Thermodynamics of 'hydrophobic' versus 'hydrophilic' binding in ligand-protein complexes

复杂的生物过程包括一个分子与另一个分子的结合。在某些情况下，这涉及到一种蛋白质与另一种蛋白质的结合，而在其他情况下，蛋白质结合一个小的有机分子（“配体”）。在某些情况下，例如在疾病状态下，需要发现一种比天然配体结合更紧密（即具有更高亲和力）的新型小分子。理想情况下，这种新分子或“铅”可以进一步开发为有效对抗特定疾病状态的药物分子。结合过程可以被认为是一个“形状”问题，因此结合的强度主要取决于配体和蛋白质结合袋之间的形状互补性。然而，结合过程比这更复杂，因为它也是由相互作用伙伴的动态程度（“软性”）决定的。使问题进一步复杂化的是，在相互作用中还有第三个伙伴，即溶剂水分子，所有生物相互作用都发生在其中。基于结构信息（基于结构的药物设计）的新药物分子的发现目前由于缺乏这些额外组成部分的信息而受到阻碍。由于这个原因，许多药物是通过筛选大量分离的化合物发现的，这可能非常耗时。本建议旨在量化上述各种成分对结合亲和力的贡献。最终，这可能使我们能够使用高速计算机预测蛋白质结构的结合亲和力，从而提高药物发现过程的效率。

Complex biological processes involve the binding of one molecule by another. In some cases this involves the binding of one protein by another, whereas in others the protein binds a small organic molecule ('ligand'). In certain instances, for example in a disease state, there is a need to discover a novel small molecule that binds more tightly (ie has higher affinity) than the natural ligand. Ideally, this novel molecule or 'lead', can be further developed as a drug molecule effective against the particular disease state. The binding process can be thought of as a 'shape' problem, whereby the strength of binding depends critically on shape complementarity between the ligand and the binding pocket on the protein. However, the binding process is more complicated than this, since it is also determined by the extent of dynamics ('floppiness') of the interacting partners. To complicate matters further, there is a third partner in the interaction, namely molecules of solvent water in which all biological interactions take place. The discovery of new drug molecules on the basis of structural information (structure-based drug design) is currently hampered by the lack of information on these additional component parts. For this reason many drugs are discovered by screening large numbers of discrete compounds, which can be very time-consuming. This proposal aims to quantify the contributions to binding affinity from the various components described above. Ultimately, this may enable us to predict binding affinities from protein structures using high-speed computers, thereby inproving the efficiency of the drug discovery process.