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Interdisciplinary protein engineering approach to design high affinity antibodies for flaviviruses

跨学科蛋白质工程方法设计黄病毒高亲和力抗体

基本信息

批准号：
10507763
负责人：
Andras Fiser
金额：
$ 41.75万
依托单位：
ALBERT EINSTEIN COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-11-15 至 2024-10-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10507763
关键词：
Address Algorithms Alphavirus Amino Acids Animals Antibiotics Antibodies Antibody Affinity Antibody Therapy Antigen-Antibody Complex Antigens Autoimmune Diseases B cell repertoire Beds Communicable Diseases Cross Reactions Cytomegalovirus Dengue Virus Development Disease Ebola Effectiveness Engineering Evaluation FDA approved Family Filovirus Flavivirus Generations Goals HIV HIV-1 Homology Modeling Human Immunization Immunotherapeutic agent Infection Infectious Agent Influenza Libraries Lymphocyte Malignant Neoplasms Medical Methods Modality Monoclonal Antibodies Mutation Peptides Phage Display Phase I Clinical Trials Phase II Clinical Trials Positioning Attribute Protein Engineering Proteins Rabies Randomized Recombinants Sampling Serotyping Structural Models Structure Technology Testing Therapeutic Variant Viral Viral Hemorrhagic Fevers Virus Virus Diseases ZIKA Zika Virus antibody engineering combinatorial cross reactivity design experimental study fighting human disease interdisciplinary approach interfacial member molecular dynamics mutant neutralizing antibody novel pathogen pharmacophore preference response screening

项目摘要

Abstract Recombinant monoclonal antibodies considered a new modality of therapeutic treatment to fight viral infections. A particular challenge for viral mAb development is the isolation and characterization of mAbs with broadly neutralizing activity (bNAbs) against multiple members of a single viral family to provide an immunotherapeutic advantage, particularly for infectious agents whose cases can progress rapidly toward serious disease. Our goal for the identification of bNAbs is protein engineering by a synergistic combination of computational and experimental methods, to enhance the breadth and potency of a specific mAb using designed mutations. Phage display provides an efficient way to randomly explore up to 1010 unique library members simultaneously. However, a typical antibody-antigen interface of ~15 residues present a combinatorial possibility of 2015 mutational variants, only a fraction of which can be sampled. As a result, phage display and other antibody combinatorial methods are reliant on restriction of either amino acid diversity or interfacial positions, which limits the effectiveness of the approach. To circumvent this limitation, we propose to develop an interdisciplinary approach where computationally designed, residue-based pharmacophore descriptions of the antibody-antigen interface are used to direct the library design in subsequent phage display experiments. As a test bed for this method, we will engineer novel bNAbs against flaviviruses, which include the globally important pathogens dengue virus and Zika virus.

摘要重组单克隆抗体被认为是抗病毒治疗的新方式感染.病毒mAb开发的一个特别挑战是mAb的分离和表征，针对单个病毒家族的多个成员的广泛中和活性（bNAb），以提供免疫优势，特别是对于感染性病原体，其病例可迅速进展为严重的疾病。我们鉴定bNAb的目标是通过以下协同组合进行蛋白质工程：计算和实验方法，以提高特异性mAb的广度和效力，设计突变噬菌体展示提供了一种有效的方法来随机探索多达1010个独特的文库会员同时然而，典型的约15个残基的抗体-抗原界面呈现一个 2015突变变体的组合可能性，只有一小部分可以被采样。因此，噬菌体展示和其它抗体组合方法依赖于氨基酸多样性的限制，界面位置，这限制了该方法的有效性。为避免这项限制，我们建议开发一种跨学科的方法，抗体-抗原界面的描述用于指导随后噬菌体展示中的文库设计实验作为这种方法的试验平台，我们将设计针对黄病毒的新型bNAbs，其中包括全球重要病原体登革热病毒和寨卡病毒。

项目成果

期刊论文数量（18）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Redesigning HVEM Interface for Selective Binding to LIGHT, BTLA, and CD160.

DOI：
10.1016/j.str.2020.07.013
发表时间：
2020-11-03
期刊：
Structure (London, England : 1993)
影响因子：
0
作者：
Shrestha R;Garrett-Thomson SC;Liu W;Almo SC;Fiser A
通讯作者：
Fiser A

Subventricular zone adult mouse neural stem cells require insulin receptor for self-renewal.

DOI：
10.1016/j.stemcr.2022.04.007
发表时间：
2022-06-14
期刊：
STEM CELL REPORTS
影响因子：
5.9
作者：
Chidambaram, Shravanthi;Velloso, Fernando J.;Rothbard, Deborah E.;Deshpande, Kaivalya;Cajuste, Yvelande;Snyder, Kristin M.;Fajardo, Eduardo;Fiser, Andras;Tapinos, Nikos;Levison, Steven W.;Wood, Teresa L.
通讯作者：
Wood, Teresa L.

Integrated structure-based protein interface prediction.