Calculating hydrogen bonds: advanced selections

We will find all intramolcular hydrogen bonds of a protein without passing any atom selections. We will also look at how to use more advanced atom selections than we saw in Calculating hydrogen bonds: the basiscs.

Last updated: June 23, 2021 with MDAnalysis 2.0.0-dev

Minimum version of MDAnalysis: 2.0.0-dev0

Packages required:

• MDAnalysis ([MADWB11], [GLB+16])

• MDAnalysisTests

• numpy

See also

• Calculating hydrogen bonds: the basics

• Calculating hydrogen bond lifetimes

Note

Please cite Smith et al. (2018) when using HydrogenBondAnaysis in published work.

import numpy as np

import MDAnalysis as mda
from MDAnalysis.tests.datafiles import PSF, DCD
from MDAnalysis.analysis.hydrogenbonds import HydrogenBondAnalysis

Loading files

u = mda.Universe(PSF, DCD)

The test files we will be working with here feature adenylate kinase (AdK), a phosophotransferase enzyme. ([BDPW09])

Find all hydrogen bonds

The simplest use case is to allow HydrogenBondAnalysis to guess the acceptor and hydrogen atoms, then to identify donor-hydrogen pairs via the bond information in the topology.

Accetptor and hydrogen atoms are guessed based on the mass and partial charge of the atoms.

hbonds = HydrogenBondAnalysis(universe=u)

hbonds.run(verbose=True)

Use guess_acceptors and guess_hydrogens to create atom selections

It is also possible to use generated hydrogens_sel and acceptors_sel via the guess_hydrogens and guess_acceptors class methods.

This selection strings may then be modified prior to calling run, or a subset of the universe may be used to guess the atoms. For example, below we will find hydrogens and acceptors belonging to specific residues.

hbonds = HydrogenBondAnalysis(universe=u)
hbonds.hydrogens_sel = hbonds.guess_hydrogens("resname ARG HIS LYS")
hbonds.acceptors_sel = hbonds.guess_acceptors("resname ARG HIS LYS")

hbonds.run(verbose=True)

We can check which atoms were used in the analysis:

print(f"hydrogen_sel = {hbonds.hydrogens_sel}")
print(f"acceptors_sel = {hbonds.acceptors_sel}")

hydrogen_sel = (resname ARG and name HE) or (resname ARG and name HH11) or (resname ARG and name HH12) or (resname ARG and name HH21) or (resname ARG and name HH22) or (resname ARG and name HN) or (resname LYS and name HN) or (resname LYS and name HZ1) or (resname LYS and name HZ2) or (resname LYS and name HZ3)
acceptors_sel = (resname ARG and name NE) or (resname ARG and name NH1) or (resname ARG and name NH2) or (resname ARG and name O) or (resname LYS and name O)

More advanced selections

Slightly more complex selection strings are also possible. For example, to find hydrogen bonds involving the protein and water within 10 Å of the protein:

hbonds = HydrogenBondAnalysis(universe=u)

protein_hydrogens_sel = hbonds.guess_hydrogens("protein")
protein_acceptors_sel = hbonds.guess_acceptors("protein")

water_hydrogens_sel = "resname TIP3 and name H1 H2"
water_acceptors_sel = "resname TIP3 and name OH2"

hbonds.hydrogens_sel = f"({protein_hydrogens_sel}) or ({water_hydrogens_sel} and around 10 not resname TIP3)"
hbonds.acceptors_sel = f"({protein_acceptors_sel}) or ({water_acceptors_sel} and around 10 not resname TIP3)"

hbonds.run(verbose=True)

Note

The Universe we are analysing has the water removed. The above example is for illustrative purposes only.

Hydrogen bonds between specific groups

To calculate the hydrogen bonds between different groups, for example protein and water, one can use the between keyword. Below we will find protein-water and protein-protein hydrogen bonds, but not water-water hydrogen bonds. We do this by passing atom selection for the groups we wish to find hydrogen bonds between.

hbonds = HydrogenBondAnalysis(
    universe=u,
    between=[
        ["protein", "resname TIP3"], # for protein-water hbonds
        ["protein", "protein"]       # for protein-protein hbonds
    ]
)

hbonds.run(verbose=True)

Note

The Universe we are analysing has the water removed. The above example is for illustrative purposes only.

References

[1] Richard J. Gowers, Max Linke, Jonathan Barnoud, Tyler J. E. Reddy, Manuel N. Melo, Sean L. Seyler, Jan Domański, David L. Dotson, Sébastien Buchoux, Ian M. Kenney, and Oliver Beckstein. MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations. Proceedings of the 15th Python in Science Conference, pages 98–105, 2016. 00152. URL: https://conference.scipy.org/proceedings/scipy2016/oliver_beckstein.html, doi:10.25080/Majora-629e541a-00e.

[2] Naveen Michaud-Agrawal, Elizabeth J. Denning, Thomas B. Woolf, and Oliver Beckstein. MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. Journal of Computational Chemistry, 32(10):2319–2327, July 2011. 00778. URL: http://doi.wiley.com/10.1002/jcc.21787, doi:10.1002/jcc.21787.

[3] Paul Smith, Robert M. Ziolek, Elena Gazzarrini, Dylan M. Owen, and Christian D. Lorenz. On the interaction of hyaluronic acid with synovial fluid lipid membranes. Phys. Chem. Chem. Phys., 21(19):9845-9857, 2018. URL: http://dx.doi.org/10.1039/C9CP01532A

[4] Oliver Beckstein, Elizabeth J. Denning, Juan R. Perilla, and Thomas B. Woolf. Zipping and Unzipping of Adenylate Kinase: Atomistic Insights into the Ensemble of Open↔Closed Transitions. Journal of Molecular Biology, 394(1):160–176, November 2009. 00107. URL: https://linkinghub.elsevier.com/retrieve/pii/S0022283609011164, doi:10.1016/j.jmb.2009.09.009.