Task 9 - Normal Mode Analysis

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Several experimental techniques, such as X-ray crystallography, NMR and spectroscopy, can provide information on the structure and dynamics of biological macromolecules, in our case proteins. However, experimental methods are often time-consuming and do not provide a complete picture of the dynamic properties of proteins. Structural bioinformatics can complement experimental methods.

Molecular dynamics (MD) simulations provide invaluable insight into protein dynamics considering the full range of harmonic and anharmonic motions at the atomic level. However, as you have found out by now, MD simulations are computational expensive. Typical simulations sample conformational motions on the nanosecond timescale.

Normal mode analysis (NMA), on the other hand, has been used successfully to determine and investigate large global motions of proteins. In NMA, the protein is modeled as a harmonic system oscillating around a stable equilibrium. Anharmonic motions are neglected. The low-frequency modes correspond to collective motions of the complete protein.
The first NMA of a protein used an all-atom representation of bovine pancreatic trypsin inhibitor (BPTI). You can have a look at the papers here:
Brooks & Karplus 1983
Go, Noguti & Nishikawa 1983

Elastic network models (among them Gaussian and anisotropic network models) greatly reduce the memory requirements for NMA. In 1996, Monique Tirion introduced this simplified model that was further developed by several others during the next years. You can find a short overview here:
http://mmb.pcb.ub.es/FlexServ/help/NMA.php
Two original papers can be viewed here:
Tirion 1996
Hinsen 1998


Introductory talks

The talk gives an introduction to normal mode analysis:

Tasks and questions

In this task you will analyze your protein structure using elastic network models. You will use two servers to calculate the normal modes:

WEBnm@ and ElNemo

For each server, calculate and analyze at least the lowest five normal modes. If possible (for ElNemo), use a cutoff for Cα atom pairs of 10 Å. Note: ElNemo reads only the ATOM record from the PDB file. If your protein has a ligand which is given as HETATM, you need to change this ATOM, if it should be accounted for in the normal mode calculation.

  • What information do the different servers provide?
  • How are the normal modes calculated, that is from which part of the structure? How many normal modes could in principle be calculated for your protein without any cutoff.
  • Visualize the modes (provided by server or using for example PyMol or VMD) and describe what movements you observe: hinge-movement, “breathing”…
  • Which regions of your protein are most flexible, most stable?
  • Can you identify domains for your protein? Compare to the CATH, SCOP and Pfam domains of your protein.
  • Can you observe notable differences between the normal modes calculated by the different servers?
  • For WEBnm@ try the amplitude scaling and vectors option.
  • When your MD simulations are finished, compare the lowest-frequency normal modes with your MD simulation using visualization software, e.g. PyMol or VMD. Can you observe different movements or similar dynamics? If possible, compare an overlay of the lowest-frequency modes to your MD simulation. You can superimpose the normal modes for example in VMD.
  • What are the advantages and disadvantages of NMA compared to MD?






Parameters

  • Calculate the 10 lowest-frequency normal modes (the six zero modes have to be considered for a few applications).
  • In most cases you can upload the original .pdb file from the Protein Data Bank. In some cases, however, you can upload only the structure itself (ATOM lines of the .pdb file).


WEBnm@

http://apps.cbu.uib.no/webnma/home

  • try the amplitude scaling and vectors option


ElNemo

http://www.igs.cnrs-mrs.fr/elnemo/start.html


Some of these servers provide a concise introduction to the theory behind NMA:


Anisotropic Network Model web server

http://ignmtest.ccbb.pitt.edu/cgi-bin/anm/anm1.cgi

  • set the distance weight to 3.0
  • try the amplitude scaling and vectors option
  • have a look at the different ANM model cutoffs


oGNM – Gaussian network model

http://ignm.ccbb.pitt.edu/GNM_Online_Calculation-t.htm

  • set the cutoff to 15 Å

we found an alternative link which works (maybe it's the same):

http://ignm.ccbb.pitt.edu/Online_GNM.htm


It appears to be the same. Thank you!

I found even another link:

http://ignm.ccbb.pitt.edu/Online_GNM.htm

which also seems to be working. The first link which is currently not working is the one specified in the original paper (http://www.ncbi.nlm.nih.gov/pubmed/16845002) and also on the website of the Bahar group (http://www.csb.pitt.edu/Faculty/bahar/index.php). When you find out about such problems, I am sure the group will appreciate it very much, if you inform them.

NOMAD-Ref

http://lorentz.dynstr.pasteur.fr/nma/submission.php

  • set the distance weight to 3.0
  • set the cutoff to 15 Å


All-atom NMA using Gromacs on the NOMAD-Ref server

http://lorentz.dynstr.pasteur.fr/gromacs/nma_submission.php

  • All-atom calculations are only supported for small proteins of up to 2,000 atoms. Use for example BPTI, PDB entry: 1BPT. Upload a .pdb file that contains only the ATOM lines of the original .pdb file. You can also choose another small protein for the all-atom NMA.
  • set the temperature to 600K and 2000K
  • you can visualize the modes with PyMol or VMD.
  • Compare the all-atom NMA of BPTI (or your chosen protein) with an elastic network calculation, e.g. NOMAD-Ref.
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