Task 10 - Normal Mode Analysis
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, 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:
Two original papers can be viewed here:
An interesting application of ENM can be found in the JMB article by Silke Wieninger (see reference section at the end; Alex I can provide you with the PDF file).
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:
For each server, calculate and analyze the lowest five (to ten) 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 to 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 some modes (provided by server or using for example PyMol or VMD). Choose between 2-10 modes you believe are interesting and describe what movements you observe: hinge-movement, “breathing”…
- Which regions of your protein are most flexible, most stable?
- Define domains for your protein based on correlated motions using WebNM@. 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.
- Try the comparison/upload of second structure option, if: (i) you have PDB structures in different conformations or (ii) your protein has a bound ligand. Then either upload a structure with and one without the ligand, or delete the ligand in your structure. Note: Due to the force field that considers only C_alpha atoms, only changes in the backbone will give results. The model does not resolve changes in side-chain positions or SNPs.
- What are the advantages and disadvantages of NMA compared to MD?
Here are some other servers:
Nathalie Reuter, Konrad Hinsen & Jean-Jacques Lacapère. (2003) Transconformations of the SERCA1 Ca-ATPase: A Normal Mode Study. Biophys J 85(4): 2186–2197.
Siv Midtun Hollup, Gisle Salensminde & Nathalie Reutercorresponding. (2005) WEBnm@: a web application for normal mode analyses of proteins. BMC Bioinformatics 6: 52.
Karsten Suhre & Yves-Henri Sanejouand. (2004) ElNemo: a normal mode web-server for protein movement analysis and the generation of templates for molecular replacement. Nucleic Acids Research 32 (suppl 2): W610-W614.
Silke A. Wieninger, Engin H. Serpersu & G. Matthias Ullmann. (2011) ATP Binding Enables Broad Antibiotic Selectivity of Aminoglycoside Phosphotransferase(3′)-IIIa: An Elastic Network Analysis. J Mol Biol 409(3):450-65.
William Humphrey, Andrew Dalke & Klaus Schulten. (1996) VMD: visual molecular dynamics. J Mol Graph14(1):33-8, 27-8.
The PyMOL Molecular Graphics System, Version 184.108.40.206 Schrödinger, LLC.