Sep 27.
Epik is a computer program for predicting pK(a) values for drug-like molecules. Epik can use this capability in combination with technology for tautomerization to adjust the protonation state of small drug-like molecules to automatically generate one or more of the most probable forms for use in further molecular modeling studies. Many medicinal chemicals can exchange protons with their environment, resulting in various ionization and tautomeric states, collectively known as protonation states. The protonation state of a drug can affect its solubility and membrane permeability. In modeling, the protonation state of a ligand will also affect which conformations are predicted for the molecule, as well as predictions for binding modes and ligand affinities based upon protein-ligand interactions. Despite the importance of the protonation state, many databases of candidate molecules used in drug development do not store reliable information on the most probable protonation states. Epik is sufficiently rapid and accurate to process large databases of drug-like molecules to provide this information. Several new technologies are employed. Extensions to the well-established Hammett and Taft approaches are used for pK(a) prediction, namely, mesomer standardization, charge cancellation, and charge spreading to make the predicted results reflect the nature of the molecule itself rather just for the particular Lewis structure used on input. In addition, a new iterative technology for generating, ranking and culling the generated protonation states is employed.
Epik是一个用于预测类药物分子pK(a)值的计算机程序。Epik可将此功能与互变异构技术相结合，以调整类药物小分子的质子化状态，从而自动生成一种或多种最可能的形式，用于进一步的分子建模研究。许多药用化学品可与其环境交换质子，从而产生各种电离和互变异构状态，统称为质子化状态。药物的质子化状态会影响其溶解度和膜通透性。在建模过程中，配体的质子化状态还会影响预测的分子构象，以及基于蛋白质-配体相互作用的结合模式和配体亲和力预测。尽管质子化状态很重要，但许多用于药物开发的候选分子数据库并未存储有关最可能质子化状态的可靠信息。Epik处理类药物分子大型数据库以提供此信息的速度足够快且准确性高。采用了几种新技术。对成熟的哈米特和塔夫脱方法进行扩展，用于pK(a)预测，即中介体标准化、电荷抵消和电荷扩散，以使预测结果反映分子本身的性质，而不仅仅针对输入时使用的特定路易斯结构。此外，还采用了一种用于生成、排序和筛选生成的质子化状态的新迭代技术。
