Structural bioinformatics software for epitope selection and antibody engineering

用于表位选择和抗体工程的结构生物信息学软件

基本信息

  • 批准号:
    8251785
  • 负责人:
  • 金额:
    $ 15.67万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-05-15 至 2013-12-15
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Human health has benefited tremendously from the therapeutic application of monoclonal antibodies (mAb), treating painful and devastating diseases such as rheumatoid arthritis and cancer, among others. However, mAb development is a laborious and time consuming process. The health benefits gained from faster mAb development are clear, creating a great need for tools to guide scientists toward discovering the most promising antigenic targets-particularly with regard to B-cell epitopes (the part of an antigen recognized by an antibody). The critical barrier to progress in this domain is the inability to deduce the conformational characteristics of protein sequence in the absence of known structure for predicting linear B-cell epitopes-the largest, most diverse, and pharmaceutically valuable class of known epitopes. The general criticism of existing prediction methods is that they are inaccurate and do not address the conformational nature of B-cell epitopes. DNASTAR proposes to create a software pipeline that guides the prediction of B-cell epitopes, models the dynamic structural interface between a monoclonal antibody and its experimentally identified antigen, and screens in silico site-directed mutations to engineer more potent antibodies with enhanced binding affinity. The Phase I goal is to improve the prediction of antigenic peptides from target protein sequences and experimental or predicted structures. Toward this goal, DNASTAR has established collaborations with experts in monoclonal antibody production, 3D structure prediction, and protein structure and dynamics, including access to their experimental methods, data, and software tools. Our predictive models will benefit from three key innovations: 1) a superior data set and professional insights into monoclonal antibody production, 2) the introduction of state of the art 3D structure prediction for training our epitope predictors, and 3) the first use of structure-based protein dynamics in B-cell epitope prediction. At the conclusion of Phase I, we will deliver an enhanced sequence-only B-cell epitope prediction model when compared to current top prediction methods (Aim 1) and a superior sequence and structure-based epitope prediction model using 3D structure prediction and protein dynamics (Aim 2). In creating these models, we will account for the chemical and physical properties of a protein sequence and the biophysics that mediate protein-protein interactions, including solvent accessibility, hydrogen bonding, residue flexibility, binding nuclei, and geometric contours of the molecular surface. The proposed software pipeline will be built upon Protean 3D, our new molecular structure and simulation viewer, and will elevate the technical capability of a broad range of experimental scientists to estimate key antigenic structural properties from proteins without known structure-all on their desktop computer. Upon achieving these aims, scientists will recognize that it is no longer adequate to describe B-cell epitopes using amino acid frequencies or propensity scales alone. PUBLIC HEALTH RELEVANCE: Monoclonal antibodies are invaluable tools for diagnosing and treating human diseases. Unfortunately, the experimental methods used today to identify the most promising immunogenic targets are time consuming and less than totally effective. By taking the novel approach of incorporating both protein sequence information and structural features derived from high quality 3D structure predictions within our desktop computer software product, we propose to advance the ability of a broad range of life scientists to properly predict B-cell epitopes (the part of an antigen recognized by an antibody) applicable to their area of interest. This will accelerate the discovery of new monoclonal antibody pharmaceuticals, leading to improved human health across many diseases.
描述(由申请人提供):人类健康极大地受益于单克隆抗体(mAb)的治疗应用,治疗痛苦和破坏性疾病,如类风湿关节炎和癌症等。然而,mAb的开发是一个费力且耗时的过程。快速开发单克隆抗体所带来的健康益处是显而易见的,因此非常需要工具来指导科学家发现最有希望的抗原靶标,特别是关于b细胞表位(抗体识别的抗原部分)。该领域进展的关键障碍是无法在缺乏已知结构的情况下推断蛋白质序列的构象特征,以预测线性b细胞表位-已知表位中最大,最多样化和具有药用价值的一类。对现有预测方法的普遍批评是,它们是不准确的,并且没有解决b细胞表位的构象性质。DNASTAR提出创建一个软件管道,用于指导b细胞表位的预测,模拟单克隆抗体与其实验鉴定的抗原之间的动态结构界面,并筛选硅位点定向突变,以设计具有增强结合亲和力的更有效的抗体。第一阶段的目标是从靶蛋白序列和实验或预测结构中改进对抗原肽的预测。为了实现这一目标,DNASTAR已经与单克隆抗体生产、3D结构预测、蛋白质结构和动力学方面的专家建立了合作关系,包括访问他们的实验方法、数据和软件工具。我们的预测模型将受益于三个关键创新:1)卓越的数据集和对单克隆抗体生产的专业见解,2)引入最先进的3D结构预测来训练我们的表位预测者,以及3)首次在b细胞表位预测中使用基于结构的蛋白质动力学。在I期结束时,我们将提供一个增强的仅基于序列的b细胞表位预测模型,与目前的顶级预测方法(Aim 1)相比,以及一个基于序列和结构的基于3D结构预测和蛋白质动力学的表位预测模型(Aim 2)。在创建这些模型时,我们将考虑蛋白质序列的化学和物理性质以及介导蛋白质-蛋白质相互作用的生物物理学,包括溶剂可及性、氢键、残基柔韧性、结合核和分子表面的几何轮廓。拟议的软件管道将建立在Protean 3D上,我们的新分子结构和模拟查看器,并将提高广泛的实验科学家的技术能力,以估计未知结构的蛋白质的关键抗原结构特性-所有这些都在他们的台式电脑上。在达到这些目标后,科学家将认识到,仅使用氨基酸频率或倾向量表来描述b细胞表位不再足够。

项目成果

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Steven Joseph Darnell其他文献

Steven Joseph Darnell的其他文献

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{{ truncateString('Steven Joseph Darnell', 18)}}的其他基金

Rapid structure-based software to enhance antibody affinity and developability for high-throughput screening
基于快速结构的软件可增强抗体亲和力和高通量筛选的可开发性
  • 批准号:
    10080587
  • 财政年份:
    2020
  • 资助金额:
    $ 15.67万
  • 项目类别:
Rapid structure-based software to enhance antibody affinity and developability for high-throughput screening
基于快速结构的软件可增强抗体亲和力和高通量筛选的可开发性
  • 批准号:
    10155411
  • 财政年份:
    2020
  • 资助金额:
    $ 15.67万
  • 项目类别:
Accurate accessible cloud software for protein folding for molecular biologists
为分子生物学家提供准确、可访问的蛋白质折叠云软件
  • 批准号:
    8931346
  • 财政年份:
    2014
  • 资助金额:
    $ 15.67万
  • 项目类别:
Accurate accessible cloud software for protein folding for molecular biologists
为分子生物学家提供准确、可访问的蛋白质折叠云软件
  • 批准号:
    8714681
  • 财政年份:
    2014
  • 资助金额:
    $ 15.67万
  • 项目类别:
Accurate accessible cloud software for protein folding for molecular biologists
为分子生物学家提供准确、可访问的蛋白质折叠云软件
  • 批准号:
    8991498
  • 财政年份:
    2014
  • 资助金额:
    $ 15.67万
  • 项目类别:
Structural bioinformatics software for epitope selection and antibody engineering
用于表位选择和抗体工程的结构生物信息学软件
  • 批准号:
    9009304
  • 财政年份:
    2012
  • 资助金额:
    $ 15.67万
  • 项目类别:
Structural bioinformatics software for epitope selection and antibody engineering
用于表位选择和抗体工程的结构生物信息学软件
  • 批准号:
    8781169
  • 财政年份:
    2012
  • 资助金额:
    $ 15.67万
  • 项目类别:

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