Metabolic Drug Targeting in Haemophilus influenze

描述（由申请人提供）：随着细菌的不断进化和新的感染生物体的出现，抗菌素耐药性的上升持续存在。这种情况使得现在和将来都迫切需要开发新的化合物来治疗这些感染。代谢是未来抗菌药物开发的潜在丰富靶标来源，但尚未开发。从机制角度确定代谢靶点并在高分辨率下理解其基本作用的能力对于治疗学的发展是理想的。利用代谢网络成分和代谢功能在许多生物体中的固有相似性和差异性，可以提供前所未有的设计窄谱和广谱抗生素的能力，提供必要的计算/实验基础设施。

DESCRIPTION (provided by applicant): The rise of antimicrobial drug resistance persists as bacteria continue to evolve and new infectious organisms are encountered. This situation has created an imperative need to develop new compounds to treat these infections both now and in the future. Metabolism represents a potentially rich source of targets for future antimicrobial drug development that remains untapped. The ability to identify metabolic targets and understand their essential roles at a high level of resolution from a mechanistic perspective is ideal for the development of therapeutics. Taking advantage of the inherent similarities and differences in the metabolic network components and functional capabilities of metabolism across many organisms may offer an unprecedented ability to design narrow as well as broad spectrum antibiotics, provided the necessary computational/experimental infrastructure. Herein we put forth an SBIR program that takes the initial first steps toward building a model-driven technology platform capable of generating the metabolic insight and characterization necessary to exploit this potentially rich class of targets. We will be using established approaches from constraints-based modeling and the powerful capabilities of SimPheny to perform modeling and integrative analysis of experimental data. Through the enhancement of an existing model of H. influenzae within SimPheny and the work proposed herein this program will generate: 1) an improved characterization of H. influenzae metabolic pathways and their regulation and role in invasive disease; 2) the necessary representation of metabolic systems to provide the context for integrative analysis of high throughput data sets (i.e. gene/protein expression profiles); 3) a scalable platform to demonstrate the capability of using models to design experimental plans and guide biological discovery; 4) novel targets for the development of antimicrobials for H. influenzae infections; 5) and enhanced validation of existing targets in H. influenzae.