EAGER: Computational Design of Peptide Ligands for the Bioseparation of "Fab" Antibody Fragments

开发一种可以治愈癌症的药物是制药业的圣杯。一种策略是制造抗体，模拟并增强人体与导致包括癌症在内的慢性和致命疾病的外来物质(抗原)结合和清除的自然能力。要提高身体的自然自我修复能力，需要产生大量高度纯化的抗体，这些抗体旨在寻找特定的抗原，同时使健康细胞不受损害。生产高纯度、有针对性的合成抗体需要分离和培养产生这种抗体的细胞，然后从细胞培养物中回收抗体。这一过程导致了单抗的产生，反映了一个能够产生感兴趣的抗体的(单)免疫细胞被大量地“克隆”(复制和培养)。从组成细胞培养的复杂介质中回收和纯化单抗是困难的，因此价格昂贵。此外，单抗是大而复杂的生物分子，这一特点导致单抗在生物组织中渗透迟缓。识别与目标抗原结合的抗体的特定片段，并仅产生该抗体片段(Fab)，从而增加组织渗透和治疗的效力。碎片化解决了渗透问题，但从分离的细胞培养中恢复Fabs仍然是一个挑战。目前回收Fab的方法价格昂贵，而且使用潜在的免疫原性蛋白。因此，该项目的目标是通过计算设计和合成新的多肽配体(短蛋白质衍生分子)，这些配体将选择性地回收目标Fabs，并且可以很容易地在实验室中生产，而不是从细胞培养中获得。这一计算项目将筛选与FABS亲和力、选择性和可逆结合的短小新肽。筛选将使用先前开发的搜索算法，该算法识别在中性pH下与目标Fab具有高亲和力的短肽序列(小于25个氨基酸)，但在中等酸性条件下(4.0 pH 5.0)释放Fab。此外，计算将识别区分具有kappa轻链和lambda轻链的Fabs的短肽序列，并允许对kappa-lambda混合物进行分级。该项目风险很高，而且是探索性的，因为目前还不能对多肽结合蛋白的序列进行良好的初步猜测。计算预测将通过实验室综合和测试得到验证。该项目将培训一名博士后研究员，并通过辅导、研讨会和外联努力，进一步努力扩大妇女和代表性不足的少数群体在STEM的参与。如果成功，该项目将导致开发用于Fab回收和选择性区分kappa和lambda Fabs的短链(15个氨基酸)合成肽。这两个结果代表了抗体纯化的新范例，可预见的扩展到其他抗体的分级、分析开发、用于免疫保护的抗体亚类的个体治疗能力的调查、疾病诊断和新抗体疗法的设计。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Developing a drug that will cure cancer is the holy grail of the pharmaceutical industry. One strategy is to produce antibodies that mimic, yet enhance, the body's natural ability to bind to, and eliminate, foreign agents (antigens) that lead to chronic and fatal diseases, including cancer. Improving upon the body's natural ability to self-heal requires producing high quantities of highly purified antibodies that are designed to seek out specific antigens while leaving healthy cells unharmed. Producing high purity, targeted synthetic antibodies requires isolation and growth of a culture of cells that produces that antibody, followed by recovery of the antibody from the cell culture. This process leads to monoclonal antibodies, reflecting that one (mono) immune cell able to produce the antibody of interest was "cloned" (reproduced and grown) in large quantity. Recovery and purification of monoclonal antibodies from the complex media that comprises the cell culture is difficult, and thus expensive. Furthermore, monoclonal antibodies are large and complex biological molecules, features that lead to sluggish penetration of the monoclonal antibody into biological tissues. Identifying the particular fragment of the antibody that binds to the targeted antigen and producing only that fragment of the antibody (Fab), thus increases tissue penetration and the potency of the treatment. Fragmentation addresses penetration concerns, but recovery of Fabs from isolated cell cultures remains a challenge. Current methods for Fab recovery are expensive and use potentially-immunogenic proteins. The goal of this project is thus to computationally design and synthesize new peptide ligands (short protein-derived molecules) that will selectively recover targeted Fabs, and can easily be produced in a laboratory rather than derived from cell cultures. This computational project will screen short novel peptides for affinity, selectivity, and reversible binding to FAbs. The screening will use a previously developed search algorithm that identifies short peptide sequences (less than 25 amino acids) that have high affinity for a target Fab at neutral pH, but release the Fab at mildly acidic conditions (4.0 pH 5.0). Moreover, the computations will identify short peptide sequences that distinguish between Fabs with kappa and lambda light chains, and allow fractionation of kappa-lambda mixtures. The project is 'high risk' and exploratory because a good initial guess for the sequence of the peptide binder is currently unavailable. The computational predictions will be validated with laboratory synthesis and testing. The project will train a post doctoral researcher, and enable further efforts to broaden participation of women and under-represented minorities in STEM via mentoring, seminars, and outreach efforts. If successful, this project will lead to the development of short chain (15 amino acids) synthetic peptides for Fab recovery and selective differentiation of kappa and lambda Fabs. These two outcomes represent a new paradigm for antibody purification, with foreseeable extension to fractionation of other antibodies, assay development, investigation of the individual therapeutic powers of antibody subclasses for immune protection, disease diagnosis, and design of novel antibody therapeutics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.