Development of a complete pathway model for the synthesis of the gram negative cell

据预测，在未来33年内，抗生素耐药细菌造成的死亡人数将超过癌症造成的死亡人数。由于缺乏新的抗菌分子的发现和开发，这一问题更加复杂。特别值得关注的是革兰氏菌的耐药水平，如大肠杆菌、克尔伯氏菌和假单胞菌。Oppilotech正在开发一个计算平台，以便于检测针对革兰氏菌的新型抗菌目标。我们已经使用这种方法成功地确定了削弱细胞壁结构的新靶点，使它们对现有药物更具渗透性。这种增强方法有能力重新激活由于高耐药性而不再使用的药物。它还可以减少抗菌素的剂量，这对于具有已知毒性问题的药物（如粘菌素）尤其重要。最后，这种方法可能有助于使用革兰氏病毒药物治疗革兰氏病毒感染。如果获得资助，Oppilotech将利用这笔奖金聘请一名计算生物学家来扩展现有的模型，以纳入肽聚糖合成。这将有效地完成所有主要的细胞质步骤，涉及细菌细胞包膜的合成。一旦完成，这个确定性模型将与一个空间模型联系起来，目的是确定在增强活性方面最理想的药物靶点。

It is predicted that within the next 33 years, deaths attributable to antibiotic resistant bacteria will outnumber those caused by cancer. This problem is compounded by the lack of both the discovery and development of novel antimicrobial molecules. Of particular concern are the resistance levels exhibited by the Gram -ve bacterial species such as E.coli, Kelbsiella and pseudomonas. Oppilotech are developing a computational platform in order to facilitate the detection of novel antimicrobial targets against Gram-ve bacteria. We have used this method successfully to identify new targets which weaken the cell wall structures making them more permeable to existing drugs. This potentiating approach has the capacity to reactivate drugs which are no longer used because of high resistance levels. It can also reduce the doses at which antimicrobials are given, particularly important for drugs with know toxicity issues (such as colistin). Finally, this approach may facilitate the use of Gram +ve drugs for Gram -ve infections. If funded Oppilotech will use the award to employ a computational biologist to expand the existing model in order to incorporate peptidoglycan synthesis. This will effectively complete all of the main cytoplasmic steps involved in the synthesis of the bacterial cell envelope. Once complete this deterministic model will be linked with a spatial model with the aim of determining the most optimal drug target in terms of potentiating activity.