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

Abstract Self-assembling processes are ubiquitous phenomena that drive the organization and hierarchical formation of complex molecular systems. The investigation assembling dynamics, emerging from interactions among biomolecules like amino-acids polypeptides, is fundamental to determine how a mixture simple objects can yield structure at nano-scale level. In this paper we present HyperBeta, novel open-source software exploits an innovative algorithm based on hyper-graphs efficiently identify graphically represent dynamics $$\beta$$ β -sheets formation. Differently existing tools, HyperBeta directly manipulates data generated by means coarse-grained simulation tools (GROMACS), performed using MARTINI force field. Coarse-grained structures visualized ’s proprietary real-time high-quality 3D engine, which provides plethora analysis statistical information, controlled intuitive event-based graphical user interface. renderer relies variety visual cues improve readability interpretability distance depth relationships between peptides. We show able track in simulations, completely new efficient mean for kinetics these nano-structures. will therefore facilitate biotechnological medical research where structural elements play crucial role, such as development high-performance biomaterials tissue engineering, or better comprehension mechanisms basis pathologies Alzheimer’s disease.