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

复杂的生物过程涉及一个分子与另一个分子的结合。在某些情况下，这涉及一种蛋白质与另一种蛋白质的结合，而在另一些情况下，蛋白质结合的是一个小的有机分子(“配体”)。在某些情况下，例如在疾病状态下，需要发现一种新的小分子，它比天然配体结合得更紧密(即亲和力更高)。理想情况下，这种新型分子或“铅”可以进一步发展成为一种对特定疾病状态有效的药物分子。结合过程可以被认为是一个“形状”问题，因此结合的强度关键取决于配体和蛋白质上的结合口袋之间的形状互补。然而，结合过程要比这复杂得多，因为它还取决于相互作用伙伴的动态程度(软性)。使情况更加复杂的是，在相互作用中还有第三个伙伴，即所有生物相互作用都发生在其中的溶剂水分子。基于结构信息的新药分子的发现(基于结构的药物设计)目前由于缺乏关于这些额外组成部分的信息而受到阻碍。出于这个原因，许多药物是通过筛选大量离散的化合物来发现的，这可能非常耗时。该提案旨在量化上述各组成部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从蛋白质结构预测结合亲和力，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.