Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Chemistry, Boston University, Boston, MA 02215, USA.
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA; Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.
Curr Opin Struct Biol. 2022 Aug;75:102396. doi: 10.1016/j.sbi.2022.102396. Epub 2022 May 27.
An increasing number of medically important proteins are challenging drug targets because their binding sites are too shallow or too polar, are cryptic and thus not detectable without a bound ligand or located in a protein-protein interface. While such proteins may not bind druglike small molecules with sufficiently high affinity, they are frequently druggable using novel therapeutic modalities. The need for such modalities can be determined by experimental or computational fragment based methods. Computational mapping by mixed solvent molecular dynamics simulations or the FTMap server can be used to determine binding hot spots. The strength and location of the hot spots provide very useful information for selecting potentially successful approaches to drug discovery.
越来越多具有医学重要性的蛋白质成为了具有挑战性的药物靶点,因为它们的结合部位过于浅或极性过大,是隐匿的,如果没有结合配体,则无法检测到,或者位于蛋白质-蛋白质界面中。虽然这些蛋白质与类似药物的小分子结合的亲和力可能不够高,但它们通常可以通过新型治疗方式进行药物治疗。可以通过实验或计算基于片段的方法来确定是否需要这些方式。通过混合溶剂分子动力学模拟或 FTMap 服务器进行计算映射,可以用于确定结合热点。热点的强度和位置为选择潜在成功的药物发现方法提供了非常有用的信息。