Rational Design of High-Affinity Peptide Drug Candidates

描述（由申请人提供）：新药的研究和开发是一项长期而昂贵的努力。典型的药物发现过程从疾病靶点的先导物鉴定到先导物优化、体外/体内评估、临床前和临床试验以及FDA批准。几项研究估计，开发一种获批新药的平均成本超过8亿美元。这一费用的很大一部分是由于放弃了候选先导药物，这些候选先导药物最初是通过筛选大量的、未集中的化合物文库来获得针对靶标的活性，但由于各种原因而失败。因此，拥有一个储备充足的候选药物管道是保证任何药物发现努力成功的必要条件。最近在人类蛋白质组和相互作用组的研究中取得了巨大进展，这使得绘制蛋白质-蛋白质相互作用（PPIs）的复杂网络成为可能。PPIs参与所有细胞过程，包括生长、维持和死亡，并且有文献证明某些PPIs的失调是各种疾病病理的基础。鉴定这些PPIs的调节剂，从而确定蛋白质的功能，并将其转化为高含量先导系列的过程是现代药物发现的关键活动。我们提出了一种快速的、基于知识的方法来开发几种高亲和力的候选肽药物，这些候选药物能够调节关键蛋白质的相互作用，并且作为药物先导物具有很高的成功潜力。肽是药物发现的高价值靶点，从PPI位点衍生的基于肽的先导物目前占制药管道的50%。在I期研究中，Lynntech和VBI的Garner团队明确证明，使用我们独特的方法，将系统生物学和生物信息学工具与先进的高密度肽微阵列相结合，用于高通量筛选候选配体，从其初级序列中获得靶向蛋白质的生物活性肽配体是可行的。通过基于阵列的亲和成熟获得了几个高亲和肽配体（nM范围亲和），并且这些配体的一个亚群显示出明显的调节ESRRG相互作用的倾向。我们第一阶段的努力也成功地开发了一个可访问网络的发现引擎和数据库，它使用户辅助的方法中涉及的各个步骤的伪自动化成为可能，从而大大加快了过程。需要进一步增强，使其成为先导生成，先导优化和先导爆炸的有效药物发现引擎。II期提案不仅将开发用于数据分析的图形用户界面工具，并为管道中的配体的下选择提供信息，而且还将阐明选择规则，这将为从蛋白质序列中获得高价值的候选先导药物提供最快的方法。

DESCRIPTION (provided by applicant): Research and development of new drugs is a protracted and expensive endeavor. The typical drug discovery process evolves from lead identification for a disease target to lead optimization, in vitro/in vivo evaluation, preclinical and clinical testing, and FDA approval. Several studies estimate the average cost of development of a single, approved new drug in excess of $800 million. A large portion of this expense is attributed to abandoned lead candidates that are obtained initially from screening vast, unfocussed libraries of compounds for activity against the target but which fail for various reasons along the pipeline. Thus, having a well stocked pipeline of drug candidates is integral to guaranteeing success in any drug discovery endeavor. Recent vast strides in unraveling the human proteome and interactome have allowed mapping of the complex network of protein-protein interactions (PPIs). PPIs are involved in all cellular processes, including growth, maintenance, and death, and it is documented that the dysregulation of certain PPIs underlies the pathology of various diseases. The identification of modulators of these PPIs, and consequently protein function, and the process of transforming these into high-content lead series are key activities in modern drug discovery. We have proposed a rapid, knowledge-based methodology to develop several high-affinity peptide drug candidates able to modulate key protein interactions, and having high potential for success as drug leads. Peptides are high value targets in drug discovery and peptide-based leads derived from PPI sites currently comprise >50% of pharmaceutical pipelines. In Phase I studies, Lynntech and the Garner group at VBI have demonstrated unequivocally that it is feasible to obtain biologically active peptide ligands to target proteins, from their primary sequence alone, using our unique approach that combines systems biology and bioinformatics tools with an advanced, high-density peptide microarray for high-throughput screening of candidate ligands. Several high- affinity peptide ligands (of nM range affinity) were obtained from array based affinity maturation, and a subset of these ligands displayed a clear proclivity to modulate ESRRG interactions. Our Phase I efforts also have resulted in the successful development of a web-accessible discovery engine and database which enables user-assisted pseudo-automation of the various steps involved in the approach, thereby vastly expediting the process. Further enhancements are required to make this a potent drug discovery engine for lead generation, lead optimization, and lead explosion. The Phase II proposal will not only develop graphic-user interface tools for data analysis and informed down-selection of ligands in a pipeline but also elucidate selection rules that will inform the quickest way to obtain a high value lead drug candidate from protein sequence.