Enzyme-Based Platform Technology for Cancers Utilizing PAM: Etiology of Novel Ami

 描述(申请人提供)：大约50%的哺乳动物生物活性多肽需要C-末端的-酰胺部分才能具有全部的生物活性。这种翻译后修饰需要双功能PAM的PHM和PAL结构域的顺序酶反应。PAM对多肽酰胺化的失调，无论是过度表达还是损伤，都是有问题的。在许多癌症中观察到PAM的上调，其中酰胺化的多肽激素作为促进肿瘤生长的自分泌和/或旁分泌生长因子。该提案选择雄激素非依赖性前列腺癌(AI CAP)作为概念验证研究，以开发一种平台技术，旨在利用PAM进行进展的癌症的合理治疗靶向和早期检测方案。晚期CAP的现代治疗方法是雄激素消融疗法。治疗荷尔蒙剥夺后，前列腺中的细胞分化，增加了神经内分泌种群(其中包含PAM)。前列腺癌(CAP)对雄激素非依赖性(AI)生长的选择与酰胺化神经肽激素的产生密切相关。我们认为PAM/PHM是一个很好的治疗靶点，因为它是已知的唯一与多肽酰胺化相关的酶。我们的研究平台寻求支持，以开发通过结合稳态和瞬变动力学的KIE来绘制TS几何图形的实验工具。利用量子计算方法，将选择化学稳定的类似物，将分子静电势(MEP)图与已知化合物的数据库相匹配。通过结合机械酶学和计算机辅助药物设计的方法来建立治疗发现的路线图，将对那些研究大量PAM依赖的癌症的人来说是有价值的。此外，我们的研究团队将使用AI帽细胞系的多肽图谱来分离和表征新的酰胺化多肽激素，作为早期检测和提高治疗效果的生物标记物(见上文)。随后的体外喂养研究将确定哪种酰胺化多肽激素(S)介导了肿瘤的增殖。识别与肿瘤增殖相关的有效生物标志物的深远目标将是设计一种强有力的检测方法，用于早期诊断和预防恶性疾病。

 DESCRIPTION (provided by applicant): Approximately 50% of all mammalian bioactive peptides require a C-terminal -amide moiety for full biological activity. This post-translationa modification requires the sequential enzyme reactions of PHM and PAL domains of bifunctional PAM. Dysregulated peptide amidation by PAM, either overexpression or impairment, is problematic. The upregulation of PAM is observed in a number of cancers, where the amidated peptide hormones serve as autocrine and/or paracrine growth factors facilitating tumor growth. This proposal has selected androgen independent prostate cancer (AI CaP) as a proof-of-concept study to development a platform technology directed towards the rational therapeutic targeting and early detection protocols of cancers that utilize PAM for progression. The contemporary treatment for late stage CaP is an androgen-ablative therapy. Following therapeutic hormone deprivation, cells in the prostate differentiate, increasing the neuroendocrine populations (which contain PAM). Selection towards the androgen-independent (AI) growth of prostate cancer (CaP) is strongly correlated with -amidated neuropeptide hormone production. We contend that PAM/PHM is an excellent therapeutic target as it is the only known enzyme associated with peptide amidation. Our research platform seeks support to develop the experimental tools to map the TS geometry through a combination of KIEs with steady and transient state kinetics. With quantum computational approaches, chemically stable analogues will be selected matching the molecular electrostatic potential (MEP) maps to databases of known compounds. Establishing a roadmap towards therapeutic discovery by combining the approach of mechanistic enzymology and computer aided drug design will be valuable to those studying the numerous PAM-dependent cancers. In addition, our research team will use peptidomic profiling of AI CaP cell lines to isolate and characterize novel -amidated peptide hormones to serve as biomarkers for early detection and improve therapeutic efficacy (vide supra). Subsequent in vitro feeding studies will identify which amidated peptide hormone(s) mediate tumor proliferation. The far reaching goal of identifying potent biomarkers associated with tumor proliferation will be the design of a robust assay for the early diagnosis and prevention of malignant disease.