Radical, force-driven computational methods for enzyme design in biotechnology

酶在现有和新分子的成本效益，环境友好的生产中提供了巨大的希望。然而，化学生物学中最具挑战性的领域之一是新酶的设计。计算机模拟特别适合于酶设计，因为它提供了对任何合理设计过程至关重要的详细分子见解。科学中发展最快的领域之一就是计算机模拟。这是因为计算机规模的不断增长和强大的新算法的发展。该项目的首席研究员Henchman博士最近开创了两种新的算法，解决了将计算方法应用于任何系统的主要技术挑战。一种算法利用作用在分子上的力来量化任何分子的振动灵活性，这是以前的算法只能对相对刚性的系统做的事情。另一种算法，称为RAD，是一种通用的，真正的预测方法来确定任何分子系统的原子配位，不仅是键合原子，更重要的是非键合配位。这两种算法的范围是巨大的，它们提供了量化分子稳定性的关键方法。在这个项目中，他们将被用来指导酶的设计，与诺贝尔奖获奖的量子力学/分子力学方法一起研究酶动力学。所有研究都将在世界领先的曼彻斯特生物技术研究所进行，这将为您提供测试预测的机会。

Enzymes offer enormous promise in the cost-efficient, environmentally friendly production of existing and new molecules. One of the most challenging areas in chemical biology, however, is the very design of new enzymes. Computer simulation is particularly suited to enzyme design because it provides detailed molecular insight that is crucial for any rational design process. And one of the most rapidly growing areas in science happens to be computer simulation. This is because of the ever-growing scale of computers and the development of powerful new algorithms. The Principal Investigator of this project, Dr Henchman, has recently pioneered two new such algorithms that solve major technical challenges in applying computational methods to any system. One algorithm quantifies the vibrational flexibility of any molecule using the force acting on the molecule, something that previous algorithms could only do for relatively rigid systems. The other algorithm, termed RAD, is a general, truly predictive way to determine atomic coordination for any molecular system, not just for bonded atoms but more importantly for non-bonded coordination. The scope of both algorithms is immense and they provide a key way to quantify molecular stability. In this project, they will be leveraged to guide enzyme design, together with the Nobel-prize winning quantum mechanics/molecular mechanics methodology to study enzyme kinetics. All research will take place in the world-leading Manchester Institute of Biotechnology which will provide opportunities to test your predictions.