Computationally guided design of helical peptide interaction reagents

描述(由申请人提供)：蛋白质-蛋白质相互作用调节所有细胞过程，是治疗抑制的有吸引力的目标。这项拟议工作的长期目标是加速发现可在研究、诊断和治疗中用作蛋白质相互作用抑制剂的修饰螺旋肽。短期目标是开发新的、集成的计算和实验方法，以提供有效的和选择性的Bcl-2蛋白抑制剂。抗凋亡的Bcl-2蛋白在许多癌症中很重要，它们的过度表达抵消了细胞死亡信号。Bcl2蛋白对化疗具有抵抗力，使其成为高优先级的肿瘤学靶点。许多Bcl2蛋白相互作用涉及一个保守的结合槽，它与伴侣蛋白中约20个残基的短α螺旋相连，称为BH3螺旋。模拟BH3螺旋的合成肽可以抑制抗凋亡功能，导致细胞死亡。然而，Bcl-2家族有多个成员，并不是所有的BH3多肽都是所有Bcl-2蛋白的同样有效的抑制剂。一个重要的目标是为每个家庭成员发现高亲和力和选择性的抑制剂。另一个挑战是，工程多肽对蛋白酶高度敏感，很难穿过细胞膜，限制了它们作为试剂的用途。最近的工作表明，稳定螺旋的化学修饰可以改善它们的性能。这项提议的具体目标是围绕紧密耦合的计算和实验技术来组织的，这些技术将加深我们对什么是好的螺旋肽抑制剂的理解，并帮助我们更有效地发现有用的分子。第一步将是使用基于计算结构的方法来设计多肽，预计这些多肽将与BFL-1和BHRF1家族成员BFL-1和BHRF1紧密和选择性结合。这些信息将被用来设计专注于高优先级候选的~107个肽的组合库。文库将在酵母表面展示程序中筛选具有所需性质的分子，该程序将提供关于计算文库设计方法质量的反馈。来自酵母展示的最佳多肽将通过溶液中的生物物理测量和X射线结晶学进行进一步表征。计算模型的建立和分析将有助于确定结合亲和力和特异性的决定因素。最后，通过这些步骤得到的最好的多肽将使用化学技术进一步优化，这些技术将稳定的交联链引入螺旋。目前对于什么是好的交联改性和不好的交联改性的见解是有限的。在这项工作中，将对修饰和未修饰的多肽进行详细的分子动力学模拟，以建立我们对多肽结构改变如何影响结合的理解。总体而言，这项工作将提供针对重要癌症调节蛋白的新分子，将加快发现选择性多肽结合的新计算方法，并更好地理解螺旋-多肽相互作用的生物物理决定因素。

DESCRIPTION (provided by applicant): Protein-protein interactions regulate all cellular processes and are attractive targets for therapeutic inhibition. The long-term goal of the proposed work is to accelerate the discovery of modified helical peptides that can be used as protein-protein interaction inhibitors in research, diagnosis and therapy. The short-term goals are to develop new, integrated computational and experimental methods that will deliver potent and selective inhibitors of Bcl-2 proteins. Anti-apoptotic Bcl-2 proteins are important in many cancers, where their over- expression counteracts cell-death signaling. Bcl-2 proteins provide resistance to chemotherapy, making them high-priority oncology targets. Many Bcl-2 protein interactions involve a well-conserved binding groove that engages short alpha helices of ~20 residues, called BH3 helices, in partner proteins. Synthetic peptides that mimic BH3 helices can inhibit anti-apoptotic function and lead to cell death. However, there are multiple members of the Bcl-2 family, and not all BH3 peptides are equally effective inhibitors of all Bcl-2 proteins. An important goal is to discover high-affinity and selective inhibitors for each family member. Another challenge is that engineered peptides are highly susceptible to proteases and have trouble crossing cell membranes, limiting their utility as reagents. Recent work has shown that chemical modifications that stabilize helices can improve their properties. The specific aims of this proposal are organized around tightly coupled computational and experimental techniques that will deepen our understanding of what makes a good helical-peptide inhibitor and help us discover useful molecules more efficiently. The first step will be to use computational structure- based methods to design peptides predicted to bind tightly and selectively to Bcl-2 family members Bfl-1 and BHRF1. This information will be used to design combinatorial libraries of ~107 peptides focused on high-priority candidates. Libraries will be screened for molecules with desired properties in a yeast-surface display procedure that will provide feedback about the quality of the computational library design methods. The best peptides from yeast display will be further characterized using biophysical measurements in solution and x-ray crystallography. Computational model building and analysis will help establish determinants of binding affinity and specificity. Finally, the best peptides resulting from these procedures will be further optimized using chemical techniques that introduce stabilizing crosslinks into helices. Current insights into what makes good vs. poor crosslinking modifications are limited. In this work, detailed molecular dynamics simulations of modified and unmodified peptides will be carried out to build our understanding of how altered peptide structure affects binding. Overall, this work wil deliver new molecules that target important cancer-regulating proteins, new computational methods that will speed the discovery of selective peptide binders, and a better understanding of the biophysical determinants of helical-peptide interactions.