Rational Design of High-Affinity Peptide Drug Candidates

说明(申请人提供)：新药研发是一个漫长而昂贵的过程。典型的药物发现过程从靶标识别演变到临床前开发和营销。几项研究估计，一种新药的平均开发成本超过8亿美元。这笔费用的很大一部分归因于最初通过筛选针对目标的活性的大量随机化合物组合文库而获得的废弃的候选铅，但由于各种原因而失败。最近在解开人类相互作用方面取得的巨大进展使得绘制出大量蛋白质-蛋白质相互作用的图谱成为可能，其中几个是疾病病理学的关键。识别蛋白质功能的调节子并将其转化为高含量的铅系列是现代药物开发中的关键活动。一种快速识别高亲和力多肽候选药物的方法将会带来巨大的好处，这些候选药物能够调节关键蛋白质的相互作用，并具有作为药物先导的高成功潜力。短的高亲和力的多肽配体是非常理想的药物候选者，因为它们是健壮的，容易大量合成，并且容易纯化。一些短肽已经显示出显著的调节蛋白质-蛋白质相互作用的能力，例如奥曲肽(SSTR2)和RGD肽(1v23整合素)，以及其他几个已经导致了高效肽模拟物的发展。在初步研究中，Lynntech已经证明，仅根据已知的氨基酸序列，通过将计算生物学和生物信息学工具与用于高通量筛选候选配体的独特、先进、高密度的多肽微阵列相结合的模块化方法，获得针对目标蛋白质的高亲和力多肽配体是可行的。通过单阵列筛选获得了几个高亲和力的多肽配体(20-30 nM亲和力)，并有可能使用迭代阵列进一步提纯亲和力。所使用的方法很容易实现自动化。这项研究建议创建一种用于高亲和力配基优化(HALO)的新的生物信息学引擎，该引擎将能够快速、自动化和定制地生成、筛选和鉴定疾病病理所必需的任何蛋白质-蛋白质相互作用的高亲和力多肽配体。Halo是一种非常有效的工具，将有助于快速生成Hit-to-Lead多肽候选药物，并有望彻底改变和加快药物发现的进程。

DESCRIPTION (provided by applicant): The R&D of new drugs is a protracted and expensive process. The typical drug discovery process evolves from target identification to preclinical development and marketing. Several studies estimate the average cost of development of a single new drug in excess of $800 million. A large portion of this expense is attributed to abandoned lead candidates initially obtained from screening vast random combinatorial libraries of compounds for activity against the target but which fail for various reasons. Recent vast strides in the unraveling of the human interactive have allowed the mapping of a large numbers of protein-protein interactions, several of which are key to the pathology of disease. The identification of modulators of protein function and the process of transforming these into high-content lead series are key activities in modern drug discovery. A rapid methodology to identify high-affinity peptide drug candidates able to modulate key protein interactions, and having high potential for success as drug leads, will have huge benefits. Short high-affinity peptide ligands are highly desirable drug candidates because they are robust, easily synthesized in large quantities, and readily purified. Several short peptides have demonstrated significant ability to modulate protein-protein interactions - e.g. octreotide (SSTR2) and RGD peptides (1v23 integrins), and several others have led to the development of highly potent peptidomimetics. In preliminary studies, Lynntech has demonstrated that it is feasible to obtain high-affinity peptide ligands to target proteins based on their known amino acid sequence alone using a modular approach that combined computational biology and bioinformatics tools with a unique, advanced, high-density peptide microarray for high throughput screening of candidate ligands. Several high-affinity peptide ligands (20-30 nM affinity) were obtained after a single array screening, with the potential to refine the affinity further using iterative arrays. The methodology used conveys itself readily for automation. This study proposes the creation of a new bioinformatics engine for High-Affinity Ligand Optimization (HALO) that will enable the rapid, automated, and customized generation, screening, and identification of high affinity peptide ligands to any protein-protein interaction integral to disease pathology. HALO is a highly potent tool that will be useful for rapid hit-to-lead peptide drug candidate generation and is expected to revolutionize and expedite the process of drug discovery.