Computational design of novel biodegrative enzyme pathways

在过去的150年里，人类已经合成了数十万种具有自然界中以前没有发现的官能团的化学物质。这些化学物质中的许多最终会被土壤和水中微生物体内最近进化的酶和代谢途径生物降解。在某些情况下，微生物对化学物质的代谢不完全，并将新的化学物质释放到环境中。在其他情况下，微生物完全代谢这些化学物质，并为生长和生存吸收碳、氮和/或磷。由于新化学物质在很短的进化时间范围内大量涌入，生物降解往往是次优的，以不稳定和低效的酶为标志，代谢途径不完整。过去，社会等待自然解决方案的进化。这项提议的一个主要目标是进一步发展常规和强有力地解决新进化的酶和代谢途径的局限性的能力，并提供用于商业目的的新酶。这项拟议的研究将产生一个蛋白质工程框架，通过将积累的关于生物降解途径的知识与计算酶设计和实验室进化中的最先进方法相结合，帮助克服新进化的酶途径的不足。这项研究将把两个不同但互补的研究小组聚集在一起，并增加量子化学和X射线结晶学方面的合作者。总体而言，我们寻求开发一种多方面的方法来更好地理解自然进化，并创造出自然界中尚未发现的新功能。拟议的工作将在化学、结构生物物理、微生物学和计算机科学的界面上培养本科生、研究生和博士后。将开发新的教学方法，如科学视频游戏和众包，并利用这些方法吸引非专家参与科学事业。将积极招募代表人数不足的群体和少数群体的学生，私人投资机构将参与公众、高中生和本科生及其教师的外联活动。

In the last 150 years, humans have synthesized hundreds of thousands of chemicals featuring functional groups not previously found in nature. Many of these chemicals are eventually biodegraded by recently-evolved enzymes and metabolic pathways found within microbes in soil and water. In some cases, microbes metabolize the chemicals incompletely and release new chemicals into the environment. In other cases, microbes completely metabolize the chemicals and assimilate the carbon, nitrogen and/or phosphorous for growth and survival. Due to the large influx of new chemicals over a very short evolutionary time scale, biodegradation is often suboptimal, marked by enzymes that are unstable and inefficient, and metabolic pathways that are incomplete.In the past, society waited for natural solutions to evolve. A major goal of this proposal is to further develop the ability to routinely and robustly address the limitations of newly evolved enzymes and metabolic pathways and provide new enzymes useful for commercial purposes. The proposed research will result in a protein-engineering framework to help overcome the deficiencies of newly evolved enzyme pathways by combining the accumulated knowledge about biodegradation pathways with state-of-the-art methods in computational enzyme design and laboratory evolution. This research will bring together two different, but complementary, research groups with additional collaborators in quantum chemistry and X-ray crystallography. Overall, we seek to develop a multi-faceted approach for better understanding natural evolution and creating new functionsnot yet discovered in nature.The proposed work will train undergraduate, graduate and postdoctoral students at the interface of chemistry, structural biophysics, microbiology, and computer science. Novel pedagogical approaches such as scientific video games and crowdsourcing will be developed and used to engage non-experts in the scientific enterprise. Students from underrepresented groups and minorities will be actively recruited and the PIs will engage in outreach activities involving the public, high school and undergraduate students and their teachers.