BMC Genomics 2009, 10(Suppl 3):S19 http://www.biomedcentral.com/1471-2164/10/S3/S19 change (ΔΔG) between the wild type and the mutated PGIPs. In order to obtain experimentally relevant informa- tion concerning the thermodynamic properties of binding, we wish to work in future, with advanced simulation methods such as free energy perturbation or thermody- namic integration to assess the binding free energy changes upon mutation of the important residues in PGIP. Conclusion It has been noted from our study on sequence analysis that 50% of the sequence variation between PvPGIP1 and PvPGIP2 fall in the non-LRR region whereas only 15% of the variation in GmPGIP3 with PvPGIP2 fall in the non-LRR region. This observation suggests specific regions in PGIPs favourable for the introduction of variation in recognition of the pathogen molecules. Structural studies involving docking techniques suggest the mode of binding of the fungal enzyme FmPG by PGIP2 from Phaseolus vulgaris to be similar to that of its homologue PGIP3 from Glycine max. In each case of binding, the active site of the enzyme from Fusarium moniliforme is being blocked by the PGIP molecule, supporting the experimentally observed phenomenon of these PGIP molecules being able to inhibit the fungal enzyme upon invasion. PGIP1 from the same plant Phaseolus vulgaris which is incapable of inhibiting FmPG, binds to FmPG in an evidently different mode, although PvPGIP1 and PvPGIP2 share a higher degree of sequence similarity compared to PvPGIP2 and GmPGIP3. Electro- static surface potential reveals considerable difference in the interacting surface of PvPGIP1 when compared to PvPGIP2 or GmPGIP3. Thus, electrostatic and van der Waals interactions may play a significant role in PGIPs for proper recognition and discrimination of PGs. Method Sequence analysis The sequences of the three PGIPs, namely PvPGIP1, PvPGIP2 and GmPGIP3 were retrieved from NCBI. We used the Pfam domain search program [23] to determine the domain architecture of these proteins. The plant specific Leucine-rich Repeats (PS_LRR) in the proteins were identified by the program PATMATDB of EMBOSS [24] using the pattern [ILVF]xx[ILVF]xx[ILVF]x [ILVF]xx [NTSC]x [ILVF] [TS]GxIPxx[ILVF]Gx as a regular expres- sion. Pairwise alignments, one between PvPGIP1 and PvPGIP2 and another between GmPGIP3 and PvPGIP2 were carried out by the program NEEDLE of EMBOSS. All the nine repeats identified by Pfam were aligned by CLUSTALW [36] for the three proteins, individually. Modelling Homology models of PvPGIP1 and GmPGIP3 were generated using MODELLER 9v4 [37] by satisfying the spatial restraints, based on the homology they share with the protein PvPGIP2 (PDB Id: 1OGQ). The best model was selected using PROCHECK [25] based on steric correctness. Energy minimization was performed for all the structures that were involved in our studies, with the help of GROMACS 3.3.3 [38,39]. The four protein molecules namely, the models of PvPGIP1 and GmPGIP3 and the crystal structure of PvPGIP2 and the fungal enzyme FmPG (PDB Id: 1HG8) were embedded in a box of simple point charge water molecules with 1 nm separation between the box boundary and the solute. Energy minimization of solvent with the solute fixed was carried out with 500 steps of steepest descent followed by 2000 steps of conjugate gradient algorithm. After that the constraint on the solute was released and energy minimization of the whole system was carried out again with 500 steps of steepest descent followed by 2000 steps of conjugate gradient algorithm. The resulting structures were sub- jected to 1 ns of molecular dynamics (MD) simulations in GROMACS at 300 K. For all the simulations GROMOS96 43a1 force field was used. The model structures of PvPGIP1 and GmPGIP3 have been deposited to PMDB Protein Model Database http:// mi.caspur.it/PMDB/ with the PMDB identifier of PM0075783 and PM0075784 respectively. Docking studies We have used GRAMM-X Protein Docking Web Server v.1.2.0 [26] for docking the three PGIP molecules to PG taken one at a time. The output PDB file that GRAMM-X produces contains 10 models ranked as the most probable prediction candidates according to the scoring function used by the program. The PGIPs acted as receptors while the PG acted as ligand in this study of protein-protein interaction. To select a model out of the ten top scoring docked complexes that GRAMM-X reported, we studied the associated change in Solvent Accessible Surface Area (SASA) of the amino acid residues in the individual molecules and when they are in the complex. We used the g_sas program in GROMACS to estimate the change in SASA for the individual residues of the proteins. Mutation prediction studies We have used mutation prediction tool [40] of the WHAT IF [30] web interface to mutate Q (224) of PvPGIP2 to K in the PvPGIP2-FmPG complex. The same mutation (Q224K) and five others that differ in PvPGIP1 were carried out on PvPGIP2 by using the same server. Page 10 of 12 (page number not for citation purposes)