NeEMO - NEtwork Enthalpic MOdelling

Quick Help and References

NeEMO (NEtwork Enthalpic MOdelling) is a tool for the evaluation of stability changes in proteins caused by amino-acid (AA) mutations. The software is based on a neural-network trained on PDBs and a curated version [1] of the ProTherm database [2]. The effective prediction is obtained by means of residue-residue interaction networks (RINs) [3], a graph where nodes describe AA as vertices and edges are the chemical and statistical relationships between vertices. The picture shows briefly the entire prediction process

Basic flowchart in NeEMO
The tool adopts a two step process:
  • 1. Generation of RINS: when the user specify the protein of interest, NEEMO computes the corresponding RINS. This process will take a few minutes.
  • 2. Prediction of the mutant amino-acids: once the RIN is computed, the user can test the mutant effects very quickly and re-test other mutations.
E-Mail address
This is both needed for identification purposes. Please check that it is typed correctly.

Input page 1: PDB structure
PDB file: NeEMO requires a PDB file in order to compute the corresponding RIN. The user can either specify the PDB id, or upload it (this enables the user to consider synthetic structures or mutants). Chain ID: this option is used for the selection of the PDB chain that need to be analyzed be NEEMO. If not specified, the tool will focus on the first chain.

Input page 2: Mutations
Mutant: after the computation of the RIN, the tool shows information about the PDB primary sequence, and allows the input of mutations. You can add mutations quickly to the textbox in the following form: XiY where X is the wild type residue (uppercase), i is the amino acid position in the PDB file and Y is the mutant (uppercase) . It is vital that you use the PDB numbering.

If you are unsure about PDB numbering or you would like to know the solvent accessibility of the mutation you can add mutations by clicking the "Add mutation(s)" button and multiple additions are possible.
PH: this represents the environment pH where the protein is placed. Default value is 8.
Temperature: the temperature of the environment where the protein is located (Celcius). Default value is 20° C.

NEEMO will report the predicted DDG (kcal/mol) changes for every mutant amino acid specified by the user. Note that it is possible to test additional mutations after the output page.

Below is the link to a sample output of NeEMO server.

Example   -    the RIN of the Bovin Phospholipase A2 (PDB id: 1BP2). The user can test any mutation, as described in the previous section.


If you use the server in work leading to publications, please cite:
  • NeEMO method:
    Manuel Giollo, Alberto J M Martin, Ian Walsh, Carlo Ferrari, Silvio C E Tosatto.
    NeEMO: a method using residue interaction networks to improve prediction of protein stability upon mutation, BMC Genomics, 15, art. no. S7. (2014)

  1. Y. Dehouck, A. Grosfils, B. Folch, D. Gilis, P. Bogaerts, and M. Rooman, "Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0" Bioinforma. Oxf. Engl., vol. 25, no. 19, pp. 2537-2543, Oct. 2009.
  2. K. A. Bava, M. M. Gromiha, H. Uedaira, K. Kitajima, and A. Sarai, "ProTherm, version 4.0: thermodynamic database for proteins and mutants," Nucleic Acids Res., vol. 32, no. Database issue, pp. D120-121, Jan. 2004.
  3. A. J. M. Martin, M. Vidotto, F. Boscariol, T. Di Domenico, I. Walsh, and S. C. E. Tosatto, "RING: networking interacting residues, evolutionary information and energetics in protein structures," Bioinformatics, vol. 27, no. 14, pp. 2003-2005, Jul. 2011.

Supplementary Materials NEEMO's supplementary materials can be downloaded as pdf here.

(c)   Manuel Giollo , Alberto J. Martin Martin , Ian Walsh and Silvio Tosatto for Biocomputing UP,    10 / 2013