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：
9247955
负责人：
AMY E KEATING
金额：
$ 29.44万
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 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9247955
关键词：
Academia Address Affect Affinity Apoptotic BCL-2 Protein BCL2 gene BH3 peptide Basic Science Binding Binding Proteins Biology Biophysics Biotechnology Cell Death Cell Death Signaling Process Cell membrane Cell physiology Cells Chemicals Chemistry Complex Computer Analysis Computer Simulation Computing Methodologies Coupled Crosslinker Data Diagnosis Disease Elements Engineering Epitopes Event Family Family member Feedback Future Goals Human Human Herpesvirus 4 Individual Industry Lead Libraries Malignant Neoplasms Methods Modification Molecular Molecular Analysis Mutation Analysis Outcome Peptide Hydrolases Peptide Library Peptides Permeability Pharmacologic Substance Procedures Property Protein Engineering Protein Family Proteins Protocols documentation Reagent Research Resistance Resolution Scheme Specificity Speed Structure Surface System Techniques Technology Testing Therapeutic Viral Proteins Work X-Ray Crystallography Yeasts alpha helix base biophysical properties cancer cell chemotherapy combinatorial computerized tools crosslink design drug discovery experience experimental study improved inhibitor/antagonist insight member model building model development molecular dynamics novel oncology outcome forecast overexpression paralogous gene peptide structure peptidomimetics pro-apoptotic protein programs protein protein interaction protein-histidine kinase public health relevance screening simulation small molecule small molecule inhibitor success synthetic peptide targeted treatment therapeutic candidate 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，并且是治疗抑制的有吸引力的靶标。拟议工作的长期目标是加速发现改良的螺旋肽，这些肽可以用作研究，诊断和治疗中的蛋白质蛋白相互作用抑制剂。短期目标是开发新的，集成的计算和实验方法，这些方法将提供Bcl-2蛋白的有效抑制剂。抗凋亡的Bcl-2蛋白在许多癌症中很重要，在许多癌症中，它们的过度表达抵消了细胞死亡信号。 Bcl-2蛋白提供了对化疗的耐药性，使其成为高优先肿瘤学靶标。许多Bcl-2蛋白相互作用都涉及一个保存良好的结合凹槽，该凹槽在伴侣蛋白中涉及约20个残基的短α螺旋，称为BH3螺旋。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。但是，Bcl-2家族中有多个成员，并且并非所有BH3肽都是所有Bcl-2蛋白的同等有效抑制剂。一个重要的目标是发现每个家庭成员的高亲和力和选择性抑制剂。另一个挑战是，工程肽非常容易受到蛋白酶的影响，并且难以穿越细胞膜，从而限制了它们作为试剂的效用。最近的工作表明，稳定螺旋的化学修饰可以改善其性能。该提案的具体目的是围绕紧密耦合的计算和实验技术组织的，这将加深我们对使良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。第一步是使用基于计算结构的方法设计被预测的肽与Bcl-2家族成员BFL-1和BHRF1的紧密结合。该信息将用于设计约107个肽的组合库，这些肽集中在高优先级候选方面。库将在酵母表面显示过程中筛选具有所需特性的分子，该过程将提供有关计算库设计方法质量的反馈。使用溶液和X射线晶体学中的生物物理测量结果，将进一步表征酵母显示的最佳肽。计算模型构建和分析将有助于建立结合亲和力和特异性的决定因素。最后，将使用化学技术进一步优化这些过程产生的最佳肽，这些化学技术将稳定的交联链接到螺旋中。当前对使良好与差的交联修改的见解是有限的。在这项工作中，将进行修改和未修饰肽的详细分子动力学模拟，以建立我们对改变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的癌症调节蛋白的新分子，将加快选择性肽粘合剂发现的新计算方法，以及对螺旋肽相互作用的生物物理决定因素的更好理解。