Fig 1.
Information available on the BioBB website for the workflow tutorials, including links to: (i) workflow versions registered and available in WorkflowHub (Jupyter Notebook, CWL, Python and Galaxy); (ii) ways to directly launch the workflow (Jupyter Notebook myBinder, Galaxy and BioBB Workflows [28] website); (iii) tutorial in web version (HTML); (iv) source code in GitHub; and (v) documentation in Read the Docs.
Fig 2.
Uniformity in the Jupyter Notebooks collection: in the pipeline process, with markdown cell for documentation followed by the execution cell and the graphical inspection of the intermediate results (left); and in the cell execution, using the BioBB syntax of importing the module, defining inputs/outputs and properties, and launching the execution for all processes run in the workflow (inline, right).
Fig 3.
Intermediate results extracted from the “GROMACS Protein MD Setup” workflow.
(a) PDB structure with missing atoms added, ready to be used as MD input; (b) pressure and density box parameters measured over time in the final NPT equilibration process (10ps); (c) RMSd of the snapshots included in the final trajectory against the first snapshot (blue) and the original experimental structure (red); and (d) interactive visualization of the final trajectory using the simpletraj tool.
Fig 4.
Intermediate results extracted from the “Protein–ligand Docking” workflow.
(a) Pockets identified on the surface of the protein by the fpocket tool; (b) box including the protein pocket to be used in the docking process; and (c) final comparison of the chosen ligand pose against the experimental structure.
Fig 5.
Markdown documentation and intermediate results extracted from the “Macromolecular Coarse-Grained Flexibility” workflow.
(a) Eigenvalue residue components analysis, indicating the residues contributing the most to the key essential deformations of the protein. An associated NGL widget displays these residues in ball and stick representation (red); (b) domain decomposition analysis displayed along the pseudo-trajectory with the simpletraj tool; (c) RMS inner product (RMSip) for all the CG pseudo-trajectories against an atomistic MD simulation; and (d) extract of documentation included for the NMA CG method.
Fig 6.
Intermediate results extracted from the “Molecular Interaction Potentials” workflow.
(a) Structural water molecules and ions placed in the energetically most favorable spots on the surface of the protein; (b) molecular interaction potential grids obtained from a positive probe (left, blue), a negative probe (middle, red), and a neutral probe (right, gray); and (c) potential energy (electrostatic + VdW) calculated for a protein–ligand interaction. The inline plot shows the representation of the protein residues with lower energy (higher affinity). (d) Representation of the residues contributing the most to the protein–protein complex interaction.