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Specificity of Molecular Fragments Binding to S100B versus S100A1 as Identified by NMR and Site Identification by Ligand Competitive Saturation (SILCS)

机译:由NMR和配体竞争饱和饱和度(Silcs)鉴定的分子片段与S100a1结合的分子片段与S100A1的特异性

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摘要

S100B, a biomarker of malignant melanoma, interacts with the p53 protein and diminishes its tumor suppressor function, which makes this S100 family member a promising therapeutic target for treating malignant melanoma. However, it is a challenge to design inhibitors that are specific for S100B in melanoma versus other S100-family members that are important for normal cellular activities. For example, S100A1 is most similar in sequence and structure to S100B, and this S100 protein is important for normal skeletal and cardiac muscle function. Therefore, a combination of NMR and computer aided drug design (CADD) was used to initiate the design of specific S100B inhibitors. Fragment-based screening by NMR, also termed “SAR by NMR,” is a well-established method, and was used to examine spectral perturbations in 2D [1H, 15N]-HSQC spectra of Ca2+-bound S100B and Ca2+-bound S100A1, side-by-side, and under identical conditions for comparison. Of the 1000 compounds screened, two were found to be specific for binding Ca2+-bound S100A1 and four were found to be specific for Ca2+-bound S100B, respectively. The NMR spectral perturbations observed in these six data sets were then used to model how each of these small molecule fragments showed specificity for one S100 versus the other using a CADD approach termed Site Identification by Ligand Competitive Saturation (SILCS). In summary, the combination of NMR and computational approaches provided insight into how S100A1 versus S100B bind small molecules specifically, which will enable improved drug design efforts to inhibit elevated S100B in melanoma. Such a fragment-based approach can be used generally to initiate the design of specific inhibitors for other highly homologous drug targets.
机译:S100B是恶性黑素瘤的生物标志物,与P53蛋白相互作用,并减少其肿瘤抑制功能,使得该S100家族成员是治疗恶性黑素瘤的有希望的治疗靶标。然而,对黑色素瘤中S100b特异性特异性的抑制剂具有挑战,而其他S100家族成员对正常细胞活性很重要。例如,S100A1的顺序和结构与S100B最相似,并且该S100蛋白对正常骨骼和心肌功能非常重要。因此,使用NMR和计算机辅助药物设计(CADD)的组合来启动特异性S100B抑制剂的设计。通过NMR基于片段的筛选,也称为“SAR通过NMR”是一种良好的方法,用于检查CA2 + -Bound S100B和CA2 + -Bound S100A1的2D [1H,15N] -HSQC光谱中的光谱扰动。并排,在相同的条件下进行比较。在筛选的1000个化合物中,发现两种具有结合Ca 2 + -Bound S100A1的特异性,发现四个是Ca2 + -Bound S100b的特异性。然后使用在这六种数据集中观察到的NMR光谱扰动来模拟这些小分子片段中的每一个如何表达一个S100与另一个使用CADD方法通过配体竞争饱和饱和度(SILC)称为位点鉴定的特异性。总之,NMR和计算方法的组合提供了对S100A1与S100B的关系的洞察力,具体地结合小分子,这将使改善的药物设计努力抑制黑色素瘤中的升高的S100B。通常可以使用这种基于片段的方法来启动特异性抑制剂的设计,用于其他高度同源的药物靶标。

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