Ivetac Anthony, McCammon J Andrew
Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA, USA.
Methods Mol Biol. 2012;819:3-12. doi: 10.1007/978-1-61779-465-0_1.
An expanding repertoire of "allosteric" drugs is revealing that structure-based drug design (SBDD) is not restricted to the "active site" of the target protein. Such compounds have been shown to bind distant regions of the protein topography, potentially providing higher levels of target specificity, reduced toxicity and access to new regions of chemical space. Unfortunately, the location of such allosteric pockets is not obvious in the absence of a bound crystal structure and the ability to predict their presence would be useful in the discovery of novel therapies. Here, we describe a method for the prediction of "druggable" binding sites that takes protein flexibility into account through the use of molecular dynamics (MD) simulation. By using a dynamic representation of the target, we are able to sample multiple protein conformations that may expose new drug-binding surfaces. We perform a fragment-based mapping analysis of individual structures in the MD ensemble using the FTMAP algorithm and then rank the most prolific probe-binding protein residues to determine potential "hot-spots" for further examination. This approach has recently been applied to a pair of human G-protein-coupled receptors (GPCRs), resulting in the detection of five potential allosteric sites.
越来越多的“变构”药物表明，基于结构的药物设计（SBDD）并不局限于靶蛋白的“活性位点”。这类化合物已被证明可结合蛋白质表面形貌的远处区域，可能提供更高水平的靶点特异性、更低的毒性，并能进入化学空间的新区域。不幸的是，在没有结合晶体结构的情况下，此类变构口袋的位置并不明显，而预测它们的存在对于发现新疗法将很有帮助。在此，我们描述了一种预测“可成药”结合位点的方法，该方法通过使用分子动力学（MD）模拟来考虑蛋白质的灵活性。通过使用靶标的动态表示，我们能够对多个可能暴露新药物结合表面的蛋白质构象进行采样。我们使用FTMAP算法对MD系综中的单个结构进行基于片段的映射分析，然后对最多产的探针结合蛋白残基进行排名，以确定潜在的“热点”以便进一步研究。这种方法最近已应用于一对人类G蛋白偶联受体（GPCR），结果检测到了五个潜在的变构位点。
