Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, The Netherlands.
Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy.
Sci Rep. 2021 Apr 8;11(1):7783. doi: 10.1038/s41598-021-87087-0.
Self-assembling processes are ubiquitous phenomena that drive the organization and the hierarchical formation of complex molecular systems. The investigation of assembling dynamics, emerging from the interactions among biomolecules like amino-acids and polypeptides, is fundamental to determine how a mixture of simple objects can yield a complex structure at the nano-scale level. In this paper we present HyperBeta, a novel open-source software that exploits an innovative algorithm based on hyper-graphs to efficiently identify and graphically represent the dynamics of [Formula: see text]-sheets formation. Differently from the existing tools, HyperBeta directly manipulates data generated by means of coarse-grained molecular dynamics simulation tools (GROMACS), performed using the MARTINI force field. Coarse-grained molecular structures are visualized using HyperBeta 's proprietary real-time high-quality 3D engine, which provides a plethora of analysis tools and statistical information, controlled by means of an intuitive event-based graphical user interface. The high-quality renderer relies on a variety of visual cues to improve the readability and interpretability of distance and depth relationships between peptides. We show that HyperBeta is able to track the [Formula: see text]-sheets formation in coarse-grained molecular dynamics simulations, and provides a completely new and efficient mean for the investigation of the kinetics of these nano-structures. HyperBeta will therefore facilitate biotechnological and medical research where these structural elements play a crucial role, such as the development of novel high-performance biomaterials in tissue engineering, or a better comprehension of the molecular mechanisms at the basis of complex pathologies like Alzheimer's disease.
自组装过程是普遍存在的现象，它驱动着复杂分子系统的组织和分层形成。研究自组装动力学，源于氨基酸和多肽等生物分子之间的相互作用，对于确定如何从简单物体的混合物在纳米尺度水平上产生复杂结构是至关重要的。在本文中，我们提出了 HyperBeta，这是一种新颖的开源软件，它利用基于超图的创新算法来有效地识别和图形化表示β-折叠形成的动力学。与现有工具不同，HyperBeta 直接操纵通过使用 MARTINI 力场的粗粒分子动力学模拟工具（GROMACS）生成的数据。粗粒分子结构使用 HyperBeta 的专有的实时高质量 3D 引擎进行可视化，该引擎提供了大量的分析工具和统计信息，通过直观的基于事件的图形用户界面进行控制。高质量渲染器依赖于各种视觉提示来提高肽之间距离和深度关系的可读性和可解释性。我们表明，HyperBeta 能够在粗粒分子动力学模拟中跟踪β-折叠的形成，并为研究这些纳米结构的动力学提供了一种全新的有效手段。因此，HyperBeta 将促进生物技术和医学研究，这些结构元素在其中起着至关重要的作用，例如在组织工程中开发新型高性能生物材料，或更好地理解阿尔茨海默病等复杂病理的基础分子机制。
