A Chemical Biology Network for Personalized Medicine

描述（由申请人提供）：生命的实时化学发生在细胞环境中蛋白质和小化学物质的界面上。历史上第一次，以3D蛋白质结构数据库和NIH Pubchem化学库的形式积累了关于人类蛋白质组及其相互作用的化学基因组的足够信息。此外，“互补算法”可以准确地评估任何化学物质和任何蛋白质表面之间的能量互补性或契合度，并且具有以高通量方式部署这些工具的计算能力。最后，系统生物学方法已经发展到这样的地步：一旦互补性算法将所有化学物质与所有蛋白质交叉评分，生命的实时化学相互作用的完整网络就可以被可视化和探索。我们建议建立一个化学生物学网络来统一这些数据，并提供一个直观的web界面，方便非定量生物医学研究者使用。该网络和附带的接口一旦部署，就代表了一个关键的基础设施，可以大大加快协作、多学科和跨学科的基础、转化和/或临床研究，特别是通过为个性化医疗和传统药物开发工作提供新的药物开发途径。个性化医疗旨在确定患者的遗传谱-通常是来自微阵列数据的高度复杂的概率表达谱-与最佳治疗反应相关。从本质上讲，所提出的化学生物学网络可以用这些特征之一进行查询，并且可以立即检索到生物学上匹配的类似药物的化合物的列表。这样的工具将对临床试验完成和药物批准的速度产生深远的影响，因为历史表明，与生物标志物（如her2-neu和赫赛汀）匹配的药物的临床试验进行得更快，成功率更高，成本也低得多。此外，所提出的化学生物学网络可以通过先导化合物查询，并且可以立即检索具有相似生物活性的化学多样性化合物。这也可能加速药物审批，因为与推进单一化学品类别相比，并行推进针对特定疗法的多种先导组合更有可能迅速获得成功。FDA的关键路径倡议（http://www.fda.gov/oc/initiatives/criticalpath/initiative.html）优雅地阐述了通过接受该提案所针对的重大机遇所解决的挑战，这是NIH和FDA共同面临的前瞻性挑战，目前还没有什么解决方案。这一具体机会得益于所有必要要素的准备就绪，因此，尽管潜在影响巨大，但在两年的ARRA时间框架内，这些里程碑是高度可实现的。一旦建成，该网络具有未来几年低开销维护的综合优势，以及在地方，商业和政府层面扩展的多个高度适用的资金机会。基础设施一旦建成，就具有高度的可持续性和可扩展性，可以继续用于美国生物医学研究企业。)

DESCRIPTION (provided by applicant): The real-time chemistry of life occurs at the interfaces of proteins and small chemicals present in the cellular environment. For the first time in history, sufficient information on the human proteome and its interacting chemogenome has accumulated in the form of the 3D protein structural database and the NIH Pubchem chemical library. In addition, 'complementarity algorithms', which accurately assess the energetic complementarity, or fit, between any chemical and any protein surface have recently become available, as has the computing power to deploy these tools in a high-throughput manner. Finally, systems biology methods have evolved to the point that the complete network of interactions of the real-time chemistry of life may be visualized and explored once complementarity algorithms have cross-scored all the chemicals to all the proteins. We propose here to build a chemical biology network to unify these data, along with an intuitive web interface for easy use by non-quantitative biomedical investigators. The network and accompanying interface, once deployed, represents a critical infrastructure that could substantially accelerate collaborative, multi- and interdisciplinary basic, translational, and/or clinical research, specifically by enabling new avenues of drug development for personalized medicine and traditional drug development efforts. Personalized medicine seeks to identify the genetic profiles of patients-frequently highly complex probabilistic expression profiles from microarray data--that correlate with optimal therapy responses. Essentially, the proposed chemical biology network may be queried with one of these profiles and a list of biologically matched drug-like chemical compounds would instantly be retrieved. Such a tool would have a profound impact on the rapidity of clinical trial completion and drug approval, as history has shown that clinical trials of drugs matched to biomarkers, such as her2-neu and Herceptin, proceed more rapidly and succeed more often at a much reduced cost. In addition, the proposed chemical biology network may be queried by lead compound and chemically diverse compounds with similar biological activity may be retrieved instantly. This, too, may accelerate drug approval as advancing a diverse portfolio of leads in parallel for a specific therapy is more likely to succeed rapidly than advancing a single chemical class. The challenge addressed by taking on the grand opportunity targeted by this proposal is elegantly articulated by the FDA's Critical Path Initiative (http://www.fda.gov/oc/initiatives/criticalpath/initiative.html), a forward- looking challenge that faces both the NIH and the FDA jointly, for which there are currently few solutions on the horizon. This specific opportunity benefits from the readiness of all the required elements, so that, despite the enormous potential impact, the milestones are highly achievable within the ARRA timeframe of two years. Once built, this network has the combined advantage of low overhead maintenance for future years, and multiple highly applicable funding opportunities for expansion at the local, commercial and governmental level. The infrastructure, once built, is thus highly sustainable and extensible for continued utility in the U.S. biomedical research enterprise. ) PUBLIC HEALTH RELEVANCE: As the RCSB Protein Data Bank of 3D structures nears 60,000 entries (with the human genome estimated to contain approximately 20,000 genes) and the NIH's Pubchem database nears 20 million chemical compounds, the possibility exists that the majority of the 3D structures of life as well as an informative sample of the diversity of chemical space is readily available to us in 2009. The grand opportunity thus presents itself to cross-connect these two elemental bioscientific databases into a single chemical biology network of direct links between genes, protein targets, and potential chemical therapeutics. Using high-throughput computational methods, we will build this network of relationships as a transformative tool for personalized medicine and drug discovery.