Computationally guided design of helical peptide interaction reagents

螺旋肽相互作用试剂的计算指导设计

基本信息

批准号：
8668226
负责人：
AMY E KEATING
金额：
$ 32.49万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-06-01 至 2018-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8668226
关键词：
Academia Address Affect Affinity Apoptotic BCL-2 Protein BCL2 gene BCL2A1 protein BH3 peptide Basic Science Binding Biology Biotechnology Cell Death Cell Death Signaling Process Cell membrane Cell physiology Cells Chemicals Chemistry Complex Computer Analysis Computer Simulation Computing Methodologies Coupled Crosslinker Crystallography Data Diagnosis Disease Elements Engineering Epitopes Event Family Family member Feedback Future Goals Human Human herpesvirus 4 BHRF1 protein Individual Industry Lead Libraries Malignant Neoplasms Methods Modification Molecular Outcome Peptide Hydrolases Peptide Library Peptides Permeability Pharmacologic Substance Procedures Property Protein Binding Protein Engineering Protein Family Proteins Protocols documentation Reagent Research Resistance Resolution Scheme Solutions Specificity Speed Structure Surface System Techniques Technology Testing Therapeutic Work Yeasts alpha helix base biophysical properties cancer cell chemotherapy combinatorial computerized tools crosslink design drug discovery experience improved inhibitor/antagonist insight member model development molecular dynamics novel oncology outcome forecast paralogous gene peptide structure pro-apoptotic protein programs protein protein interaction protein-histidine kinase public health relevance research study screening simulation small molecule success synthetic peptide therapeutic protein therapeutic target tool transcription factor

项目摘要

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.

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，并且是治疗性抑制的有吸引力的靶标。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-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、选择性的 Bcl-2 蛋白抑制剂。抗凋亡 Bcl-2 蛋白在许多癌症中很重要，它们的过度表达会抵消细胞死亡信号。 Bcl-2 蛋白对化疗具有抵抗力，使其成为高度优先的肿瘤学靶标。许多 Bcl-2 蛋白相互作用涉及一个高度保守的结合槽，该结合槽与伴侣蛋白中约 20 个残基的短 α 螺旋（称为 BH3 螺旋）接合。模拟 BH3 螺旋的合成肽可以抑制抗凋亡功能并导致细胞死亡。然而，Bcl-2 家族有多个成员，并非所有 BH3 肽都是所有 Bcl-2 蛋白同样有效的抑制剂。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。另一个挑战是工程肽对蛋白酶高度敏感，并且难以穿过细胞膜，限制了它们作为试剂的用途。最近的研究表明，稳定螺旋的化学修饰可以改善其特性。该提案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良好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。第一步是使用基于计算结构的方法来设计预计能与 Bcl-2 家族成员 Bfl-1 和 BHRF1 紧密且选择性结合的肽。该信息将用于设计约 107 种肽的组合文库，重点关注高优先级候选肽。将在酵母表面展示程序中筛选文库中具有所需特性的分子，这将提供有关计算文库设计方法质量的反馈。来自酵母展示的最佳肽将通过溶液中的生物物理测量和 X 射线晶体学来进一步表征。计算模型的构建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，这些程序产生的最佳肽将使用化学技术进一步优化，将稳定的交联引入螺旋中。目前对交联修饰的优劣的认识还很有限。在这项工作中，将对修饰和未修饰的肽进行详细的分子动力学模拟，以加深我们对改变的肽结构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、加速选择性肽结合物发现的新计算方法，以及更好地理解螺旋-肽相互作用的生物物理决定因素。