PICORNAVIRAL PROCESSING PROTEINASES

我们的长期目标是开发有效和有选择性的 小核糖核酸病毒加工酶的抑制剂， 抗病毒治疗 为了实现这一目标，我们将研究催化和约束 人甲型肝炎病毒3C半胱氨酸蛋白酶的性质 鼻病毒2型和14型以及人脊髓灰质炎病毒。 协作组， 由Protos的布鲁斯马尔科姆领导， 肝炎酶 我们已经研究了各种潜在的肽亚- 并开发了快速、定量的检测方法。 我们现在准备 通过改进被识别的肽结构来扩展我们的研究。 这种酶，通过开发新的检测方法的基础上敏感 荧光方法，并通过构建基于 肽结构。 我们将利用所有这些方法， 分析底物和抑制剂与肝炎病毒的相互作用 酵素 由于肝炎酶在手，它将作为我们最初的 目标 然而，我们将继续研究与之密切相关的鼻病毒， 脊髓灰质炎病毒的酶通过相同的方法。 我们预计每个系统 将为选择性抑制剂的设计提供新的见解。 人半胱氨酸蛋白酶存在于大肠杆菌的溶酶体区室中， 大多数人类细胞，组织蛋白酶B、H和L，将用于研究 针对小核糖核酸病毒设计的化合物的特异性 蛋白酶 将提供酶和第一代抑制剂样品 一个结晶学合作小组 由此产生的数据 在进一步的努力中，将利用这种方法来设计新的生物反应器 以提高选择性。

Our long term objective is to develop potent and selective inhibitors of the picornaviral processing enzymes that may be of value in antiviral therapy. To achieve this goal, we will study the catalytic and binding properties of the 3C cysteine proteinases of hepatitis A virus, human rhinovirus types 2 and 14 and human poliovirus. The collaborating group, led by Bruce Malcolm at Protos, has expressed large quantities of the hepatitis enzyme. We have examined a variety of potential peptide sub- strates and developed rapid, quantitative assays. We are now poised to expand our study by refining the peptide structure that is recognized by this enzyme, by developing new assay methods based on sensitive fluorescence methods, and by constructing potential inhibitors based on peptide structures. We will utilize all these methods to thoroughly analyze the interaction of substrates and inhibitors with the Hepatitis enzyme. As the hepatitis enzyme is in hand, it will serves as our initial target. However, we will pursue the closely related rhinovirus and poliovirus enzymes by the same approach. We anticipate that each system will provide new insights into selective inhibitors design. The human cysteine proteinases found in the lysosomal compartment of most human cells, cathepsins B,H, and L, will be utilized in studies for the specificity of compounds designed against the picornaviral proteinases. Samples of enzymes and first-generation inhibitor will be provided to a collaborating crystallography group. Data arising from this approach will be utilized to design newer inhibiotrs in a further effort to improve the selectivity.