HyperBeta: characterizing the structural dynamics of proteins and self-assembling peptides

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作者
Marco S. Nobile
Federico Fontana
Luca Manzoni
Paolo Cazzaniga
Giancarlo Mauri
Gloria A. A. Saracino
Daniela Besozzi
Fabrizio Gelain
机构
[1] Eindhoven University of Technology,Department of Industrial Engineering and Innovation Sciences
[2] University of Milano-Bicocca,Department of Informatics, Systems and Communication
[3] SYSBIO/ISBE.IT Centre of Systems Biology,Department of Mathematics and Geosciences
[4] Bicocca Bioinformatics,Department of Human and Social Sciences
[5] Biostatistics and Bioimaging Centre (B4),undefined
[6] Fondazione IRCCS Casa Sollievo della Sofferenza,undefined
[7] Unità Ingegneria Tissutale,undefined
[8] University of Trieste,undefined
[9] University of Bergamo,undefined
[10] Center for Nanomedicine and Tissue Engineering (CNTE),undefined
[11] A.S.S.T. Grande Ospedale Metropolitano Niguarda,undefined
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摘要
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 β\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}-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 β\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}-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.
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