Novel Enhanced Sampling Methods in Multiscale Modeling

由于硬件处理能力和软件算法效率的不断提高，基于计算机的技术正在成为最有前途的新方法之一。最近的一个例子包括机器学习算法，它彻底改变了计算机科学中的数据分析，并导致了新的计算机游戏、视觉识别和其他在许多情况下超过人类表现的应用。在这里，我们建议使用新的增强采样算法来执行原子分子模拟。与目前的计算机模拟相比，大多数生物学上重要的过程发生的时间尺度要长得多。因此，为了获得关于复杂分子体系的动力学和构象动力学的有意义和准确的结果，我们使用了使用不同偏差的并行计算来增强采样的算法。开发更优化的偏置算法将使我们能够更快、更准确地对感兴趣的关键生物过程进行建模，包括配体结合、蛋白质构象等。在这里，我们的目标是使用受机器学习启发的统计算法来开发新的增强采样方法，用于分子模拟。新颖的算法可以应用于广泛的分子建模问题。我们将重点研究磷酸催化酶，并研究关键的DNA加工酶，以揭示这些系统中的催化机制。由于磷酸催化酶在大多数生物过程中的本质，目前临床上大量的药物也针对磷酸加工酶治疗广泛的疾病。例如，用于抗艾滋病毒和乙肝的逆转录酶和整合酶抑制剂，用于胃病的质子泵抑制剂，用于治疗大量癌症的激酶、PARP和拓扑异构酶抑制剂。用现代分子模拟方法研究磷酸盐催化体系将使我们对生命的分子基础的现有知识取得根本性进展。它还将为合理开发更好的抗击疾病的药物创造机会。

Computer-based technologies are becoming one of the most promising novel approaches due to continuously accelerated growth of both hardware processing power and software algorithm efficiency. One recent example includes machine learning algorithms that revolutionised data analysis in computer science, and lead to new computer games, visual recognition, and other applications that overtake human performance in many cases. Here, we propose to perform atomistic molecular simulations using novel enhanced sampling algorithms. Most biologically important processes take place on significantly longer timescales than those accessible to current computer simulations. Therefore, to obtain meaningful and accurate results regarding the kinetics and conformational dynamics of complex molecular systems, we use algorithms that enhance the sampling using parallel calculations with different biases. Developing more optimal biasing algorithms will allow us to model faster and more accurately the key biological processes of interest, including ligand binding, protein conformations, etc.Here we aim to use statistical algorithms inspired by machine learning to develop novel enhanced sampling methods for molecular simulations. Novel algorithms can be applied to a wide range of molecular modeling problems. We will focus on phosphate catalytic enzymes, and study key DNA processing enzymes to reveal the catalytic mechanism in these systems.Due to the essential nature of phosphate catalytic enzymes in most biological processes, a large number of drugs in current clinical practice also target phosphate-processing enzymes treating a wide range of diseases. Examples include reverse transcriptase and integrase inhibitors used against HIV and hepatitis B, proton pump inhibitors used in gastric diseases, kinase, PARP and topoisomerase inhibitors used against a large number of cancers. Studying phosphate catalytic systems with modern molecular modeling methods will enable fundamental advances in our current knowledge of the molecular basis of life. It will also create opportunities for rational development of better drugs to fight diseases.