A Library for Self-Assembling Peptide Analysis from Molecular Dynamics Simulation made with Gromacs
The knowledge of the time-dependent formation of secondary structures is crucial for a deeper understanding of the self-assembling phenomenon. We have developed and validated Morphoscanner, a standalone topological pattern recognition software on diverse protein dynamics and structures. Morphoscanner allows to analyze of MARTINI CG-MD and AA-MD simulations of peptide systems. Lately, a new version called Morphoscanner2.0 is released which has a new python library suitable for MD simulations of multimolecular systems. Not only that, the main highlight Morphoscanner is ideal for tracking capability secondary structure patterns and quantifying the transition entropy related to the self-assembly process. Morphoscanner2.0 will open new opportunities in the field of structural biology and synthetic biology.
Overview of Morphoscanner
Take a Glance at some of analyses provided by Morphoscanner2.0
The 3-dimensional plot of the shift values along the trajectory
The distribution of shift values during the trajectory can be visualized with three separate methods, one for each type of shift:
plot3d_parallel() for the cumulative frequency use plot_shift_parallel_percentage()
plot3d_antiparallel_negative() for the cumulative frequency use plot_shift_antiparallel_negative_percentage()
plot3d_antiparallel_positive() for the cumulative frequency use plot_shift_antiparallel_positive_percentage()
In the first column, CG structures are visualized highlighting α-helix identified through Morphoscanner2.0.
are shown in the third column. The Morphoscanner2.0 analyses of 3bep, shown in A) are in agreement with STRIDE analyses. Indeed, as shown in A) and B) Morphoscanner2.0 correctly identifies all the α-helix domains. Similar results from the analysis of 4d2g and 5i55 (See D,E,F and G,H,I)
Analysis of atomistic MD simulation of SAPs B24. As shown in A)
Morphoscanner can be used, in combination with NGLview, for obtaining graphical
representation B) By considering a single frame Morphoscanner returns the graph and clustering, C) The conformational transitional analysis points out that the formation of antiparallel β-sheets domains relies on the structural transitions of α-helix peptides.
D), at the beginning of the simulations 18% of
the peptides are folded in α-helix structures, whereas just 5% of the peptides adopt
a β-turn conformation.
Look into the tutorial given below for downloading and setting up the Morphoscanner2.0: